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Accepted for/Published in: JMIR mHealth and uHealth

Date Submitted: May 14, 2018
Open Peer Review Period: May 14, 2018 - Jun 13, 2018
Date Accepted: Sep 10, 2018
(closed for review but you can still tweet)

The final, peer-reviewed published version of this preprint can be found here:

Design Rationale and Performance Evaluation of the Wavelet Health Wristband: Benchtop Validation of a Wrist-Worn Physiological Signal Recorder

Dur O, Rhoades C, Ng MS, Elsayed R, van Mourik R, Majmudar MD

Design Rationale and Performance Evaluation of the Wavelet Health Wristband: Benchtop Validation of a Wrist-Worn Physiological Signal Recorder

JMIR Mhealth Uhealth 2018;6(10):e11040

DOI: 10.2196/11040

PMID: 30327288

PMCID: 6231731

Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.

Design Rationale and Performance Evaluation of the Wavelet Health Wristband: Benchtop Validation of a Wrist-Worn Physiological Signal Recorder

  • Onur Dur; 
  • Colleen Rhoades; 
  • Man Suen Ng; 
  • Ragwa Elsayed; 
  • Reinier van Mourik; 
  • Maulik D Majmudar

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 (HR), heart rate variability (HRV), and respiration rate (RR).

Objective:

This study aimed to evaluate the accuracy of the biometric estimates and signal quality of the wristband.

Methods:

Measurements collected from 35 subjects using the Wavelet wristband were compared with simultaneously recorded electrocardiogram and spirometry measurements.

Results:

The HR, HRV SD of normal-to-normal intervals, HRV root mean square of successive differences, and RR estimates matched within 0.7 beats per minute (SD 0.9), 7 milliseconds (SD 10), 11 milliseconds (SD 12), and 1 breaths per minute (SD 1) mean absolute deviation of the reference measurements, respectively. The quality of the raw plethysmography signal collected by the wristband, as determined by the harmonic-to-noise ratio, was comparable with that obtained from measurements from a finger-clip plethysmography device.

Conclusions:

The accuracy of the biometric estimates and high signal quality indicate that the wristband photoplethysmography device is suitable for performing pulse wave analysis and measuring vital signs.


 Citation

Please cite as:

Dur O, Rhoades C, Ng MS, Elsayed R, van Mourik R, Majmudar MD

Design Rationale and Performance Evaluation of the Wavelet Health Wristband: Benchtop Validation of a Wrist-Worn Physiological Signal Recorder

JMIR Mhealth Uhealth 2018;6(10):e11040

DOI: 10.2196/11040

PMID: 30327288

PMCID: 6231731

Per the author's request the PDF is not available.

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