A Photoplethysmography Wearable with Long-term Heart Rate Variability Detection Algorithm
Published in Proceedings of IEEE MIT Undergraduate Research Technology Conference (IEEE link: https://ieeexplore.ieee.org/document/9668881), 2020
This paper presents a wearable device that extracts and utilizes a photoplethysmogram waveform to measure and estimate various vital signs via our mobile application’s custom-designed algorithms. These vital signs include peripheral oxygen saturation, heart rate, respiratory rate, and short/long term heartrate variability. The device wirelessly transmits accumulated data to our Android smartphone application that is backed by a realtime database (Firebase), over Bluetooth Low Energy (BLE). Moreover, this paper explores the proposed device as an emerging technology with the COVID-19 pandemic’s contemporary concerns. The peripheral oxygen saturation measurements would give an early indicator of degrading respiratory health before the apparent manifestation of symptoms. The convenient use of this device in a mobile setting is especially relevant due to current isolation precautions in place and due to its critical role in improving at-risk patients’ care.
Recommended citation: B. Chieng, F. Kavassalis, F. Baudino and U. Guler, "A Photoplethysmography Wearable with Long-term Heart Rate Variability Detection Algorithm," 2020 IEEE MIT Undergraduate Research Technology Conference (URTC), 2020, pp. 1-4, doi: 10.1109/URTC51696.2020.9668881. http://FivosJKavassalis.github.io/files/MIT_URTC_2020_PO.pdf