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  • 1.
    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.

  • 2.
    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)
  • 3.
    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)
  • 4.
    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)
  • 5.
    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)
  • 6.
    Gyllencreutz, E.
    et al.
    Karolinska Inst, Stockholm, Sweden.;Ostersund Hosp, Dept Obstet & Gynecol, Ostersund, Sweden..
    Lu, Ke
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Health Informatics.
    Lindecrantz, Kaj
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Health Informatics. Karolinska Inst, Stockholm, Sweden.
    Lindqvist, P.
    Karolinska Inst, Stockholm, Sweden..
    Nordström, L.
    Karolinska Inst, Stockholm, Sweden..
    Holzmann, M.
    Karolinska Inst, Stockholm, Sweden.;Karolinska Univ Hosp, Dept Obstet & Gynecol, Stockholm, Sweden..
    Abtahi, F.
    Karolinska Inst, Stockholm, Sweden.;Karolinska Univ Hosp, Dept Clin Physiol, Stockholm, Sweden..
    Validation of a computerised algorithm to quantify fetal heart rate deceleration area: An observational study2018In: British Journal of Obstetrics and Gynecology, ISSN 1470-0328, E-ISSN 1471-0528, Vol. 125, p. 54-54Article in journal (Other academic)
  • 7.
    Gyllencreutz, Erika
    et al.
    Karolinska Inst, Dept Womens & Childrens Hlth, Stockholm, Sweden.;Ostersund Hosp, Dept Obstet & Gynecol, S-83183 Region Jamtland Harjedal, Ostersund, Sweden..
    Lu, Ke
    KTH, School of Technology and Health (STH).
    Lindecrantz, Kaj
    KTH, School of Technology and Health (STH). Karolinska Inst, Dept Clin Sci Intervent & Technol, Stockholm, Sweden..
    Lindqvist, Pelle G.
    Karolinska Inst, Dept Clin Sci Intervent & Technol, Stockholm, Sweden.;Karolinska Univ Hosp, Pregnancy & Delivery Care, Stockholm, Sweden..
    Nordström, Lennart
    Karolinska Inst, Dept Womens & Childrens Hlth, Stockholm, Sweden.;Karolinska Univ Hosp, Pregnancy & Delivery Care, Stockholm, Sweden..
    Holzmann, Malin
    Karolinska Inst, Dept Womens & Childrens Hlth, Stockholm, Sweden.;Karolinska Univ Hosp, Pregnancy & Delivery Care, Stockholm, Sweden..
    Abtahi, Farhad
    Karolinska Inst, Inst Environm Med, Stockholm, Sweden.;Karolinska Univ Hosp Huddinge, Dept Clin Physiol, Stockholm, Sweden..
    Validation of a computerized algorithm to quantify fetal heart rate deceleration area2018In: Acta Obstetricia et Gynecologica Scandinavica, ISSN 0001-6349, E-ISSN 1600-0412, Vol. 97, no 9, p. 1137-1147Article in journal (Refereed)
    Abstract [en]

    IntroductionReliability in visual cardiotocography interpretation is unsatisfying, which has led to the development of computerized cardiotocography. Computerized analysis is well established for antenatal fetal surveillance but has yet not performed sufficiently during labor. We aimed to investigate the capacity of a new computerized algorithm compared with visual assessment in identifying intrapartum fetal heart rate baseline and decelerations. Material and methodsIn all, 312 intrapartum cardiotocography tracings with variable decelerations were analyzed by the computerized algorithm and visually examined by two observers, blinded to each other and the computer analysis. The width, depth and area of each deceleration was measured. Four cases (>100 variable decelerations) were subjected to in-depth detailed analysis. The outcome measures were bias in seconds (width), beats per minute (depth), and beats (area) between computer and observers using Bland-Altman analysis. Interobserver reliability was determined by calculating intraclass correlation and Spearman rank analysis. ResultsThe analysis (312 cases) showed excellent intraclass correlation (0.89-0.95) and very strong Spearman correlation (0.82-0.91). The detailed analysis of >100 decelerations in four cases revealed low bias between the computer and the two observers; width 1.4 and 1.4 seconds, depth 5.1 and 0.7 beats per minute, and area 0.1 and -1.7 beats. This was comparable to the bias between the two observers: 0.3 seconds (width), 4.4 beats per minute (depth) and 1.7 beats (area). The intraclass correlation was excellent (0.90-.98). ConclusionA novel computerized algorithm for intrapartum cardiotocography analysis is as accurate as gold standard visual assessment, with high correlation and low bias.

