A Pulse Rate Estimation Algorithm Using PPG and Smartphone Camera

Siddiqui, Sarah; Zhang, Yuwei; Feng, Zhiquan; Kos, Anton

doi:10.1007/s10916-016-0485-6

Cited by 55 publications

(22 citation statements)

References 23 publications

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“…In other studies, similar luminosity or brightness data (or just the data of the red channel) were used for computations (in the RGB video recording mode) [27, 28]. It can be seen that these techniques are equivalent, because in the RGB mode, all the blue and green pixel values are zeros and, consequently, all the linear combinations of RGB channels will result in similar curves like those for luminosity.…”

Section: Methodsmentioning

confidence: 99%

Analysis of a Pulse Rate Variability Measurement Using a Smartphone Camera

Bánhalmi

Borbás

Fidrich

et al. 2018

Journal of Healthcare Engineering

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Background Heart rate variability (HRV) provides information about the activity of the autonomic nervous system. Because of the small amount of data collected, the importance of HRV has not yet been proven in clinical practice. To collect population-level data, smartphone applications leveraging photoplethysmography (PPG) and some medical knowledge could provide the means for it. Objective To assess the capabilities of our smartphone application, we compared PPG (pulse rate variability (PRV)) with ECG (HRV). To have a baseline, we also compared the differences among ECG channels. Method We took fifty parallel measurements using iPhone 6 at a 240 Hz sampling frequency and Cardiax PC-ECG devices. The correspondence between the PRV and HRV indices was investigated using correlation, linear regression, and Bland-Altman analysis. Results High PPG accuracy: the deviation of PPG-ECG is comparable to that of ECG channels. Mean deviation between PPG-ECG and two ECG channels: RR: 0.01 ms–0.06 ms, SDNN: 0.78 ms–0.46 ms, RMSSD: 1.79 ms–1.21 ms, and pNN50: 2.43%–1.63%. Conclusions Our iPhone application yielded good results on PPG-based PRV indices compared to ECG-based HRV indices and to differences among ECG channels. We plan to extend our results on the PPG-ECG correspondence with a deeper analysis of the different ECG channels.

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Section: Methodsmentioning

confidence: 99%

Analysis of a Pulse Rate Variability Measurement Using a Smartphone Camera

Bánhalmi

Borbás

Fidrich

et al. 2018

Journal of Healthcare Engineering

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“…PPG estimates the volumetric changes in blood by detecting the fluctuation of transmissivity and/or reflectivity of light with arterial pulsation through the tissue (Figure 4) [22,35]. Although near-infrared (NIR), red light sources are used in most commercial systems [22,35], some researchers [36,37,38,39,40] exploited the smartphone embedded white flashlight to illuminate the tissue to measure the PPG.…”

Section: Smartphone Sensors For Health Monitoringmentioning

confidence: 99%

Smartphone Sensors for Health Monitoring and Diagnosis

Majumder

Deen

2019

Sensors

308

162

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Over the past few decades, we have witnessed a dramatic rise in life expectancy owing to significant advances in medical science and technology, medicine as well as increased awareness about nutrition, education, and environmental and personal hygiene. Consequently, the elderly population in many countries are expected to rise rapidly in the coming years. A rapidly rising elderly demographics is expected to adversely affect the socioeconomic systems of many nations in terms of costs associated with their healthcare and wellbeing. In addition, diseases related to the cardiovascular system, eye, respiratory system, skin and mental health are widespread globally. However, most of these diseases can be avoided and/or properly managed through continuous monitoring. In order to enable continuous health monitoring as well as to serve growing healthcare needs; affordable, non-invasive and easy-to-use healthcare solutions are critical. The ever-increasing penetration of smartphones, coupled with embedded sensors and modern communication technologies, make it an attractive technology for enabling continuous and remote monitoring of an individual’s health and wellbeing with negligible additional costs. In this paper, we present a comprehensive review of the state-of-the-art research and developments in smartphone-sensor based healthcare technologies. A discussion on regulatory policies for medical devices and their implications in smartphone-based healthcare systems is presented. Finally, some future research perspectives and concerns regarding smartphone-based healthcare systems are described.

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“…Many researchers have used the principle of photoplethysmography (PPG) to measure the heart rate using smartphones. The researchers have validated the smartphone PPG based method for calculating heart rate [7][10] [15]. Daniel J Plews et al [8] have validated the method of measuring heart rate using PPG signals captured using smartphone to be a preferable one for athletes.…”

Section: Introductionmentioning

confidence: 99%

“…Arteries are close to the skin such as fingertip or on earlobe , hence the change of blood volume in the finger artery can be detected easily. PPG is an optical technique used to measure the change in the quantity of blood in the skin surface by shining a light on the skin surface with a light source [7].…”

Section: Introductionmentioning

confidence: 99%