Affiliation:
1. Department of ICT - e Health the University of Agder, Grimstad, Norway.
Abstract
Cardiovascular problems are evolving as the chief cause of death worldwide. Heart Rate, Blood Pressure, Respiratory Rate, Oxygen Saturation, Systolic Upstroke Time, Heart Beat duration, Diastolic time, RR intervalare some important physiological parameters that help to monitor our daily health condition. Those parameters are very useful to determine if a person is suffering from any cardiovascular problems or not based on daily data collection and monitoring over a certain period of time and in this context machine learning algorithms will be very helpful for developing a smart cardiovascular tele-monitoring & recommendation system for better lifestyle. Irregularities in the heart signal can pop up a serious indication for upcoming cardiac problem. Here, we have concentrated on intensity variation based heart rate calculation process from PPG with major analysis on captured contact video. Here we have used normal handy smart phone camera which is available to everyone and able to capture fingertip videos of flowing blood in the vessels with visible light wavelength. In this paper, we have performed analysis on captured videos for accurate health parameter capturing and compared it with standard devices (FDA approved).
Publisher
Oriental Scientific Publishing Company
Cited by
9 articles.
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