Metadata Correction: Clinical Validation of Heart Rate Apps: Mixed-Methods Evaluation

Vandenberk, Thijs; Stans, Jelle; Mortelmans, Christophe; Haelst, Ruth Van; Schelvergem, Gertjan Van; Pelckmans, Caroline; Smeets, C. J. P. P.; Lanssens, Dorien; Cannière, Hélène De; Storms, Valérie; Thijs, Inge M; Vaes, Bert; Vandervoort, Pieter

doi:10.2196/mhealth.9509

Cited by 2 publications

(1 citation statement)

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“…The maximum recommended heart rate [ 9 ] is usually manually entered by the user (or doctor) or calculated. The simplest estimation method is h = 220 – a , where h is the maximum recommended heart rate and a is the age.…”

Section: Methodsmentioning

confidence: 99%

ISO/IEEE 11073 Treadmill Interoperability Framework and its Test Method: Design and Implementation

Huang

Wang

2020

JMIR Med Inform

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Background Regular physical activity is proven to help prevent and treat noncommunicable diseases such as heart disease, stroke, diabetes, and breast and colon cancer. The exercise data generated by health and fitness devices (eg, treadmill, exercise bike) are very important for health management service providers to develop personalized training programs. However, at present, there is little research on a unified interoperability framework in the health and fitness domain, and there are not many solutions; besides, the privatized treadmill data transmission scheme is not conducive to data integration and analysis. Objective This article will expand the IEEE 11073-PHD standard protocol family, develop standards for health and fitness device (using treadmill as an example) based on the latest version of the 11073-20601 optimized exchange protocol, and design protocol standards compliance testing process and inspection software, which can automatically detect whether the instantiated object of the treadmill meets the standard. Methods The study includes the following steps: (1) Map the data transmitted by the treadmill to the 11073-PHD objects; (2) Construct a programming language structure corresponding to the 11073-PHD application protocol data unit (APDU) to complete the coding and decoding part of the test software; and (3) Transmit the instantiated simulated treadmill data to the gateway test software through transmission control protocol for standard compliance testing. Results According to the characteristics of the treadmill, a data exchange framework conforming to 11073-PHD is constructed, and a corresponding testing framework is developed; a treadmill agent simulation is implemented, and the interoperability test is performed. Through the designed testing process, the corresponding testing software was developed to complete the standard compliance testing of the treadmill. Conclusions The extended research of IEEE 11073-PHD in the field of health and fitness provides a potential new idea for the data transmission framework of sports equipment such as treadmills, which may also provide some help for the development of sports health equipment interoperability standards.

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Section: Methodsmentioning

confidence: 99%

ISO/IEEE 11073 Treadmill Interoperability Framework and its Test Method: Design and Implementation

Huang

Wang

2020

JMIR Med Inform

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

Dur¹,

Rhoades²,

Ng³

et al. 2018

JMIR Mhealth Uhealth

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BackgroundWearable 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).ObjectiveThis study aimed to evaluate the accuracy of the biometric estimates and signal quality of the wristband.MethodsMeasurements collected from 35 subjects using the Wavelet wristband were compared with simultaneously recorded electrocardiogram and spirometry measurements.ResultsThe 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.ConclusionsThe 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.

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Metadata Correction: Clinical Validation of Heart Rate Apps: Mixed-Methods Evaluation

Cited by 2 publications

References 0 publications

ISO/IEEE 11073 Treadmill Interoperability Framework and its Test Method: Design and Implementation

ISO/IEEE 11073 Treadmill Interoperability Framework and its Test Method: Design and Implementation

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

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