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P177 Cardiorespiratory physiology remotely monitored via wearable wristband photoplethysmography: feasibility and initial benchmarking
  1. G Sneddon1,
  2. R van Mourik2,
  3. P Law2,
  4. O Dur2,
  5. D Lowe1,
  6. C Carlin1
  1. 1Queen Elizabeth University Hospital, Glasgow, UK
  2. 2Wavelet Health, Mountain View, USA


Background The ability to reliably remotely monitor physiological data including heart rate, respiratory rate and oxygen saturation in clinical scenarios such as in patients at risk for exacerbations of respiratory disease, patients at risk for progression to ventilatory failure and patients during home NIV setup would be of significant benefit. Advances in connected wearable device signal acquisition, data analysis and cloud-based computing make acquisition and real-time clinical monitoring of advanced biometric data a realistic prospect. The Wavelet photo-plethysmography (PPG) wristband and Wavelet health platform capture multiple physiological signals – an advance on activity and heart rate monitoring within standard wearable devices. These biometrics are surfaced via Bluetooth paired smartphone or tablet app for clinician review. Feasibility and benchmarking in the clinical environment is a necessary first step before testing the prospective value of these remote monitored wearable-derived physiology measurements.

Methods Patient setup, wristband sampling rate options and comparison of Wavelet derived heart rate (HR), heart rate variability (HRV), respiratory rate (RR) and oxygen saturation (SpO2) measurements across multiple nights have so far been evaluated in 9 patients undergoing sleep studies and/or CPAP or NIV initiation. Wavelet data was compared with simultaneously acquired 1st night single lead ECG, finger-probe SpO2 (Somnomedics polysomnography, S-Med) and transcutaneous HR and SpO2 (TCM5, Radiometer) data.

Results Wavelet dashboard and device setup was straightforward, with reliable data acquisition. Patient feedback on device acceptability has been positive. There was an encouraging corroboration between Wavelet acquired HR, HRV, RR and SpO2 and simultaneous ECG lead, finger probe and transcutaneous diagnostic monitoring. Standard deviation of absolute deviation for Wavelet derived HR (0.91), RR (0.82) and SpO2 (1.41) is encouraging indication of device accuracy, mirroring other recently acquired data.1

Conclusions Feasibility and early accuracy data from the wearable PPG device and remote-monitoring platform is encouraging. These preliminary results suggest that this device may be suitable for prospective clinical trials, for example evaluating utility of wearable physiological monitoring in digitally-enabled preventative service models for respiratory disorders.


  1. Dur O, Rhoades C, Ng SMS, et al. Design rationale and performance evaluation of wavelet health wristband: Bench-top validation of a wrist-worn physiological signal recorder. JMIR Preprints 14 May 2018:11040. doi:10.2196/preprints.11040

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