  • 8.
    Lu, Ke
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH).
    Wearable Solutions for P-Health at Work: Precise, Pervasive and Preventive2018Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    With a demographic change towards an older population, the structure of the labor force is shifting, and people are expected to work longer within their extended life span. However, for many people, wellbeing has been compromised by work-related problems before they reach the retirement age. Prevention of chronic diseases such as cardiovascular diseases and musculoskeletal disorders is needed to provide a sustainable working life. Therefore, pervasive tools for risk assessment and intervention are needed. The vision is to use wearable technologies to promote a sustainable work life, to be more detailed, to develop a system that integrates wearable technologies into workwear to provide pervasive and precise occupational disease prevention. This thesis presents some efforts towards this vision, including system-level design for a wearable risk assessment and intervention system, as well as specific insight into solutions for in-field assessment of physical workload and technologies to make smart sensing garments. The overall system is capable of providing unobtrusive monitoring of several signs, automatically estimating risk levels and giving feedback and reports to different stakeholders. The performance and usability of current energy expenditure estimation methods based on heart rate monitors and accelerometers were examined in occupational scenarios. The usefulness of impedance pneumography-based respiration monitoring for energy expenditure estimation was explored. A method that integrates heart rate, respiration and motion information using a neuronal network for enhancing the estimation is shown. The sensing garment is an essential component of the wearable system. Smart textile solutions that improve the performance, usability and manufacturability of sensing garments, including solutions for wiring and textile-electronics interconnection as well as an overall garment design that utilizes different technologies, are demonstrated.

  • 9.
    Lu, Ke
    et al.
    KTH, School of Technology and Health (STH).
    Abtahi, Farhad
    KTH, School of Technology and Health (STH).
    Nordström, Lennart
    Lindqvist, Pelle
    Lindecrantz, Kaj
    KTH, School of Technology and Health (STH).
    Software tool for fetal heart rate signal analysis2015Conference paper (Refereed)
  • 10.
    Lu, Ke
    et al.
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Health Informatics. Royal Inst Technol, Stockholm, Sweden..
    Holzmann, M.
    Karolinska Inst, Stockholm, Sweden.;Karolinska Univ Hosp, Dept Obstet & Gynecol, Stockholm, Sweden..
    Abtahi, F.
    Karolinska Inst, Stockholm, Sweden.;Karolinska Univ Hosp, Dept Clin Physiol, Stockholm, Sweden..
    Lindecrantz, Kaj
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Health Informatics. Karolinska Univ Hosp, Dept Clintec, Stockholm, Sweden..
    Lindqvist, P.
    Karolinska Inst, Stockholm, Sweden.;Karolinska Univ Hosp, Dept Clintec, Stockholm, Sweden..
    Nordström, L.
    Karolinska Inst, Stockholm, Sweden..
    Fetal heart rate short term variation (STV) during labour in relation to early stages of hypoxia: An observational study2018In: British Journal of Obstetrics and Gynecology, ISSN 1470-0328, E-ISSN 1471-0528, Vol. 125, p. 55-55Article in journal (Other academic)
  • 11.
    Lu, Ke
    et al.
    KTH, School of Technology and Health (STH).
    Holzmann, Malin
    Karolinska Inst, Dept Womens & Childrens Hlth, Stockholm, Sweden.;Karolinska Univ Hosp, Patient Area Pregnancy & Delivery Care, Stockholm, Sweden..
    Abtahi, Fahrad
    Karolinska Inst, Inst Environm Med, Stockholm, Sweden.;Karolinska Univ Hosp Huddinge, Dept Clin Physiol, Stockholm, Sweden..
    Lindecrantz, Kaj
    KTH, School of Technology and Health (STH). Karolinska Inst, Dept Clin Sci Intervent & Technol, Stockholm, Sweden..
    Lindqvist, Pelle G.
    Karolinska Univ Hosp, Patient Area Pregnancy & Delivery Care, Stockholm, Sweden.;Karolinska Inst, Dept Clin Sci Intervent & Technol, Stockholm, Sweden..
    Nordström, Lennart
    Karolinska Inst, Dept Womens & Childrens Hlth, Stockholm, Sweden.;Karolinska Univ Hosp, Patient Area Pregnancy & Delivery Care, Stockholm, Sweden..
    Fetal heart rate short term variation during labor in relation to scalp blood lactate concentration2018In: Acta Obstetricia et Gynecologica Scandinavica, ISSN 0001-6349, E-ISSN 1600-0412, Vol. 97, no 10, p. 1274-1280Article in journal (Refereed)
    Abstract [en]

