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  • 1. Abtahi, F.
    et al.
    Gyllesten, I. C.
    Lindecrantz, Kaj
    University of Borås, School of Engineering.
    Seoane, Fernando
    University of Borås, School of Engineering.
    Software Tool for Analysis of Breathing Related Errors in Transthoracic Electrical Bioimpedance Spectroscopy Measurements2012Conference paper (Refereed)
  • 2. Abtahi, F
    et al.
    Seoane, F
    University of Borås, School of Engineering.
    Lindecrantz, K
    University of Borås, School of Engineering.
    Electrical bioimpedance spectroscopy in time-variant systems: Is undersampling always a problem?2014In: Journal of Electrical Bioimpedance, ISSN 1891-5469, E-ISSN 1891-5469, Vol. 5, no 1, p. 28-33Article in journal (Refereed)
    Abstract [en]

    During the last decades, Electrical Bioimpedance Spectroscopy (EBIS) has been applied mainly by using the frequency-sweep technique, across a range of many different applications. Traditionally, the tissue under study is considered to be time-invariant and dynamic changes of tissue activity are ignored by treating the changes as a noise source. A new trend in EBIS is simultaneous electrical stimulation with several frequencies, through the application of a multi-sine, rectangular or other waveform. This method can provide measurements fast enough to sample dynamic changes of different tissues, such as cardiac muscle. This high sampling rate comes at a price of reduction in SNR and the increase in complexity of devices. Although the frequency-sweep technique is often inadequate for monitoring the dynamic changes in a variant system, it can be used successfully in applications focused on the time-invariant or slowly-variant part of a system. However, in order to successfully use frequency-sweep EBIS for monitoring time-variant systems, it is paramount to consider the effects of aliasing and especially the folding of higher frequencies, on the desired frequency e.g. DC level. This paper discusses sub-Nyquist sampling of thoracic EBIS measurements and its application in the case of monitoring pulmonary oedema. It is concluded that by considering aliasing, and with proper implementation of smoothing filters, as well as by using random sampling, frequency-sweep EBIS can be used for assessing time-invariant or slowly-variant properties of time-variant biological systems, even in the presence of aliasing. In general, undersampling is not always a problem, but does always require proper consideration.

  • 3.
    Abtahi, Farhad
    et al.
    KTH, School of Technology and Health (STH). Karolinska Institute, Sweden.
    Anund, A.
    Fors, C.
    Seoane, Fernando
    KTH, School of Technology and Health (STH), Medical Engineering, Computer and Electronic Engineering. Karolinska Institute, Sweden.
    Lindecrantz, Kaj
    KTH, School of Technology and Health (STH), Medical Engineering, Computer and Electronic Engineering. Karolinska Institute, Sweden.
    Association of drivers’ sleepiness with heart rate variability: A pilot study with drivers on real roads2017In: EMBEC & NBC 2017, Springer, 2017, Vol. 65, p. 149-152Conference paper (Refereed)
    Abstract [en]

    Vehicle crashes lead to huge economic and social consequences, and one non-negligible cause of accident is driver sleepiness. Driver sleepiness analysis based on the monitoring of vehicle acceleration, steering and deviation from the road or physiological and behavioral monitoring of the driver, e.g., monitoring of yawning, head pose, eye blinks and eye closures, electroencephalogram, electrooculogram, electromyogram and electrocardiogram (ECG), have been used as a part of sleepiness alert systems. Heart rate variability (HRV) is a potential method for monitoring of driver sleepiness. Despite previous positive reports from the use of HRV for sleepiness detection, results are often inconsistent between studies. In this work, we have re-evaluated the feasibility of using HRV for detecting drivers’ sleepiness during real road driving. A database consists of ECG measurements from 10 drivers, driving during morning, afternoon and night sessions on real road were used. Drivers have reported their average sleepiness level by using the Karolinska sleepiness scale once every five minutes. Statistical analysis was performed to evaluate the potential of HRV indexes to distinguish between alert, first signs of sleepiness and severe sleepiness states. The results suggest that individual subjects show different reactions to sleepiness, which produces an individual change in HRV indicators. The results motivate future work for more personalized approaches in sleepiness detection.

  • 4.
    Abtahi, Farhad
    et al.
    Karolinska Institutet.
    Anund, Anna
    Fors, Carina
    Seoane, Fernando
    University of Borås, Faculty of Textiles, Engineering and Business. University of Borås, Faculty of Caring Science, Work Life and Social Welfare. Karolinska Institutet.
    Lindecrantz, Kaj
    University of Borås, Faculty of Textiles, Engineering and Business. Karolinska Institutet.
    Association of Drivers’ sleepiness with heart rate variability. A Pilot Study with Drivers on Real Road2017Conference paper (Other academic)
  • 5. Abtahi, Farhad
    et al.
    Aslamy, Benjamin
    Boujabir, I
    Seoane, Fernando
    University of Borås, School of Health Science.
    Lindecrantz, Kaj
    University of Borås, School of Engineering.
    An Affordable ECG and Respiration Monitoring System Based on Raspberry PI and ADAS1000: First Step towards Homecare Applications2014In: 16th Nordic-Baltic Conference on Biomedical Engineering / [ed] Mindedal H., Persson M., Springer International Publishing , 2014, p. 5-8Conference paper (Refereed)
    Abstract [en]

    Homecare is a potential solution for problems associated with an aging population. This may involve several physiological measurements, and hence a flexible but affordable measurement device is needed. In this work, we have designed an ADAS1000-based four-lead electrocardiogram (ECG) and respiration monitoring system. It has been implemented using Raspberry PI as a platform for homecare applications. ADuM chips based on iCoupler technology have been used to achieve electrical isolation as required by IEC 60601 and IEC 60950 for patient safety. The result proved the potential of Raspberry PI for the design of a compact, affordable, and medically safe measurement device. Further work involves developing a more flexible software for collecting measurements from different devices (measuring, e.g., blood pressure, weight, impedance spectroscopy, blood glucose) through Bluetooth or user input and integrating them into a cloud-based homecare system.

  • 6.
    Abtahi, Farhad
    et al.
    University of Borås, School of Health Science.
    Berndtsson, A
    University of Borås, School of Health Science.
    Abtahi, Shirin
    University of Borås, School of Health Science.
    Seoane, Fernando
    University of Borås, School of Health Science.
    Lindecrantz, Kaj
    KTH.
    Development and preliminary evaluation of an Android based heart rate variability biofeedback system2014Conference paper (Refereed)
    Abstract [en]

    The reduced Heart Rate Variability (HRV) is believed to be associated with several diseases such as congestive heart failure, diabetes and chronic kidney diseases (CKD). In these cases, HRV biofeedback may be a potential intervention method to increase HRV which in turn is beneficial to these patients. In this work, a real-time Android biofeedback application based on a Bluetooth enabled ECG and thoracic electrical bioimpedance (respiration) measurement device has been developed. The system performance and usability have been evaluated in a brief study with eight healthy volunteers. The result demonstrates real-time performance of system and positive effects of biofeedback training session by increased HRV and reduced heart rate. Further development of the application and training protocol is ongoing to investigate duration of training session to find an optimum length and interval of biofeedback sessions to use in potential interventions.

  • 7.
    Abtahi, Farhad
    et al.
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.
    Berndtsson, Andreas
    Abtahi, Shirin
    Seoane, Fernando
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.
    Lindecrantz, Kaj
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.
    Development and preliminary evaluation of an Android based heart rate variability biofeedback system2014In: Engineering in Medicine and Biology Society (EMBC), 2014 36th Annual International Conference of the IEEE, IEEE conference proceedings, 2014, p. 3382-3385Conference paper (Refereed)
    Abstract [en]

    The reduced Heart Rate Variability (HRV) is believed to be associated with several diseases such as congestive heart failure, diabetes and chronic kidney diseases (CKD). In these cases, HRV biofeedback may be a potential intervention method to increase HRV which in turn is beneficial to these patients. In this work, a real-time Android biofeedback application based on a Bluetooth enabled ECG and thoracic electrical bioimpedance (respiration) measurement device has been developed. The system performance and usability have been evaluated in a brief study with eight healthy volunteers. The result demonstrates real-time performance of system and positive effects of biofeedback training session by increased HRV and reduced heart rate. Further development of the application and training protocol is ongoing to investigate duration of training session to find an optimum length and interval of biofeedback sessions to use in potential interventions.

