Design rationale and performance evaluation of Wavelet Health Wristband: bench-top validation of a wrist-worn physiological signal recorder (Preprint)

Abstract

Background: Wearable and connected health devices along with the recent advances in mobile and cloud computing provide a continuous, convenient-to-patient and scalable way to collect personal health data remotely. The Wavelet Health Platform and the Wavelet Wristband have been developed to capture multiple physiological signals and to derive biometrics from these signals including resting heart rate, heart rate variability, and respiration rate.

On the reliability of wearable technology: A tutorial on measuring heart rate and heart rate variability in the wild

“…The validity of data from wearable sensors is now thought to be quite good (Barrios et al, 2019;Dur et al, 2018;Hernando et al, 2018;Kinnunen et al, 2020;Menghini et al, 2019;Steinberg, Yuceege, Mutlu, Korkmaz, van Mourik, et al, 2017). However, the reliability of the biometrics captured by these devices in daily life has so far been assumed to be high, but it has rarely been tested systematically.…”

“…The Biostrap wristband is a commercially available PPG sensor of heart rate (https://biostrap.com). Biostrap (formerly Wavelet) has been validated against clinical-grade wearable devices and ECG (Dur et al, 2018;Jarchi et al, 2018;Steinberg, Yuceege, Mutlu, Korkmaz, van Mourik, et al, 2017). The device uses long wavelength light (red) to detect pulse.…”

“…The heart-rate measurements consisted of raw PPG waveforms, which were processed by Biostrap's algorithms in their servers (Dur et al, 2018). The data presented here were based on the aggregated metrics provided by the Biostrap for each successful sample, which included beats per minute (BPM) and heart rate variability (HRV), calculated as the root mean square difference between successive heartbeats (rMSSD).…”

“…The recent rapid proliferation of wearable sensing technology has been accompanied by many tests of their validity (Barrios et al, 2019;Bent et al, 2020;Dur et al, 2018;Hernando et al, 2018;Kinnunen et al, 2020;Koskimäki et al, 2018;Menghini et al, 2019;Steinberg, Yuceege, Mutlu, Korkmaz, Van Mourik, et al, 2017), usually by examining the correlation of the wearable's signal in a quiet environment with that of trusted laboratory equipment (van Lier et al, 2020). What is usually overlooked in these tests is that most laboratory measurement procedures severely limit participants' bodily movements and cognitive activities (Berntson et al, 2007).…”