Sources of Inaccuracy in Photoplethysmography for Continuous Cardiovascular Monitoring (original) (raw)
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Evaluating the accuracy of heart rate sensors based on photoplethysmography for in-the-wild analysis
Proceedings of the 13th EAI International Conference on Pervasive Computing Technologies for Healthcare, 2019
Continuous measurement of physiological functions, like heart rate (HR) and heart rate variability (HRV), using commercially available wearable sensors provides the prospects of improving the healthcare of individuals with a positive impact on society, bringing pervasiveness, lower cost, and broader access. However, common wearable devices use photoplethysmography (PPG) to derive data on HR and HRV, and it is yet unclear to which extent PPG signals can be used as a proxy for data collected using medical-grade devices. To address this challenge, we consider five consumer devices to assess the signal quality of HR and two devices measuring HRV and compare them with a standard electrocardiography (ECG) Holter monitor. We collect data from fourteen participants who followed a 55 minutes protocol for at least two sessions. Using this data set, which we make publicly available to the research community, we show that PPG is a valid proxy for both HR and standard time-and frequency-domain measurements of HRV. Further, we demonstrate that wearable devices are suitable for monitoring both HR and HRV in daily life but might be limited during strenuous exercise. The study indicates that armband-based devices are more reliable than wrist-based wearables for HRV assessment.
2018
Photoplethysmography (PPG) is an uncomplicated and inexpensive optical measurement method that is often used for heart rate monitoring purposes. PPG is a non-invasive technology that uses a light source and a photodetector at the surface of skin to measure the volumetric variations of blood circulation. Recently, there has been much interest from numerous researchers around the globe to extract further valuable information from the PPG signal in addition to heart rate estimation and pulse oxymetry readings. PPG signal’s second derivative wave contains important health-related information. Thus, analysis of this waveform can help researchers and clinicians to evaluate various cardiovascular-related diseases such as atherosclerosis and arterial stiffness. Moreover, investigating the second derivative wave of PPG signal can also assist in early detection and diagnosis of various cardiovascular illnesses that may possibly appear later in life. For early recognition and analysis of such ...
Engineering Proceedings
It is very challenging to estimate the accurate heart rate/beat during intense physical activities due to corruption of motion artifacts (MAs). However, it is difficult to reconstruct a clean signal and extract heart rate/beat from contaminated photoplethysmography (PPG) signals. It was also observed that various algorithms have been developed for use in the detection of heart rates during physical activities by reconstructing the contaminated PPG signals to clean PPG signals. Against this backdrop, an overview of the various algorithms was conducted with their results from various works. These results are such that the motion-tolerant adaptive algorithm indicated high agreement and high correlation of more than 0.98 for heart rate (HR) and 0.7 for pulse oxygen saturation (SpO2) extraction between measurements by reference sensors and the algorithm. In addition, the distortion rates were reduced from 52.3% to 3.53%, at frequencies between 1 Hz and 2.5 Hz, when the two-dimensional ac...
Advances in Photoplethysmogram and Electrocardiogram Signal Analysis for Wearable Applications
Photoplethysmography (PPG) is a simple and noninvasive optical method for monitoring people's physiological parameters like oxygen level of blood, pulse rate, heart rate, respiratory rate, blood pressure, blood viscosity, etc. PPG is an optical technique that uses a pulse oximeter to take the measurements. Most of the pulse oximeter has light-emitting diodes (LED's) and photodetector placed at the uppermost layer of the skin to obtain the variation of blood volume in the microvessels of a body. The electrocardiogram (ECG) is the method that shows the action of the heart, and it helps to diagnose any heart-related diseases. Analysis of the PPG signal and ECG signal will help the researchers and doctors to detect various cardiovascular diseases. Measuring the physiological parameters is very essential for people with old age, a woman in pregnancy, and all patients with any other serious situations. PPG technology is becoming familiar because of its easy access, portability, and low cost. Technological development in digital sensors, mobiles, wearable devices, and wireless transmission makes continuous and real-time monitoring feasible. This paper aims to show the present improvements and difficulties of ECG and PPG based monitoring systems.