  • 8.
    Abtahi, Farhad
    et al.
    KTH, School of Technology and Health (STH), Patient Safety (Closed 20130701).
    Gyllensten, Illapha Cuba
    KTH, School of Technology and Health (STH).
    Lindecrantz, Kaj
    KTH, School of Technology and Health (STH), Medical sensors, signals and systems (MSSS) (Closed 20130701).
    Seoane, Fernando
    KTH, School of Technology and Health (STH), Medical sensors, signals and systems (MSSS) (Closed 20130701).
    Software tool for analysis of breathing-related errors in transthoracic electrical bioimpedance spectroscopy measurements2012In: Journal of Physics, Conference Series, ISSN 1742-6588, E-ISSN 1742-6596, Vol. 407, no 1, p. 012028-Article in journal (Refereed)
    Abstract [en]

    During the last decades, Electrical Bioimpedance Spectroscopy (EBIS) has been applied in a range of different applications and mainly using the frequency sweep-technique. Traditionally the tissue under study is considered to be timeinvariant and dynamic changes of tissue activity are ignored and instead treated as a noise source. This assumption has not been adequately tested and could have a negative impact and limit the accuracy for impedance monitoring systems. In order to successfully use frequency-sweeping EBIS for monitoring time-variant systems, it is paramount to study the effect of frequency-sweep delay on Cole Model-based analysis. In this work, we present a software tool that can be used to simulate the influence of respiration activity in frequency-sweep EBIS measurements of the human thorax and analyse the effects of the different error sources. Preliminary results indicate that the deviation on the EBIS measurement might be significant at any frequency, and especially in the impedance plane. Therefore the impact on Cole-model analysis might be different depending on method applied for Cole parameter estimation.

  • 9.
    Abtahi, Farhad
    et al.
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems. Karolinska Institutet, Sweden.
    Hilderman, Marie
    Bruchfeld, Annette
    Seoane, Fernando
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems. University of Borås, Sweden.
    Janerot-Sjöberg, Birgitta
    KTH, School of Technology and Health (STH), Medical Engineering, Medical Imaging. Karolinska Institutet, Sweden.
    Lindecrantz, Kaj
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems. Karolinska Institutet, Sweden.
    Pro-inflammatory Blood Markers and Heart Rate Variability in Apnoea as a Reflection of Basal Vagal ToneManuscript (preprint) (Other academic)
    Abstract [en]

    Pro-inflammatory cytokines play a crucial role in inflammatory response, which istightly regulated by the nervous system to avoid the damage caused by inflammation. There isevidence for a cholinergic anti-inflammatory pathway that includes afferent and efferent vagalnerves that sense the inflammation and stimulate the anti-inflammatory response. Non-functionalanti-inflammatory response might lead to excessive and chronic inflammation e.g., rheumatoidarthritis (RA), inflammatory bowel disease (IBD), and poor outcome. Heart rate variability(HRV) has been proposed as a potential tool to monitor the level of anti-inflammatory activitythrough the monitoring of vagal activity. In this paper, the association of pro-inflammatorymarkers with HRV indices is evaluated. We used a database called “Heart Biomarker Evaluationin Apnea Treatment (HeartBEAT)” that consists of 6±2 hours of Electrocardiogram (ECG)recordings during nocturnal sleep from 318 patients at baseline and 301of them at 3 monthsfollow-up. HRV indices are calculated from ECG recordings of 5-360 minutes. The results showa statistically significant correlation between heart rate (HR) and pro-inflammatory cytokines,independent of duration of ECG analysis. HRV indices e.g., standard deviation of all RRintervals (SDNN) show an inverse relation to the pro-inflammatory cytokines. Longer ECGrecordings show a higher potential to reflect the level of anti-inflammatory response. In light oftheories for the cholinergic anti-inflammatory pathway, a combination of HR and HRV as areflection of basal vagal activity might be a potential prognostic tool for interventional guidance.

  • 10.
    Abtahi, Farhad
    et al.
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.
    Ji, Guangchao
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.
    Lu, Ke
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.
    Rodby, Kristian
    Seoane, Fernando
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.
    A knitted garment using intarsia technique for Heart Rate Variability biofeedback: Evaluation of initial prototype2015In: Engineering in Medicine and Biology Society (EMBC), 2015 37th Annual International Conference of the IEEE, IEEE , 2015, Vol. 2015, p. 3121-3124Conference paper (Refereed)
    Abstract [en]

    Heart rate variability (HRV) biofeedback is a method based on paced breathing at specific rate called resonance frequency by giving online feedbacks from user respiration and its effect on HRV. Since the HRV is also influence by different factors like stress and emotions, stress related to an unfamiliar measurement device, cables and skin electrodes may cover the underling effect of such kind of intervention. Wearable systems are usually considered as intuitive solutions which are more familiar to the end-user and can help to improve usability and hence reducing the stress. In this work, a prototype of a knitted garment using intarsia technique is developed and evaluated. Results show the satisfactory level of quality for Electrocardiogram and thoracic electrical bioimpedance i.e. for respiration monitoring as a part of HRV biofeedback system. Using intarsia technique and conductive yarn for making the connection instead of cables will reduce the complexity of fabrication in textile production and hence reduce the final costs in a final commercial product. Further development of garment and Android application is ongoing and usability and efficiency of final prototype will be evaluated in detail.

  • 11.
    Abtahi, Farhad
    et al.
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.
    Ji, Guangchao
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.
    Lu, Ke
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.
    Rödby, Kristian
    Högskolan i Borås, Akademin för textil, teknik och ekonomi.
    Björlin, Anders
    Kiwok AB.
    Östlund, Anders
    Kiwok AB.
    Seoane, Fernando
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems. Högskolan i Borås, Akademin för vård, arbetsliv och välfärd.
    Lindecrantz, Kaj
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.
    Textile-Electronic Integration in Wearable Measurement Garments for Pervasive Healthcare Monitoring2015Conference paper (Other academic)
  • 12.
    Abtahi, Farhad
    et al.
    KTH-School of Technology and Health.
    Ji, Guangchao
    KTH-School of Technology and Health.
    Lu, Ke
    KTH-School of Technology and Health.
    Rödby, Kristian
    University of Borås, Faculty of Textiles, Engineering and Business.
    Björlin, Anders
    Kiwok AB.
    Östlund, Anders
    Kiwok AB.
    Seoane, Fernando
    University of Borås, Faculty of Caring Science, Work Life and Social Welfare. KTH-School of Technology and Health.
    Lindecrantz, Kaj
    KTH-School of Technology and Health.
    Textile-Electronic Integration in Wearable Measurement Garments for Pervasive Healthcare Monitoring2015Conference paper (Other academic)
  • 13.
    Abtahi, Farhad
    et al.
    KTH-School of Technology and Health.
    Ji, Guangchao
    KTH-School of Technology and Health.
    Lu, Ke
    KTH-School of Technology and Health.
    Rödby, Kristian
    University of Borås, Faculty of Textiles, Engineering and Business.
    Seoane, Fernando
    University of Borås, Faculty of Caring Science, Work Life and Social Welfare. KTH-School of Technology and Health.
    A knitted garment using intarsia technique for Heart Rate Variability biofeedback: Evaluation of initial prototype2015In: Proceedings of the 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2015, p. 3121-3124Conference paper (Refereed)
  • 14.
    Abtahi, Farhad
    et al.
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.
    Lindecrantz, Kaj
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.
    Seoane, Fernando
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.
    Aslamy, Benjamin
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.
    Boujabir, Imaneh
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.
    An Affordable ECG and Respiration Monitoring System Based on Raspberry PI and ADAS1000: First Step towards Homecare Applications2015In: 16th Nordic-Baltic Conference on Biomedical Engineering: 16. NBC & 10. MTD 2014 joint conferences. October 14-16, 2014, Gothenburg, Sweden, Springer, 2015, p. 5-8Conference paper (Refereed)
    Abstract [en]

    Homecare is a potential solution for problems associated with an aging population. This may involve several physiological measurements, and hence a flexible but affordable measurement device is needed. In this work, we have designed an ADAS1000-based four-lead electrocardiogram (ECG) and respiration monitoring system. It has been implemented using Raspberry PI as a platform for homecare applications. ADuM chips based on iCoupler technology have been used to achieve electrical isolation as required by IEC 60601 and IEC 60950 for patient safety. The result proved the potential of Raspberry PI for the design of a compact, affordable, and medically safe measurement device. Further work involves developing a more flexible software for collecting measurements from different devices (measuring, e.g., blood pressure, weight, impedance spectroscopy, blood glucose) through Bluetooth or user input and integrating them into a cloud-based homecare system.

