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Vision-Based Remote Heart Rate Variability Monitoring using Camera
Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system.ORCID-id: 0000-0002-1547-4386
Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system.ORCID-id: 0000-0003-3802-4721
Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system.ORCID-id: 0000-0002-1212-7637
2018 (Engelska)Ingår i: Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST, Volume 225, 2018, s. 10-18Konferensbidrag, Publicerat paper (Refereegranskat)
Abstract [en]

Heart Rate Variability (HRV) is one of the important physiological parameter which is used to early detect many fatal disease. In this paper a non-contact remote Heart Rate Variability (HRV) monitoring system is developed using the facial video based on color variation of facial skin caused by cardiac pulse. The lab color space of the facial video is used to extract color values of skin and signal processing algorithms i.e., Fast Fourier Transform (FFT), Independent Component Analysis (ICA), Principle Component Analysis (PCA) are applied to monitor HRV. First, R peak is detected from the color variation of skin and then Inter-Beat-Interval (IBI) is calculated for every consecutive R-R peak. HRV features are then calculated based on IBI both in time and frequency domain. MySQL and PHP programming language is used to store, monitor and display HRV parameters remotely. In this study, HRV is quantified and compared with a reference measurement where a high degree of similarities is achieved. This technology has significant potential for advancing personal health care especially for telemedicine.

Ort, förlag, år, upplaga, sidor
2018. s. 10-18
Nyckelord [en]
Physiological signals, Heart Rate, Inter-beat-Interval, Heart-Rate-Variability, Non-contact, Remote Monitoring.
Nationell ämneskategori
Medicinteknik
Identifikatorer
URN: urn:nbn:se:mdh:diva-37072DOI: 10.1007/978-3-319-76213-5_2ISI: 000476922000002Scopus ID: 2-s2.0-85042538568ISBN: 9783319762128 (tryckt)OAI: oai:DiVA.org:mdh-37072DiVA, id: diva2:1153827
Konferens
4th EAI International Conference on IoT Technologies for HealthCare HealthyIOT'17, 24 Oct 2017, Angers, France
Projekt
SafeDriver: A Real Time Driver's State Monitoring and Prediction SystemTillgänglig från: 2017-10-31 Skapad: 2017-10-31 Senast uppdaterad: 2019-08-08Bibliografiskt granskad

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Rahman, HamidurAhmed, Mobyen UddinBegum, Shahina

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Totalt: 77 träffar
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