Dual Wavelength Photoplethysmography Framework for Heart Rate Calculation
Sensors
The quality of heart rate (HR) measurements extracted from human photoplethysmography (PPG) signals are known to deteriorate under appreciable human motion. Auxiliary signals, such as accelerometer readings, are usually employed to detect and suppress motion artifacts. A 2019 study by Yifan Zhang and his coinvestigatorsused the noise components extracted from an infrared PPG signal to denoise a green PPG signal from which HR was extracted. Until now, this approach was only tested on “micro-motion” such as finger tapping. In this study, we extend this technique to allow accurate calculation of HR under high-intensity full-body repetitive “macro-motion”. Our Dual Wavelength (DWL) framework was tested on PPG data collected from 14 human participants while running on a treadmill. The DWL method showed the following attributes: (1) it performed well under high-intensity full-body repetitive “macro-motion”, exhibiting high accuracy in the presence of motion artifacts (as compared to the l...
Healthcare Technology Letters
Wearable physiological monitors are becoming increasingly commonplace in the consumer domain, but in literature there exists no substantive studies of their performance when measuring the physiology of ambulatory patients. In this Letter, the authors investigate the reliability of the heart-rate (HR) sensor in an exemplar 'wearable' wrist-worn monitoring system (the Microsoft Band 2); their experiments quantify the propagation of error from (i) the photoplethysmogram (PPG) acquired by pulse oximetry, to (ii) estimation of HR, and (iii) subsequent calculation of HR variability (HRV) features. Their experiments confirm that motion artefacts account for the majority of this error, and show that the unreliable portions of HR data can be removed, using the accelerometer sensor from the wearable device. The experiments further show that acquired signals contain noise with substantial energy in the high-frequency band, and that this contributes to subsequent variability in standard HRV features often used in clinical practice. The authors finally show that the conventional use of longduration windows of data is not needed to perform accurate estimation of time-domain HRV features.
Imaging Photoplethysmography: a Real-time Signal Quality Index
Computing in Cardiology Conference (CinC)
Imaging photoplethysmography (iPPG) is a promising technology for contactless heart rate (HR) monitoring. However iPPG signals are easily deteriorated by subject movements and illumination changes. The purpose of this study was to develop a signal quality index (SQI) for realtime HR monitoring applications and to assess its performance on a challenging dataset composed of videos of moving subjects. HR was estimated using a multi-input adaptive frequency tracking scheme, in which the iPPG signals derived with different methods and their corresponding SQIs were provided as inputs. Using the proposed SQI, the average absolute error was reduced by 42%/45% when the forehead/entire face region was used to derive iPPG signals, respectively.
PPG Heart Rate Detection in the Presence of Motion Artifacts
2016
Peripheral circulation can elicit a lot of relevant diagnostic information like heart rate and blood oxygenation level without the need of any invasive measurements. Photoplethysmographic(PPG) signals are obtained by such non-invasive measurements using pulse oximeters. PPG signals, although non-invasive, come with some inherent problems. In a nonhospital environment, like when using a wearable type of sensor, a measured PPG signal predominantly suffers from motion artifacts. Ambient light conditions, temperature, and respiratory artifacts are a few other noise sources that affect the PPG signals when trying to measure heart rates. Most motion artifacts lie in the same frequency range as that of the required noise free signal. So, simple filtering is unlikely to work. This work explores adaptive filtering techniques that are commonly used for noise removal. The current work also proposes to use a popular active noise cancellation technique combined with adaptive filtering and artifi...
A Review of Wearable Multi-wavelength Photoplethysmography
IEEE Reviews in Biomedical Engineering, 2021
Optical pulse detection 'photoplethysmography' (PPG) provides a means of low cost and unobtrusive physiological monitoring that is popular in many wearable devices. However, the accuracy, robustness and generalizability of single-wavelength PPG sensing are sensitive to biological characteristics as well as sensor configuration and placement; this is significant given the increasing adoption of single-wavelength wrist-worn PPG devices in clinical studies and healthcare. Since different wavelengths interact with the skin to varying degrees, researchers have explored the use of multi-wavelength PPG to improve sensing accuracy, robustness and generalizability. This paper contributes a novel and comprehensive state-of-the-art review of wearable multi-wavelength PPG sensing, encompassing motion artifact reduction and estimation of physiological parameters. The paper also encompasses theoretical details about multi-wavelength PPG sensing and the effects of biological characteristics. The review findings highlight the promising developments in motion artifact reduction using multi-wavelength approaches, the effects of skin temperature on PPG sensing, the need for improved diversity in PPG sensing studies and the lack of studies that investigate the combined effects of factors. Recommendations are made for the standardization and completeness of reporting in terms of study design, sensing technology and participant characteristics.