  • 15.
    Abtahi, Farhad
    et al.
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.
    Lu, Ke
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.
    Dizon, M
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.
    Johansson, M
    KTH-School of Technology and Health.
    Seoane, Fernando
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems. Högskolan i Borås.
    Lindecrantz, Kaj
    KTH, School of Technology and Health (STH), Medical Engineering, Computer and Electronic Engineering. Högskolan i Borås, Akademin för vård, arbetsliv och välfärd.
    Evaluating Atrial Fibrillation Detection Algorithm based on Heart Rate Variability analysis2015In: Medicinteknikdagarna, Uppsala: Svensk förening för medicinsk teknik och fysik , 2015Conference paper (Refereed)
  • 16.
    Abtahi, Farhad
    et al.
    KTH-School of Technology and Health.
    Lu, Ke
    KTH-School of Technology and Health.
    Dizon, M
    KTH-School of Technology and Health.
    Johansson, M
    KTH-School of Technology and Health.
    Seoane, Fernando
    University of Borås, Faculty of Caring Science, Work Life and Social Welfare. KTH-School of Technology and Health.
    Lindecrantz, Kaj
    University of Borås, Faculty of Caring Science, Work Life and Social Welfare. KTH-School of Technology and Health.
    Evaluating Atrial Fibrillation Detection Algorithm based on Heart Rate Variability analysis2015In: Medicinteknikdagarna, Uppsala: Svensk förening för medicinsk teknik och fysik , 2015Conference paper (Refereed)
  • 17.
    Abtahi, Farhad
    et al.
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.
    Lu, Ke
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.
    Dizon, M
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.
    Johansson, M
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.
    Seoane, Fernando
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems. Högskolan i Borås, Akademin för vård, arbetsliv och välfärd.
    Lindecrantz, Kaj
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.
    Evaluation of Atrial Fibrillation Detection by using Heart Rate Variability analysis2015Conference paper (Other academic)
  • 18.
    Abtahi, Farhad
    et al.
    KTH-School of Technology and Health.
    Lu, Ke
    KTH-School of Technology and Health.
    Dizon, M
    KTH-School of Technology and Health.
    Johansson, M
    KTH-School of Technology and Health.
    Seoane, Fernando
    University of Borås, Faculty of Caring Science, Work Life and Social Welfare. KTH-School of Technology and Health.
    Lindecrantz, Kaj
    University of Borås, Faculty of Caring Science, Work Life and Social Welfare. KTH-School of Technology and Health.
    Evaluation of Atrial Fibrillation Detection by using Heart Rate Variability analysis2015Conference paper (Other academic)
  • 19.
    Abtahi, Farhad
    et al.
    KTH-School of Technology and Health.
    Lu, Ke
    KTH-School of Technology and Health.
    Guangchao, Li
    KTH-School of Technology and Health.
    Rödby, Kristian
    University of Borås, Faculty of Textiles, Engineering and Business.
    Seoane, Fernando
    University of Borås, Faculty of Caring Science, Work Life and Social Welfare. KTH-School of Technology and Health.
    A Knitted Garment using Intarsia Technique for Heart Rate Variability Biofeedback: Evaluation of Initial Prototype.2015Conference paper (Other academic)
  • 20.
    Abtahi, Farhad
    et al.
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.
    Lu, Ke
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.
    Guangchao, Li
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.
    Rödby, Kristian
    Högskolan i Borås, Akademin för textil, teknik och ekonomi.
    Seoane, Fernando
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems. Högskolan i Borås.
    A Knitted Garment using Intarsia Technique for Heart Rate Variability Biofeedback: Evaluation of Initial Prototype.2015Conference paper (Other academic)
  • 21.
    Abtahi, Farhad
    et al.
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.
    Seoane, Fernando
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.
    Lindecrantz, Kaj
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.
    Electrical bioimpedance spectroscopy in time-variant systems: Is undersampling always a problem?2014In: Journal of Electrical Bioimpedance, ISSN 1891-5469, Vol. 5, no 1, p. 28-33Article in journal (Refereed)
    Abstract [en]

    During the last decades, Electrical Bioimpedance Spectroscopy (EBIS) has been applied mainly by using the frequency-sweep technique, across a range of many different applications. Traditionally, the tissue under study is considered to be time-invariant and dynamic changes of tissue activity are ignored by treating the changes as a noise source. A new trend in EBIS is simultaneous electrical stimulation with several frequencies, through the application of a multi-sine, rectangular or other waveform. This method can provide measurements fast enough to sample dynamic changes of different tissues, such as cardiac muscle. This high sampling rate comes at a price of reduction in SNR and the increase in complexity of devices. Although the frequency-sweep technique is often inadequate for monitoring the dynamic changes in a variant system, it can be used successfully in applications focused on the time-invariant or slowly-variant part of a system. However, in order to successfully use frequency-sweep EBIS for monitoring time-variant systems, it is paramount to consider the effects of aliasing and especially the folding of higher frequencies, on the desired frequency e.g. DC level. This paper discusses sub-Nyquist sampling of thoracic EBIS measurements and its application in the case of monitoring pulmonary oedema. It is concluded that by considering aliasing, and with proper implementation of smoothing filters, as well as by using random sampling, frequency-sweep EBIS can be used for assessing time-invariant or slowly-variant properties of time-variant biological systems, even in the presence of aliasing. In general, undersampling is not always a problem, but does always require proper consideration.

  • 22.
    Abtahi, Farhad
    et al.
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.
    Seoane, Fernando
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.
    Lindecrantz, Kaj
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.
    Löfgren, Nils
    Elimination of ECG Artefacts in Foetal EEG Using Ensemble Average Subtraction and Wavelet Denoising Methods: A Simulation2014In: XIII Mediterranean Conference on Medical and Biological Engineering and Computing 2013, Springer, 2014, p. 551-554Conference paper (Refereed)
    Abstract [en]

    Biological signals recorded from surface electrodes contain interference from other signals which are not desired and should be considered as noise. Heart activity is especially present in EEG and EMG recordings as a noise. In this work, two ECG elimination methods are implemented; ensemble average subtraction (EAS) and wavelet denoising methods. Comparison of these methods has been done by use of simulated signals achieved by adding ECG to neonates EEG. The result shows successful elimination of ECG artifacts by using both methods. In general EAS method which remove estimate of all ECG components from signal is more trustable but it is also harder for implementation due to sensitivity to noise. It is also concluded that EAS behaves like a high-pass filter while wavelet denoising method acts as low-pass filter and hence the choice of one method depends on application.

  • 23.
    Abtahi, Farhad
    et al.
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.
    Snäll, Jonatan
    KTH, School of Technology and Health (STH).
    Aslamy, Benjamin
    KTH, School of Technology and Health (STH).
    Abtahi, Shirin
    KTH, School of Technology and Health (STH).
    Seoane, Fernando
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems. University of Boras, Sweden.
    Lindecrantz, Kaj
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems. Karolinska Institute, Sweden.
    Biosignal PI, an Affordable Open-Source ECG and Respiration Measurement System2014In: Sensors, ISSN 1424-8220, E-ISSN 1424-8220, Vol. 15, no 1, p. 93-109Article in journal (Refereed)
    Abstract [en]

    Bioimedical pilot projects e.g., telemedicine, homecare, animal and human trials usually involve several physiological measurements. Technical development of these projects is time consuming and in particular costly. A versatile but affordable biosignal measurement platform can help to reduce time and risk while keeping the focus on the important goal and making an efficient use of resources. In this work, an affordable and open source platform for development of physiological signals is proposed. As a first step an 8–12 leads electrocardiogram (ECG) and respiration monitoring system is developed. Chips based on iCoupler technology have been used to achieve electrical isolation as required by IEC 60601 for patient safety. The result shows the potential of this platform as a base for prototyping compact, affordable, and medically safe measurement systems. Further work involves both hardware and software development to develop modules. These modules may require development of front-ends for other biosignals or just collect data wirelessly from different devices e.g., blood pressure, weight, bioimpedance spectrum, blood glucose, e.g., through Bluetooth. All design and development documents, files and source codes will be available for non-commercial use through project website, BiosignalPI.org.