    IntroductionFetal heart rate short term variation (STV) decreases with severe chronic hypoxia in the antenatal period. However, only limited research has been done on STV during labor. We have tested a novel algorithm for a valid baseline estimation and calculated STV. To explore the value of STV during labor, we compared STV with fetal scalp blood (FBS) lactate concentration, an early marker in the hypoxic process. Material and methodsSoftware was developed which estimates baseline frequency using a novel algorithm and thereby calculates STV according to Dawes and Redman in up to four 30-minute blocks prior to each FBS. Cardiotocography traces from 1070 women in labor who had had FBS performed on 2134 occasions were analyzed. ResultsIn acidemic cases (lactate >4.8mmol/L; Lactate Pro), median STV 30minutes prior to FBS was 7.10milliseconds compared with 6.09milliseconds in the preacidemic (4.2-4.8mmol/L) and 5.23milliseconds in the normal (<4.2mmol/L) groups (P<.05). There was a positive correlation between lactate and STV (rho=0.16-0.24; P<.05). Median lactate concentration in cases with STV <3.0milliseconds (n=160) was 2.3mmol/L. When 2 FBS were performed within 60minutes the change rate of lactate correlated to STV (rho=0.33; P<.001). Cases with increasing lactate concentration had a median STV of 5.29milliseconds vs 4.41milliseconds in those with decreasing lactate (P<.001). ConclusionsIn the early stages of intrapartum hypoxia, STV increases, contrary to findings regarding chronic hypoxia in the antenatal period. The increase in the adrenergic surge is a likely explanation.

  • 12.
    Lu, Ke
    et al.
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH).
    Yang, Liyun
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Ergonomics.
    Abtahi, F.
    Lindecrantz, Kaj
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Industrial Biotechnology.
    Rödby, K.
    Seoane, F.
    Wearable cardiorespiratory monitoring system for unobtrusive free-living energy expenditure tracking2019In: IFMBE Proceedings, Springer, 2019, no 1, p. 433-437Conference paper (Refereed)
    Abstract [en]

    In this work, we want to introduce combined heart rate and respiration monitoring for more accurate energy expenditure tracking on free-living subjects. We have developed a wearable cardiorespiratory monitoring system with unobtrusive heart rate measurement and ventilation estimation function for this purpose. The system is based on a garment with integrated textile electrodes for one-lead electrocardiogram and impedance pneumography measurements. A pilot experiment has been performed to prove the concept and to evaluate the characteristics of heart rate and ventilation estimated by our system in relation to energy expenditure. In the experiment, ventilation shows a better linearity in relation to the energy expenditure at the low intensity region than heart rate. Based on these characteristics, a model combining heart rate and ventilation for energy expenditure estimation is proposed which shows a significantly lower estimation error than the heart rate only model.

  • 13.
    Lu, Ke
    et al.
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH). Institute of Environmental Medicine, Karolinska Institutet, Solnavägen 1, 171 77 Solna, Sweden.
    Yang, Liyun
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Ergonomics.
    Seoane, F.
    Abtahi, Farhad
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH). Institute of Environmental Medicine, Karolinska Institutet, Solnavägen 1, 171 77 Solna, Sweden.
    Forsman, Mikael
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Ergonomics. Institute of Environmental Medicine, Karolinska Institutet, Solnavägen 1, 171 77 Solna, Sweden.
    Lindecrantz, K.
    Fusion of heart rate, respiration and motion measurements from a wearable sensor system to enhance energy expenditure estimation2018In: Sensors, ISSN 1424-8220, E-ISSN 1424-8220, Vol. 18, no 9, article id 3092Article in journal (Refereed)
    Abstract [en]

    This paper presents a new method that integrates heart rate, respiration, and motion information obtained from a wearable sensor system to estimate energy expenditure. The system measures electrocardiography, impedance pneumography, and acceleration from upper and lower limbs. A multilayer perceptron neural network model was developed, evaluated, and compared to two existing methods, with data from 11 subjects (mean age, 27 years, range, 21–65 years) who performed a 3-h protocol including submaximal tests, simulated work tasks, and periods of rest. Oxygen uptake was measured with an indirect calorimeter as a reference, with a time resolution of 15 s. When compared to the reference, the new model showed a lower mean absolute error (MAE = 1.65 mL/kg/min, R2 = 0.92) than the two existing methods, i.e., the flex-HR method (MAE = 2.83 mL/kg/min, R2 = 0.75), which uses only heart rate, and arm-leg HR+M method (MAE = 2.12 mL/kg/min, R2 = 0.86), which uses heart rate and motion information. As indicated, this new model may, in combination with a wearable system, be useful in occupational and general health applications. 

