Study of Acceleration Plethysmogram Based Biometric Identification Incorporating Different Time Instances

Azam, Siti Nurfarah Ain Mohd; Sidek, Khairul Azami

doi:10.1166/asl.2017.10278

Cited by 2 publications

(2 citation statements)

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“…Accounting for the manifestation of these differences in a PPG is known to be an under-researched area [ 110 , 111 ]. For respiratory measurements, Nilsson et al have reported that respiratory synchronous variation in the PPG signal is irrespective of gender, and thus no action is required [ 111 ].…”

Section: Individual Variations In the Human Populationmentioning

confidence: 99%

Sources of Inaccuracy in Photoplethysmography for Continuous Cardiovascular Monitoring

et al. 2021

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Photoplethysmography (PPG) is a low-cost, noninvasive optical technique that uses change in light transmission with changes in blood volume within tissue to provide information for cardiovascular health and fitness. As remote health and wearable medical devices become more prevalent, PPG devices are being developed as part of wearable systems to monitor parameters such as heart rate (HR) that do not require complex analysis of the PPG waveform. However, complex analyses of the PPG waveform yield valuable clinical information, such as: blood pressure, respiratory information, sympathetic nervous system activity, and heart rate variability. Systems aiming to derive such complex parameters do not always account for realistic sources of noise, as testing is performed within controlled parameter spaces. A wearable monitoring tool to be used beyond fitness and heart rate must account for noise sources originating from individual patient variations (e.g., skin tone, obesity, age, and gender), physiology (e.g., respiration, venous pulsation, body site of measurement, and body temperature), and external perturbations of the device itself (e.g., motion artifact, ambient light, and applied pressure to the skin). Here, we present a comprehensive review of the literature that aims to summarize these noise sources for future PPG device development for use in health monitoring.

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Section: Individual Variations In the Human Populationmentioning

confidence: 99%

Sources of Inaccuracy in Photoplethysmography for Continuous Cardiovascular Monitoring

et al. 2021

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“…Past studies have highlighted the potential influence of sex on PPG waveform results [31,32], though there are ongoing debates and differing perspectives regarding sex differences in PPG outcomes [33,34]. Given these unresolved discussions, it is advisable for users to exercise caution when monitoring heart rate data during physical activities using PPG-based smart wristbands [13].…”

Section: Principal Findingsmentioning

confidence: 99%

Assessment of Heart Rate Monitoring During Exercise With Smart Wristbands and a Heart Rhythm Patch: Validation and Comparison Study

Wang,

Wu,

Wang

et al. 2023

JMIR Form Res

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Background The integration of wearable devices into fitness routines, particularly in military settings, necessitates a rigorous assessment of their accuracy. This study evaluates the precision of heart rate measurements by locally manufactured wristbands, increasingly used in military academies, to inform future device selection for military training activities. Objective This research aims to assess the reliability of heart rate monitoring in chest straps versus wearable wristbands. Methods Data on heart rate and acceleration were collected using the Q-Band Q-69 smart wristband (Mobile Action Technology Inc) and compared against the Zephyr Bioharness standard measuring device. The Lin concordance correlation coefficient, Pearson product moment correlation coefficient, and intraclass correlation coefficient were used for reliability analysis. Results Participants from a Northern Taiwanese medical school were enrolled (January 1-June 31, 2021). The Q-Band Q-69 demonstrated that the mean absolute percentage error (MAPE) of women was observed to be 13.35 (SD 13.47). Comparatively, men exhibited a lower MAPE of 8.54 (SD 10.49). The walking state MAPE was 7.79 for women and 10.65 for men. The wristband’s accuracy generally remained below 10% MAPE in other activities. Pearson product moment correlation coefficient analysis indicated gender-based performance differences, with overall coefficients of 0.625 for women and 0.808 for men, varying across walking, running, and cooldown phases. Conclusions This study highlights significant gender and activity-dependent variations in the accuracy of the MobileAction Q-Band Q-69 smart wristband. Reduced accuracy was notably observed during running. Occasional extreme errors point to the necessity of caution in relying on such devices for exercise monitoring. The findings emphasize the limitations and potential inaccuracies of wearable technology, especially in high-intensity physical activities.

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Study of Acceleration Plethysmogram Based Biometric Identification Incorporating Different Time Instances

Cited by 2 publications

References 0 publications

Sources of Inaccuracy in Photoplethysmography for Continuous Cardiovascular Monitoring

Sources of Inaccuracy in Photoplethysmography for Continuous Cardiovascular Monitoring

Assessment of Heart Rate Monitoring During Exercise With Smart Wristbands and a Heart Rhythm Patch: Validation and Comparison Study

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