  • 24. Abtahi, Farhad
    et al.
    Snäll, Jonathan
    Aslamy, Benjamin
    Abtahi, Shirin
    Seoane, Fernando
    University of Borås, Faculty of Caring Science, Work Life and Social Welfare. KTH-School of Technology and Health.
    Lindecrantz, Kaj
    University of Borås, Faculty of Caring Science, Work Life and Social Welfare. KTH-School of Technology and Health.
    Biosignal PI, an Affordable Open-Source ECG and Respiration Measurement System2015In: Sensors, ISSN 1424-8220, E-ISSN 1424-8220, Vol. 15, no 1, p. 93-109Article in journal (Refereed)
    Abstract [en]

    Bioimedical pilot projects e.g., telemedicine, homecare, animal and human trials usually involve several physiological measurements. Technical development of these projects is time consuming and in particular costly. A versatile but affordable biosignal measurement platform can help to reduce time and risk while keeping the focus on the important goal and making an efficient use of resources. In this work, an affordable and open source platform for development of physiological signals is proposed. As a first step an 8–12 leads electrocardiogram (ECG) and respiration monitoring system is developed. Chips based on iCoupler technology have been used to achieve electrical isolation as required by IEC 60601 for patient safety. The result shows the potential of this platform as a base for prototyping compact, affordable, and medically safe measurement systems. Further work involves both hardware and software development to develop modules. These modules may require development of front-ends for other biosignals or just collect data wirelessly from different devices e.g., blood pressure, weight, bioimpedance spectrum, blood glucose, e.g., through Bluetooth. All design and development documents, files and source codes will be available for non-commercial use through project website, BiosignalPI.org.

  • 25. Atefi, S. R.
    et al.
    Seoane, Fernando
    University of Borås, School of Engineering.
    Lindecrantz, Kaj
    University of Borås, School of Engineering.
    Electrical Bioimpedance Cerebral Monitoring.: Preliminary Results from Measurements on Stroke Patients2012Conference paper (Refereed)
    Abstract [en]

    Electrical Bioimpedance Spectroscopy (EBIS) is currently used in different tissue characterization applications. In this work we aim to use EBIS to study changes in electrical properties of the cerebral tissues after an incident of hemorrhage/ischemic stroke. To do so a case-control study was conducted using six controls and three stroke cases. The preliminary results of this study show that by using Cole-based analysis on EBIS measurements and analyzing the Cole parameters R0 and R∞, it is possible to detect changes on electrical properties of cerebral tissue after stroke.

  • 26.
    Atefi, Seyed Reza
    et al.
    KTH, School of Technology and Health (STH), Medical sensors, signals and systems (MSSS) (Closed 20130701).
    Buendia, Ruben
    KTH, School of Technology and Health (STH), Medical sensors, signals and systems (MSSS) (Closed 20130701).
    Lindecrantz, Kaj
    KTH, School of Technology and Health (STH), Medical sensors, signals and systems (MSSS) (Closed 20130701).
    Seoane, Fernando
    KTH, School of Technology and Health (STH), Medical sensors, signals and systems (MSSS) (Closed 20130701).
    Cole Function and Conductance-Based Parasitic Capacitance Compensation for Cerebral Electrical Bioimpedance Measurements2012In: Engineering in Medicine and Biology Society (EMBC), 2012 Annual International Conference of the IEEE, San Diego: IEEE press , 2012, p. 3368-3371Conference paper (Refereed)
    Abstract [en]

    One of the most common measurement artifacts present in Electrical Bioimpedance Spectroscopy measurements (EBIS) comes from the capacitive leakage effect resulting from parasitic stray capacitances. This artifact produces a deviation in the measured impedance spectrum that is most noticeable at higher frequencies. The artifact taints the spectroscopy measurement increasing the difficulty of producing reliable EBIS measurements at high frequencies. In this work, an approach for removing such capacitive influence from the spectral measurement is presented making use of a novel method to estimate the value of the parasitic capacitance equivalent that causes the measurement artifact. The proposed method has been tested and validated theoretically and experimentally and it gives a more accurate estimation of the value of the parasitic capacitance than the previous methods. Once a reliable value of parasitic capacitance has been estimated the capacitive influence can be easily compensated in the EBIS measured data. Thus enabling analysis of EBIS data at higher frequencies, i.e. in the range of 300-500 kHz like measurements intended for cerebral monitoring, where the characteristic frequency is remarkably higher than EBIS measurements i.e. within the range 30 to 50 kHz, intended for body composition assessment.

  • 27. Atefi, Seyed Reza
    et al.
    Seoane, Fernando
    University of Borås, School of Health Science.
    The Emergence of Electrical Bioimpedance Monitoring for Prompt Detection of Stroke Damage2014Conference paper (Refereed)
  • 28.
    Atefi, Seyed Reza
    et al.
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.
    Seoane, Fernando
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.
    Kamalian, Shervin
    Rosenthal, Eric
    Lev, Michael
    Bonmassar, Giorgio
    Intracranial haemorrhage alters scalp potential distributions in bioimpedance cerebral monitoring applications: preliminary results from FEM simulation on a realistic head model and human subjects2016In: Medical Physics, ISSN 2473-4209, Vol. 43, no 2, p. 675-686Article in journal (Refereed)
    Abstract [en]

    Purpose: Current diagnostic neuroimaging for detection of intracranial hemorrhage (ICH) is limited to fixed scanners requiring patient transport and extensive infrastructure support. ICH diagnosis would therefore benefit from a portable diagnostic technology, such as electrical bioimpedance (EBI). Through simulations and patient observation, the authors assessed the influence of unilateral ICH hematomas on quasisymmetric scalp potential distributions in order to establish the feasibility of EBI technology as a potential tool for early diagnosis. Methods: Finite element method (FEM) simulations and experimental leftright hemispheric scalp potential differences of healthy and damaged brains were compared with respect to the asymmetry caused by ICH lesions on quasisymmetric scalp potential distributions. In numerical simulations, this asymmetry was measured at 25 kHz and visualized on the scalp as the normalized potential difference between the healthy and ICH damaged models. Proof-of-concept simulations were extended in a pilot study of experimental scalp potential measurements recorded between 0 and 50 kHz with the authors custom-made bioimpedance spectrometer. Mean leftright scalp potential differences recorded from the frontal, central, and parietal brain regions of ten healthy control and six patients suffering from acute/subacute ICH were compared. The observed differences were measured at the 5% level of significance using the two-sample Welch ttest. Results: The 3D-anatomically accurate FEM simulations showed that the normalized scalp potential difference between the damaged and healthy brain models is zero everywhere on the head surface, except in the vicinity of the lesion, where it can vary up to 5%. The authors preliminary experimental results also confirmed that the leftright scalp potential difference in patients with ICH (e.g., 64 mV) is significantly larger than in healthy subjects (e.g., 20.8 mV; P < 0.05). Conclusions: Realistic, proof-of-concept simulations confirmed that ICH affects quasisymmetric scalp potential distributions. Pilot clinical observations with the authors custom-made bioimpedance spectrometer also showed higher leftright potential differences in the presence of ICH, similar to those of their simulations, that may help to distinguish healthy subjects from ICH patients. Although these pilot clinical observations are in agreement with the computer simulations, the small sample size of this study lacks statistical power to exclude the influence of other possible confounders such as age, ex, and electrode positioning. The agreement with previously published simulation-based and clinical results, however, suggests that EBI technology may be potentially useful for ICH detection. © 2016 American Association of Physicists in Medicine.