  • 14.
    Seoane, Fernando
    et al.
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems. Högskolan i Borås, Akademin för vård, arbetsliv och välfärd.
    Soroudi, Azadeh
    Högskolan i Borås, Sverige.
    Abtahi, Farhad
    KTH, School of Technology and Health (STH), Medical Engineering.
    Lu, Ke
    KTH, School of Technology and Health (STH), Medical Engineering.
    Skrifvars, Mikael
    Högskolan i Borås, Sverige.
    Printed Electronics Enabling a Textile-friendly Interconnection between Wearable Measurement Instrumentation & Sensorized Garments2016Conference paper (Refereed)
  • 15. Seoane, Fernando
    et al.
    Soroudi, Azadeh
    Lu, Ke
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH).
    Abtahi, Farhad
    Nilsson, David
    Nilsson, Marie
    Skrifvars, Mikael
    Textile-Friendly Interconnection between WearableMeasurement Instrumentation and SensorizedGarments – Initial Performance Evaluation forElectrocardiogram RecordingsManuscript (preprint) (Other academic)
  • 16.
    Yang, Liyun
    et al.
    KTH, School of Technology and Health (STH).
    Lu, Ke
    Abtahi, Farhad
    Lindecrantz, Kaj
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Ergonomics.
    Seoane, Fernando
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Ergonomics.
    Forsman, Mikael
    Institute of Environmental Medicine, Karolinska Institutet.
    Eklund, Jörgen
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Ergonomics.
    A pilot study of using smart clothes for physicalworkload assessment2017In: JOY AT WORK, Lund, Sweden, 2017, p. 169-170Conference paper (Refereed)
  • 17.
    Yang, Liyun
    et al.
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Ergonomics.
    Lu, Ke
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Ergonomics.
    Diaz-Olivares, Jose A.
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Ergonomics.
    Seoane, Fernando
    Univ Boras, Swedish Sch Text, S-50190 Boras, Sweden.;Karolinska Inst, Inst Clin Sci Intervent & Technol, S-14157 Huddinge, Sweden.;Karolinska Univ Hosp, Dept Biomed Engn, S-14157 Huddinge, Sweden..
    Lindecrantz, Kaj
    Karolinska Inst, Inst Environm Med, S-17177 Stockholm, Sweden.;Univ Boras, Swedish Sch Text, S-50190 Boras, Sweden..
    Forsman, Mikael
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Ergonomics. nstitute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden.
    Abtahi, Farhad
    Karolinska Inst, Inst Environm Med, S-17177 Stockholm, Sweden..
    Eklund, Jörgen A. E.
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Ergonomics.
    Towards Smart Work Clothing for Automatic Risk Assessment of Physical Workload2018In: IEEE Access, E-ISSN 2169-3536, Vol. 6, p. 40059-40072Article in journal (Refereed)
    Abstract [en]

    Work-related musculoskeletal and cardiovascular disorders are still prevalent in today's working population. Nowadays, risk assessments are usually performed via self-reports or observations, which have relatively low reliability. Technology developments in textile electrodes (textrodes), inertial measurement units, and the communication and processing capabilities of smart phones/tablets provide wearable solutions that enable continuous measurements of physiological and musculoskeletal loads at work with sufficient reliability and resource efficiency. In this paper, a wearable system integrating textrodes, motion sensors, and real-time data processing through a mobile application was developed as a demonstrator of risk assessment related to different types and levels of workload and activities. The system was demonstrated in eight subjects from four occupations with various workload intensities, during which the heart rate and leg motion data were collected and analyzed with real-time risk assessment and feedback. The system showed good functionality and usability as a risk assessment tool. The results contribute to designing and developing future wearable systems and bring new solutions for the prevention of work-related disorders.

  • 18.
    Yang, Liyun
    et al.
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Ergonomics.
    Lu, Ke
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH).
    Forsman, Mikael
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Ergonomics.
    Lindecrantz, Kaj
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Industrial Biotechnology.
    Seoane, Fernando
    Ekblom, Örjan
    Eklund, Jörgen
    Development of smart wearable systems for physiological workload assessment using heart rate and accelerometryManuscript (preprint) (Other academic)
1 - 18 of 18
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