Application of real-time HRV biofeedback in the scenario of meditation practice: Feasibility, usability and medical fidelity
Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Chronic stress is a prevalent and universally present hazard in modern society. It lowers the quality of life for individuals and significantly con- tributes to unsustainable health care costs. Therefore it is important to have natural and noninvasive ways of controlling stress. One such way is meditation, a technique which has been practiced for over five thousand years to improve stress regulation. Also, proceedings in sensing technologies lead to the discovery of biofeedback as another cost-effective technique for stress assessment and reduction. In continuation of research on real-time reflective human-computer-interfaces, this thesis combines these techniques by exploring the application of electrocardiography sensing technology in a heart rate variability (HRV) biofeedback system for the scenario of medita- tion practice. A proof-of-concept prototype was designed and implemented which quantifies stress and gives feedback on meditation effectiveness. For evaluation, a user study has been performed. Results were analysed in a systematic way to evaluate the feasibility and acceptance of the solution as well as the fidelity of HRV data that was measured during user tests. The prototype was found to be feasible in the context of technology acceptance while the fidelity of data, acquired by an algorithm for time and frequency domain analysis of HRV, was confirmed. A final conclusion is that the reflective aspect of the implemented real-time biofeedback system helps to improve regulatory capacity and thus lowers stress in individuals.
Place, publisher, year, edition, pages
2015. , 59 p.
heart rate variability analysis, autonomic nervous system, stress quantification, meditation, real-time biofeedback, electrocardiography, Lomb method
Human Computer Interaction
IdentifiersURN: urn:nbn:se:lnu:diva-45420OAI: oai:DiVA.org:lnu-45420DiVA: diva2:841086
Subject / course
Social Media and Web Technologies, Master Programme, 120 credits
2015-06-02, D2272, Linnaeus University, Växjö, 14:00 (English)
Rana, Juwel, PhD
Jusufi, Ilir, PhD