  • 29.
    Atefi, Seyed Reza
    et al.
    Harvard Univsersity.
    Seoane, Fernando
    University of Borås, Faculty of Caring Science, Work Life and Social Welfare. KTH-School of Technology and Health.
    Kamalian, Shervin
    Rosenthal, Eric
    Lev, Michael
    Massachussets University Hospital.
    Bonmassar, Giorgio
    Harvard University.
    Intracranial haemorrhage alters scalp potential distributions in bioimpedance cerebral monitoring applications: preliminary results from FEM simulation on a realistic head model and human subjects2016In: Medical Physics, ISSN 0094-2405, Vol. 43, no 2, p. 675-686Article in journal (Refereed)
    Abstract [en]

    Purpose:

    Current diagnostic neuroimaging for detection of intracranial hemorrhage (ICH) is limited to fixed scanners requiring patient transport and extensive infrastructure support. ICH diagnosis would therefore benefit from a portable diagnostic technology, such as electrical bioimpedance (EBI). Through simulations and patient observation, the authors assessed the influence of unilateral ICH hematomas on quasisymmetric scalp potential distributions in order to establish the feasibility of EBI technology as a potential tool for early diagnosis.

    Methods:

    Finite element method(FEM) simulations and experimental left–right hemispheric scalp potential differences of healthy and damaged brains were compared with respect to the asymmetry caused by ICH lesions on quasisymmetric scalp potential distributions. In numerical simulations, this asymmetry was measured at 25 kHz and visualized on the scalp as the normalized potential difference between the healthy and ICH damaged models. Proof-of-concept simulations were extended in a pilot study of experimental scalp potential measurements recorded between 0 and 50 kHz with the authors’ custom-made bioimpedance spectrometer. Mean left–right scalp potential differences recorded from the frontal, central, and parietal brain regions of ten healthy control and six patients suffering from acute/subacute ICH were compared. The observed differences were measured at the 5% level of significance using the two-sample Welch t-test.

    Results:

    The 3D-anatomically accurate FEM simulations showed that the normalized scalp potential difference between the damaged and healthy brainmodels is zero everywhere on the head surface, except in the vicinity of the lesion, where it can vary up to 5%. The authors’ preliminary experimental results also confirmed that the left–right scalp potential difference in patients with ICH (e.g., 64 mV) is significantly larger than in healthy subjects (e.g., 20.8 mV; P < 0.05).

    Conclusions:

    Realistic, proof-of-concept simulations confirmed that ICH affects quasisymmetric scalp potential distributions. Pilot clinical observations with the authors’ custom-made bioimpedance spectrometer also showed higher left–right potential differences in the presence of ICH, similar to those of their simulations, that may help to distinguish healthy subjects from ICH patients. Although these pilot clinical observations are in agreement with the computer simulations, the small sample size of this study lacks statistical power to exclude the influence of other possible confounders such as age, sex, and electrode positioning. The agreement with previously published simulation-based and clinical results, however, suggests that EBI technology may be potentially useful for ICH detection.

  • 30.
    Atefi, Seyed Reza
    et al.
    KTH, School of Technology and Health (STH), Medical sensors, signals and systems (MSSS).
    Seoane, Fernando
    KTH, School of Technology and Health (STH), Medical sensors, signals and systems (MSSS).
    Lindecrantz, Kaj
    KTH, School of Technology and Health (STH), Medical sensors, signals and systems (MSSS).
    Electrical Bioimpedance cerebral monitoring. Preliminary results from measurements on stroke patients2012In: Engineering in Medicine and Biology Society (EMBC), 2012 Annual International Conference of the IEEE, IEEE , 2012, p. 126-129Conference paper (Refereed)
    Abstract [en]

    Electrical Bioimpedance Spectroscopy (EBIS) is currently used in different tissue characterization applications. In this work we aim to use EBIS to study changes in electrical properties of the cerebral tissues after an incident of hemorrhage/ischemic stroke. To do so a case-control study was conducted using six controls and three stroke cases. The preliminary results of this study show that by using Cole-based analysis on EBIS measurements and analyzing the Cole parameters R0 and R∞, it is possible to detect changes on electrical properties of cerebral tissue after stroke. 

  • 31.
    Atefi, Seyed Reza
    et al.
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.
    Seoane, Fernando
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.
    Lindecrantz, Kaj
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.
    Study of the dynamics of transcephalic cerebral impedance data during cardio-vascular surgery2013In: XV International Conference on Electrical Bio-Impedance (ICEBI) & XIV Conference on Electrical Impedance Tomography (EIT), Institute of Physics (IOP), 2013, Vol. 434, no 1, p. 012045-Conference paper (Refereed)
    Abstract [en]

    Postoperative neurological deficits are one of the risks associated with cardio vascular surgery, necessitating development of new techniques for cerebral monitoring. In this study an experimental observation regarding the dynamics of transcephalic Electrical Bioimpedance (EBI) in patients undergoing cardiac surgery with and without extracorporeal circulation (ECC) was conducted to investigate the potential use of electrical Bioimpedance for cerebral monitoring in cardio vascular surgery. Tetrapolar transcephalic EBI measurements at single frequency of 50 kHz were recorded prior to and during cardio vascular surgery. The obtained results show that the transcephalic impedance decreases in both groups of patients as operation starts, however slight differences in these two groups were also observed with the cerebral impedance reduction in patients having no ECC being less common and not as pronounced as in the ECC group. Changes in the cerebral impedance were in agreement with changes of haematocrit and temperature. The origin of EBI changes is still unexplained however these results encourage us to continue investigating the application of electrical bioimpedance cerebral monitoring clinically.

  • 32.
    Atefi, Seyed Reza
    et al.
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.
    Seoane, Fernando
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.
    Thorlin, Thorleif
    Lindecrantz, Kaj
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.
    Stroke Damage Detection Using Classification Trees on Electrical Bioimpedance Cerebral Spectroscopy Measurements2013In: Sensors, ISSN 1424-8220, E-ISSN 1424-8220, Vol. 13, no 8, p. 10074-10086Article in journal (Refereed)
    Abstract [en]

    After cancer and cardio-vascular disease, stroke is the third greatest cause of death worldwide. Given the limitations of the current imaging technologies used for stroke diagnosis, the need for portable non-invasive and less expensive diagnostic tools is crucial. Previous studies have suggested that electrical bioimpedance (EBI) measurements from the head might contain useful clinical information related to changes produced in the cerebral tissue after the onset of stroke. In this study, we recorded 720 EBI Spectroscopy (EBIS) measurements from two different head regions of 18 hemispheres of nine subjects. Three of these subjects had suffered a unilateral haemorrhagic stroke. A number of features based on structural and intrinsic frequency-dependent properties of the cerebral tissue were extracted. These features were then fed into a classification tree. The results show that a full classification of damaged and undamaged cerebral tissue was achieved after three hierarchical classification steps. Lastly, the performance of the classification tree was assessed using Leave-One-Out Cross Validation (LOO-CV). Despite the fact that the results of this study are limited to a small database, and the observations obtained must be verified further with a larger cohort of patients, these findings confirm that EBI measurements contain useful information for assessing on the health of brain tissue after stroke and supports the hypothesis that classification features based on Cole parameters, spectral information and the geometry of EBIS measurements are useful to differentiate between healthy and stroke damaged brain tissue.

  • 33.
    Atefi, Seyed Reza
    et al.
    Harvard University.
    Seoane, Fernando
    University of Borås, Faculty of Caring Science, Work Life and Social Welfare. KTH-School of Technology and Health.
    Thorlin, Thorleif
    salhgrenska Hospital.
    Lindecrantz, Kaj
    KTH-School of Technology and Health.
    Stroke Damage Detection Using Classification Trees on Electrical Bioimpedance Cerebral Spectroscopy Measurements2013In: Sensors, ISSN 1424-8220, E-ISSN 1424-8220, Vol. 13, no 8, p. 10074-10086Article in journal (Refereed)
  • 34.
    Atefi, Seyed Reza
    et al.
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.
    Seoane, Fernando
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.
    Tomner, Jens
    Kostulas, Konstantinos
    Lindecrantz, Kaj
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.
    Bonmassar, Giorgio
    Stroke Pathogenesis Alters Dielectric Properties of Brain Tissue Supporting Electrical Bioimpedance Technology as a tool for Cerebral MonitoringManuscript (preprint) (Other academic)
  • 35. Ayllnon, David
    et al.
    Gil-Pita, Roberto
    Seoane, Fernando
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.
    Detection and Classification of Measurement Errors in Bioimpedance Spectroscopy2016In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 11, no 6, article id e0156522Article in journal (Refereed)
    Abstract [en]

    Bioimpedance spectroscopy (BIS) measurement errors may be caused by parasitic stray capacitance, impedance mismatch, cross-talking or their very likely combination. An accurate detection and identification is of extreme importance for further analysis because in some cases and for some applications, certain measurement artifacts can be corrected, minimized or even avoided. In this paper we present a robust method to detect the presence of measurement artifacts and identify what kind of measurement error is present in BIS measurements. The method is based on supervised machine learning and uses a novel set of generalist features for measurement characterization in different immittance planes. Experimental validation has been carried out using a database of complex spectra BIS measurements obtained from different BIS applications and containing six different types of errors, as well as error-free measurements. The method obtained a low classification error (0.33%) and has shown good generalization. Since both the features and the classification schema are relatively simple, the implementation of this pre-processing task in the current hardware of bioimpedance spectrometers is possible.

  • 36.
    Ayllon, David
    et al.
    Universidad de Alcalá.
    Gil-Pita, Roberto
    Universidad de Alcalá.
    Seoane, Fernando
    University of Borås, Faculty of Textiles, Engineering and Business. KTH-School of Technology and Health.
    Detection and Classification of Measurement Errors in Bioimpedance Spectroscopy2016In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 11, no 6, article id e0156522Article in journal (Refereed)
    Abstract [en]

    Bioimpedance spectroscopy (BIS) measurement errors may be caused by parasitic stray capacitance, impedance mismatch, cross-talking or their very likely combination. An accurate detection and identification is of extreme importance for further analysis because in some cases and for some applications, certain measurement artifacts can be corrected, minimized or even avoided. In this paper we present a robust method to detect the presence of measurement artifacts and identify what kind of measurement error is present in BIS measurements. The method is based on supervised machine learning and uses a novel set of generalist features for measurement characterization in different immittance planes. Experimental validation has been carried out using a database of complex spectra BIS measurements obtained from different BIS applications and containing six different types of errors, as well as error-free measurements. The method obtained a low classification error (0.33%) and has shown good generalization. Since both the features and the classification schema are relatively simple, the implementation of this pre-processing task in the current hardware of bioimpedance spectrometers is possible.

  • 37.
    Ayllon, David
    et al.
    Department of Signal Theory and Communications.
    Seoane, Fernando
    KTH, School of Technology and Health (STH), Medical sensors, signals and systems (MSSS).
    Gil-Pita, Roberto
    Department of Signal Theory and Communications.
    Cole equation and parameter estimation from electrical bioimpedance spectroscopy measurements: A comparative study2009In: EMBC: 2009 ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOLS 1-20, Buenos Aires: IEEE Engineering in Medicine and Biology , 2009, p. 3779-3782Conference paper (Refereed)
    Abstract [en]

    Since there are several applications of Electrical Bioimpedance (EBI) that use the Cole parameters as base of the analysis, to fit EBI measured data onto the Cole equation is a very common practice within Multifrequency-EBI and spectroscopy. The aim of this paper is to compare different fitting methods for EBI data in order to evaluate their suitability to fit the Cole equation and estimate the Cole parameters. Three of the studied fittings are based on the use of Non-Linear Least Squares on the Cole model, one using the real part only, a second using the imaginary part and the third using the complex impedance. Furthermore, a novel fitting method done on the impedance plane, without using any frequency information has been implemented and included in the comparison. Results show that the four methods perform relatively well but the best fitting in terms of standard error of estimate is the fitting obtained from the resistance only. The results support the possibility of measuring only the resistive part of the bioimpedance to accurately fit Cole equation and estimate the Cole parameters, with entailed advantages.

  • 38. Ayllón, David
    et al.
    Seoane Martínez, Fernando
    University of Borås, School of Engineering.
    Gil-Pita, Roberto
    Cole Equation and Parameter Estimation from Electrical Bioimpedance Spectroscopy Measurements: A Comparative Study2009Conference paper (Other academic)
    Abstract [en]

    Since there are several applications of Electrical Bioimpedance (EBI) that use the Cole parameters as base of the analysis, to fit EBI measured data onto the Cole equation is a very common practice within Multifrequency-EBI and spectroscopy. The aim of this paper is to compare different fitting methods for EBI data in order to evaluate their suitability to fit the Cole equation and estimate the Cole parameters. Three of the studied fittings are based on the use of Non-Linear Least Squares on the Cole model, one using the real part only, a second using the imaginary part and the third using the complex impedance. Furthermore, a novel fitting method done on the Impedance plane, without using any frequency information has been implemented and included in the comparison. Results show that the four methods perform relatively well but the best fitting in terms of Standard Error of Estimate is the fitting obtained from the resistance only. The results support the possibility of measuring only the resistive part of the bioimpedance to accurately fit Cole equation and estimate the Cole parameters, with entailed advantages.

  • 39. Brown, Shannon
    et al.
    Ortiz-Catalan, Max
    Chalmers University of Technology.
    Petersson, Joel
    University of Borås, Faculty of Textiles, Engineering and Business.
    Rödby, Kristian
    University of Borås, Faculty of Textiles, Engineering and Business.
    Seoane, Fernando
    University of Borås, Faculty of Textiles, Engineering and Business. KTH-School of Technology and Health.
    Intarsia-sensorized band and textrodes for real-time myoelectric pattern recognition2016In: Engineering in Medicine and Biology Society (EMBC), 2016 IEEE 38th Annual International Conference of the, Institute of Electrical and Electronics Engineers (IEEE) , 2016, p. 6074-6077Conference paper (Refereed)
    Abstract [en]

    Surface Electromyography (sEMG) has applications in prosthetics, diagnostics and neuromuscular rehabilitation. Self-adhesive Ag/AgCl are the electrodes preferentially used to capture sEMG in short-term studies, however their long-term application is limited. In this study we designed and evaluated a fully integrated smart textile band with electrical connecting tracks knitted with intarsia techniques and knitted textile electrodes. Real-time myoelectric pattern recognition for motor volition and signal-to-noise ratio (SNR) were used to compare its sensing performance versus the conventional Ag-AgCl electrodes. After a comprehending measurement and performance comparison of the sEMG recordings, no significant differences were found between the textile and the Ag-AgCl electrodes in SNR and prediction accuracy obtained from pattern recognition classifiers.

  • 40.
    Brown, Shannon
    et al.
    Högskolan i Borås.
    Ortiz-Catalan, Max
    Chalmers University of Technology.
    Petersson, Joel
    Högskolan i Borås.
    Rödby, Kristian
    Högskolan i Borås.
    Seoane, Fernando
    Högskolan i Borås, Akademin för vård, arbetsliv och välfärd.
    Intarsia-Sensorized Band and Textrodes for the Acquisition of Myoelectric Signals2016In: The Second International Conference on Smart Portable, Wearable, Implantable and Disability-oriented Devices and Systems, International Academy, Research and Industry Association (IARIA), 2016, p. 14-19, article id 2_10_80013Conference paper (Refereed)
    Abstract [en]

    Abstract— Surface Electromyography (sEMG) has applications in prosthetics, diagnostics and neuromuscular rehabilitation, and has been an increasing area of study. This study attempts to use a fully integrated smart textile band with electrical connecting tracks knitted with intarsia techniques to evaluate the quality of sEMG acquired by knitted textile electrodes. Myoelectric pattern recognition for motor volition and signal-to-noise ratio (SNR) were used to compare its sensing performance versus the conventional Ag-AgCl electrodes. Overall no significant differences were found between the textile and the Ag-AgCl electrodes in SNR and prediction accuracy obtained from pattern recognition classifiers. On average the textile electrodes produced a high prediction accuracy, >97% across all movements, which is equivalent to the accuracy obtained with conventional gel electrodes (Ag-AgCl). Furthermore the SNR for the Maximum Voluntary Contraction did not differ considerably between the textile and the Ag-AgCl electrodes.

  • 41. Brown, Shannon
    et al.
    Ortiz-Catalan, Max
    Chalmers University of Technology.
    Petersson, Joel
    University of Borås, Faculty of Textiles, Engineering and Business. Högskolan i Borås.
    Rödby, Kristian
    University of Borås, Faculty of Textiles, Engineering and Business.
    Seoane, Fernando
    University of Borås, Faculty of Textiles, Engineering and Business. KTH-School of Technology and Health.
    Intarsia-Sensorized Band and Textrodes for the Acquisition of Myoelectric Signals2016In: The Second International Conference on Smart Portable, Wearable, Implantable and Disability-oriented Devices and Systems, International Academy, Research and Industry Association (IARIA) , 2016, p. 14-19, article id 2_10_80013Conference paper (Refereed)
    Abstract [en]

    Surface Electromyography (sEMG) has applications in prosthetics, diagnostics and neuromuscular rehabilitation, and has been an increasing area of study. This study attempts to use a fully integrated smart textile band with electrical connecting tracks knitted with intarsia techniques to evaluate the quality of sEMG acquired by knitted textile electrodes. Myoelectric pattern recognition for motor volition and signal-to-noise ratio (SNR) were used to compare its sensing performance versus the conventional Ag-AgCl electrodes. Overall no significant differences were found between the textile and the Ag-AgCl electrodes in SNR and prediction accuracy obtained from pattern recognition classifiers. On average the textile electrodes produced a high prediction accuracy, >97% across all movements, which is equivalent to the accuracy obtained with conventional gel electrodes (Ag-AgCl). Furthermore the SNR for the Maximum Voluntary Contraction did not differ considerably between the textile and the Ag-AgCl electrodes.

  • 42.
    Buendia, Ruben
    et al.
    University of Borås, Sweden.
    bogonez-franco, Paco
    Technical University of Catalonia.
    Nescolarde, Lexa
    Technical University of Catalonia.
    Seoane, Fernando
    KTH, School of Technology and Health (STH), Medical sensors, signals and systems (MSSS).
    Influence of electrode mismatch on Cole parameter estimation from Total Right Side Electrical Bioimpedance Spectroscopy measurements2012In: Medical Engineering and Physics, ISSN 1350-4533, E-ISSN 1873-4030, Vol. 34, no 7, p. 1024-1028Article in journal (Refereed)
    Abstract [en]

    Applications based on measurements of Electrical Bioimpedance (EBI) spectroscopy analysis, like assessment of body composition, have proliferated in the past years. Currently Body Composition Assessment (BCA) based in Bioimpedance Spectroscopy (BIS) analysis relays on an accurate estimation of the Cole parameters R-0 and R-infinity. A recent study by Bogonez-Franco et al. has proposed electrode mismatch as source of remarkable artefacts in BIS measurements. Using Total Right Side BIS measurements from the aforementioned study, this work has focused on the influence of electrode mismatch on the estimation of R-0 and R-infinity using the Non-Linear Least Square curve fitting technique on the modulus of the impedance. The results show that electrode mismatch on the voltage sensing electrodes produces an overestimation of the impedance spectrum leading to a wrong estimation of the parameters R-0 and R-infinity, and consequently obtaining values around 4% larger that the values obtained from BIS without electrode mismatch. The specific key factors behind electrode mismatch or its influence on the analysis of single and spectroscopy measurements have not been investigated yet, no compensation or correction technique is available to overcome the deviation produced on the EBI measurement. Since textile-enabled EBI applications using dry textrodes, i.e. textile electrodes with dry skin-electrode interfaces and potentially large values of electrode polarization impedance are more prone to produce electrode mismatch, the lack of a correction or compensation technique might hinder the proliferation of textile-enabled EBI applications for personalized healthcare monitoring.

  • 43.
    Buendia, Ruben
    et al.
    University of Borås, School of Engineering.
    Gil-Pita, Roberto
    Seoane, Fernando
    University of Borås, School of Engineering.
    Cole Parameter Estimation from the Modulus of the Electrical Bioimpeadance for Assessment of Body Composition. A Full Spectroscopy Approach2011In: Journal of Electrical Bioimpedance, ISSN 1891-5469, E-ISSN 1891-5469, Vol. 2, p. 72-78Article in journal (Refereed)
    Abstract [en]

    Activities around applications of Electrical Bioimpedance Spectroscopy (EBIS) have proliferated in the past decade significantly. Most of these activities have been focused in the analysis of the EBIS measurements, which eventually might enable novel applications. In Body Composition Assessment (BCA), the most common analysis approach currently used in EBIS is based on the Cole function, which most often requires curve fitting. One of the most implemented approaches for obtaining the Cole parameters is performed in the impedance plane through the geometrical properties that the Cole function exhibit in such domain as depressed semi-circle. To fit the measured impedance data to a semi-circle in the impedance plane, obtaining the Cole parameters in an indirect and sequential manner has several drawbacks. Applying a Non-Linear Least Square (NLLS) iterative fitting on the spectroscopy measurement, obtains the Cole parameters considering the frequency information contained in the measurement. In this work, from experimental total right side EBIS measurements, the BCA parameters have been obtained to assess the amount and distribution of whole body fluids. The values for the BCA parameters have been obtained using values for the Cole parameters estimated with both approaches: circular fitting on the impedance plane and NLLS impedance-only fitting. The comparison of the values obtained for the BCA parameters with both methods confirms that the NLLS impedance-only is an effective alternative as Cole parameter estimation method in BCA from EBIS measurements. Using the modulus of the Cole function as the model for the fitting would eliminate the need for performing phase detection in the acquisition process, simplifying the hardware specifications of the measurement instrumentation when implementing a bioimpedance spectrometer.

  • 44.
    Buendia, Ruben
    et al.
    KTH, School of Technology and Health (STH), Medical sensors, signals and systems (MSSS).
    Gil-Pita, Roberto
    Department of Theory of the Signal and Communications.
    Seoane, Fernando
    KTH, School of Technology and Health (STH), Medical sensors, signals and systems (MSSS).
    Cole Parameter Estimation from the Modulus of the Electrical Bioimpeadance for Assessment of Body Composition: A Full Spectroscopy Approach2011In: Journal of Electrical Bioimpedance, ISSN 1891-5469, E-ISSN 1891-5469, Vol. 2, p. 72-78Article in journal (Refereed)
    Abstract [en]

    Activities around applications of Electrical Bioimpedance Spectroscopy (EBIS) have proliferated in the past decade significantly. Most of these activities have been focused in the analysis of the EBIS measurements, which eventually might enable novel applications. In Body Composition Assessment (BCA) the most common analysis approach currently used in EBIS is based on the Cole function, which most often requires curve fitting. One of the most implemented approaches for obtaining the Cole parameters is performed in the impedance plane through the geometrical properties that the Cole function exhibit in such domain as depressed semi-circle. To fit the measured impedance data to a semi-circle in the impedance plane, obtaining the Cole parameters in an indirect and sequential manner has several drawbacks. Applying a Non-Linear Least Square (NLLS) iterative fitting on the spectroscopy measurement, obtains the Cole parameters considering the frequency information contained in the measurement. In this work, from experimental total right side EBIS measurements, the BCA parameters have been obtained to assess the amount and distribution of whole body fluids. The values for the BCA parameters have been obtained using values for the Cole parameters estimated with both approaches: circular fitting on the impedance plane and NLLS impedance-only fitting. The comparison of the values obtained for the BCA parameters with both methods confirms that the NLLS impedance-only is an effective alternative as Cole parameter estimation method in BCA from EBIS measurements. Using the modulus of the Cole function as the model for the fitting would eliminate the need for performing a phase detection in the acquisition process, simplifying the hardware specifications of the measurement instrumentation when implementing a bioimpedance spectrometer.

  • 45.
    Buendia, Ruben
    et al.
    University of Borås, School of Engineering.
    Gil-Pita, Roberto
    Seoane, Fernando
    University of Borås, School of Engineering.
    Cole parameter estimation from total right side electrical bioimpedance spectroscopy measurements: Influence of the number of frequencies and the upper limit2011In: Engineering in Medicine and Biology Society,EMBC, 2011 Annual International Conference of the IEEE, IEEE , 2011, p. 1843-1846Conference paper (Refereed)
    Abstract [en]

    Applications based on measurements of Electrical Bioimpedance Spectrocopy (EBIS) analysis are proliferating. The most spread and known application of EBIS is the non-invasive assessment of body composition. Fitting to the Cole function to obtain the Cole parameters, R0 and R∞, is the core of the EBIS analysis to obtain the body fluid distribution. An accurate estimation of the Cole parameters is essential for the Body Composition Assessment (BCA) and the estimation process depends on several factors. One of them is the upper frequency limit used for the estimation and the other is the number of measured frequencies in the measurement frequency range. Both of them impose requirements on the measurement hardware, influencing largely in the complexity of the bioimpedance spectrometer. In this work an analysis of the error obtained when estimating the Cole parameters with several frequency ranges and different number of frequencies has been performed. The study has been done on synthetic EBIS data obtained from experimental Total Right Side (TRS) measurements. The results suggest that accurate estimations of R0 and R∞ for BCA measurements can be achieved using much narrower frequency ranges and quite fewer frequencies than electrical bioimpedance spectrometers commercially available nowadays do.

  • 46.
    Buendia, Ruben
    et al.
    School of Engineering, University of Borås.
    Gil-Pita, Roberto
    Department of Theory of the Signal and Communications, University of Alcala, Madrid, Spain.
    Seoane, Fernando
    KTH, School of Technology and Health (STH), Medical sensors, signals and systems (MSSS).
    Cole parameter estimation from total right side electrical bioimpedance spectroscopy measurements: Influence of the number of frequencies and the upper limit2011In: 2011 ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC), 2011, p. 1843-1846Conference paper (Refereed)
    Abstract [en]

    Applications based on measurements of Electrical Bioimpedance Spectroscopy (EBIS) analysis are proliferating. The most spread and known application of EBIS is the non-invasive assessment of body composition. Fitting to the Cole function to obtain the Cole parameters, R<sub>0</sub> and R<sub>&#x221E;</sub>, is the core of the EBIS analysis to obtain the body fluid distribution. An accurate estimation of the Cole parameters is essential for the Body Composition Assessment (BCA) and the estimation process depends on several factors. One of them is the upper frequency limit used for the estimation and the other is the number of measured frequencies in the measurement frequency range. Both of them impose requirements on the measurement hardware, influencing largely in the complexity of the bioimpedance spectrometer. In this work an analysis of the error obtained when estimating the Cole parameters with several frequency ranges and different number of frequencies has been performed. The study has been done on synthetic EBIS data obtained from experimental Total Right Side (TRS) measurements. The results suggest that accurate estimations of R<sub>0</sub> and R<sub>&#x221E;</sub> for BCA measurements can be achieved using much narrower frequency ranges and quite fewer frequencies than electrical bioimpedance spectrometers commercially available nowadays do.

  • 47.
    Buendia, Ruben
    et al.
    KTH, School of Technology and Health (STH), Medical sensors, signals and systems (MSSS).
    Seoane, Fernando
    KTH, School of Technology and Health (STH), Medical sensors, signals and systems (MSSS).
    Bosacus, I.
    University of Gothenburg.
    Gil-Pita, Roberto
    Department of Theory of the Signal and Communications, University of Alcala, Madrid, Spain.
    Johannsson, G.
    Ellegård, L.
    Lindecrantz, Kaj
    KTH, School of Technology and Health (STH), Medical sensors, signals and systems (MSSS).
    Robust approach against capacitive coupling for the estimation of body fluids using clinical bioimpedance spectroscopy measurementsManuscript (preprint) (Other academic)
  • 48. Buendia, Ruben
    et al.
    Seoane, Fernando
    University of Borås, School of Engineering.
    Bosaeus, Ingvar
    Gil-Pita, Roberto
    Johannsson, G
    Ellegård, Lars
    Lindecrantz, Kaj
    University of Borås, School of Engineering.
    Robustness study of the different immittance spectra and frequency ranges in bioimpedance spectroscopy analysis for assessment of total body composition2014In: Physiological Measurement, ISSN 0967-3334, E-ISSN 1361-6579, ISSN 0967-3334, Vol. 35, no 7, p. 1373-Article in journal (Refereed)
    Abstract [en]

    The estimation of body fluids is a useful and common practice for assessment of disease status and therapy outcomes. Electrical bioimpedance spectroscopy (EBIS) methods are noninvasive, inexpensive and efficient alternatives for determination of body fluids. One of the main source of errors in EBIS measurements in the estimation of body fluids is capacitive coupling. In this paper an analysis of capacitive coupling in EBIS measurements was performed and the robustness of the different immittance spectra against it tested. On simulations the conductance (G) spectrum presented the smallest overall error, among all immittance spectra, in the estimation of the impedance parameters used to estimate body fluids. Afterwards the frequency range of 10–500 kHz showed to be the most robust band of the G spectrum. The accuracy of body fluid estimations from the resulting parameters that utilized G spectrum and parameters provided by the measuring device were tested on EBIS clinical measurements from growth hormone replacement therapy patients against estimations performed with dilution methods. Regarding extracellular fluid, the correlation between each EBIS method and dilution was 0.93 with limits of agreement of 1.06 ± 2.95 l for the device, 1.10 ± 2.94 l for G [10–500 kHz] and 1.04 ± 2.94 l for G [5–1000 kHz]. Regarding intracellular fluid, the correlation between dilution and the device was 0.91, same as for G [10–500 kHz] and 0.92 for G [5–1000 kHz]. Limits of agreement were 0.12 ± 4.46 l for the device, 0.09 ± 4.45 for G [10–500 kHz] and 0.04 ± 4.58 for G [5–1000 kHz]. Such close results between the EBIS methods validate the proposed approach of using G spectrum for initial Cole characterization and posterior clinical estimation of body fluids status.

  • 49. Buendia, Ruben
    et al.
    Seoane, Fernando
    University of Borås, School of Engineering.
    Gil-Pita, Roberto
    A Novel Approach for Removing the Hook Effect Artefact from Electrical Bioimpedance Spectroscopy Measurements2009In: Journal of Physics: Conference Series, Institute of Physics Publishing Ltd. , 2009Conference paper (Refereed)
    Abstract [en]

    Very often in Electrical Bioimpedance (EBI) spectroscopy measurements the presence of stray capacitances creates a measurement artefact commonly known as Hook Effect. Such an artefact creates a hook-alike deviation of the EBI data noticeable when representing the measurement on the impedance plane. Such Hook Effect is noticeable at high frequencies but it also causes a data deviation at lower measurement frequencies. In order to perform any accurate analysis of the EBI spectroscopy data, the influence of the Hook Effect must be removed. An established method to compensate the hook effect is the well known Td compensation, which consist on multiplying the obtained spectrum, Zmeas() by a complex exponential in the form of exp[jTd]. Such a method cannot correct entirely the Hook Effect since the hook-alike deviation occurs a broad frequency range in both magnitude and phase of the measured impedance, and by using a real value for Td. First, a real value only modifies the phase of the measured impedance and second, it can only correct the Hook Effect at a single frequency. In addition, the process to select a value for Td by an iterative process with the aim to obtain the best Cole fitting lacks solid scientific grounds. In this work the Td compensation method is revisited and a modified approach for correcting the Hook Effect that includes a novel method for selecting the correcting values is proposed. The initial validation results confirm that the proposed method entirely corrects the Hook Effect at all frequencies.

  • 50.
    Buendia, Ruben
    et al.
    School of Engineering, University of Borås.
    Seoane, Fernando
    School of Engineering, University of Borås.
    Gil-Pita, Roberto
    Department of Theory of the Signals and Communications.
    A novel approach for removing the hook effect artefact from Electrical Bioimpedance spectroscopy measurements2010Conference paper (Refereed)
    Abstract [en]

    Very often in Electrical Bioimpedance (EBI) spectroscopy measurements the presence of stray capacitances creates a measurement artefact commonly known as Hook Effect . Such an artefact creates a hook-alike deviation of the EBI data noticeable when representing the measurement on the impedance plane. Such Hook Effect is noticeable at high frequencies but it also causes a data deviation at lower measurement frequencies. In order to perform any accurate analysis of the EBI spectroscopy data, the influence of the Hook Effect must be removed. An established method to compensate the hook effect is the well known Td compensation , which consists on multiplying the obtained spectrum, Z meas (ω) by a complex exponential in the form of exp[jωTd]. Such a method cannot correct entirely the Hook Effect since the hook-alike deviation occurs a broad frequency range in both magnitude and phase of the measured impedance, and by using a scalar value for Td . First a scalar only modifies the phase of the measured impedance and second, a single value can truly corrects the Hook Effect only at a single frequency. In addition, the process to select a value for the scalar Td by an iterative process with the aim to obtain the best Cole fitting lacks solid scientific grounds. In this work the Td compensation method is revisited and a modified approach for correcting the Hook Effect including a novel method for selecting the correcting values is proposed. The initial validation results confirm that the proposed method entirely corrects the Hook Effect at all frequencies.

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