Real-Time Webcam Heart-Rate and Variability Estimation with Clean Ground Truth for Evaluation

Remote photo-plethysmography (rPPG) uses a camera to estimate a person’s heart rate (HR). Similar to how heart rate can provide useful information about a person’s vital signs, insights about the underlying physio/psychological conditions can be obtained from heart rate variability (HRV). HRV is a measure of the fine fluctuations in the intervals between heart beats. However, this measure requires temporally locating heart beats with a high degree of precision. We introduce a refined and efficient real-time rPPG pipeline with novel filtering and motion suppression that not only estimates heart rates, but also extracts the pulse waveform to time heart beats and measure heart rate variability. This unsupervised method requires no rPPG specific training and is able to operate in real-time. We also introduce a new multi-modal video dataset, VicarPPG 2, specifically designed to evaluate rPPG algorithms on HR and HRV estimation. We validate and study our method under various conditions on a comprehensive range of public and self-recorded datasets, showing state-of-the-art results and providing useful insights into some unique aspects. Lastly, we make available CleanerPPG, a collection of human-verified ground truth peak/heart-beat annotations for existing rPPG datasets. These verified annotations should make future evaluations and benchmarking of rPPG algorithms more accurate, standardized and fair.

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Heart Rate Variability, Emotions, and Music

Journal of Psychophysiology ◽

10.1027/0269-8803/a000021 ◽

2010 ◽

Vol 24 (2) ◽

pp. 112-119 ◽

Cited By ~ 9

Author(s):

F. Riganello ◽

A. Candelieri ◽

M. Quintieri ◽

G. Dolce

Keyword(s):

Data Mining ◽

Heart Rate ◽

Heart Rate Variability ◽

Vegetative State ◽

Low Frequency ◽

Emotional Reactions ◽

Heart Beat ◽

Healthy Controls ◽

Frequency Spectra ◽

Emotional Value

The purpose of the study was to identify significant changes in heart rate variability (an emerging descriptor of emotional conditions; HRV) concomitant to complex auditory stimuli with emotional value (music). In healthy controls, traumatic brain injured (TBI) patients, and subjects in the vegetative state (VS) the heart beat was continuously recorded while the subjects were passively listening to each of four music samples of different authorship. The heart rate (parametric and nonparametric) frequency spectra were computed and the spectra descriptors were processed by data-mining procedures. Data-mining sorted the nu_lf (normalized parameter unit of the spectrum low frequency range) as the significant descriptor by which the healthy controls, TBI patients, and VS subjects’ HRV responses to music could be clustered in classes matching those defined by the controls and TBI patients’ subjective reports. These findings promote the potential for HRV to reflect complex emotional stimuli and suggest that residual emotional reactions continue to occur in VS. HRV descriptors and data-mining appear applicable in brain function research in the absence of consciousness.

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An Examination of Real-Time Heart Rate Variability During Laparoscopic Cholecystectomies and Radical Surgeries

10.21236/ada389114 ◽

2000 ◽

Cited By ~ 1

Author(s):

K. Zaglaniczny ◽

W. Shoemaker ◽

D. S. Gorguze ◽

C. Woo ◽

J. Colombo

Keyword(s):

Heart Rate ◽

Heart Rate Variability ◽

Real Time

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Real-Time Analysis of Heart Rate Variability Patterns during Hemodialysis

2019 23rd International Computer Science and Engineering Conference (ICSEC) ◽

10.1109/icsec47112.2019.8974764 ◽

2019 ◽

Author(s):

Motoki Tanaka ◽

Yasuyuki Satoh ◽

Osamu Sakata

Keyword(s):

Heart Rate ◽

Heart Rate Variability ◽

Real Time ◽

Time Analysis ◽

Real Time Analysis

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Detecting Pedestrian Situation Awareness in Real-Time: Algorithm Development Using Heart Rate Variability and Phone Position

Proceedings of the Human Factors and Ergonomics Society Annual Meeting ◽

10.1177/1541931218621357 ◽

2018 ◽

Vol 62 (1) ◽

pp. 1579-1583

Author(s):

Yourui Tong ◽

Bochen Jia ◽

Yi Wang ◽

Si Yang

Keyword(s):

Heart Rate ◽

Heart Rate Variability ◽

Real Time ◽

Situation Awareness ◽

Mental State ◽

Time Algorithm ◽

Support Vector ◽

Vehicle Design ◽

Automated Vehicle ◽

Hrv Analysis

To help automated vehicles learn surrounding environments via V2X communications, it is important to detect and transfer pedestrian situation awareness to the related vehicles. Based on the characteristics of pedestrians, a real-time algorithm was developed to detect pedestrian situation awareness. In the study, the heart rate variability (HRV) and phone position were used to understand the mental state and distractions of pedestrians. The HRV analysis was used to detect the fatigue and alert state of the pedestrian, and the phone position was used to define the phone distractions of the pedestrian. A Support Vector Machine algorithm was used to classify the pedestrian’s mental state. The results indicated a good performance with 86% prediction accuracy. The developed algorithm shows high applicability to detect the pedestrian’s situation awareness in real-time, which would further extend our understanding on V2X employment and automated vehicle design.

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Heart Rate monitor based on IP networking

MATEC Web of Conferences ◽

10.1051/matecconf/201821001006 ◽

2018 ◽

Vol 210 ◽

pp. 01006

Author(s):

Miguel G. Molina ◽

Priscila E. Garzón ◽

Carolina J. Molina ◽

Juan X. Nicola

Keyword(s):

Heart Rate ◽

Real Time ◽

Electronic Devices ◽

Vital Signs ◽

Well Being ◽

Heart Rate Monitor ◽

Ip Address ◽

Health Concept ◽

New Applications ◽

Threat Situation

With the uprising of Internet of Things (IoT) networks, new applications have taken advantage of this new concept. Having all devices and all people connected 24/7 have several advantages in a variated amount of disciplines. One of them is medicine and the e-health concept. The possibility of having a real time lecture of the vital signs of people can prevent a live threat situation. This paper describes the realization of a device capable of measuring the heart rate of a person and checking for abnormalities that may negatively affect the patient’s well-being. This project will make use of electronic devices known as microcontrollers, specifically from the Arduino family, enabling us to capture data, and, with the help of a network card and a RJ-45 cable, transfer it to a PC and visualize the heart rate in real time over its assigned IP address.

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Non-intrusive vital sign monitoring using an intelligent pillow based on a piezoelectric ceramic sensor

Journal of Engineered Fibers and Fabrics ◽

10.1177/1558925020977268 ◽

2020 ◽

Vol 15 ◽

pp. 155892502097726

Author(s):

Wei Wang ◽

Zhiqiang Pang ◽

Ling Peng ◽

Fei Hu

Keyword(s):

Heart Rate ◽

Real Time ◽

Piezoelectric Ceramic ◽

Low Cost ◽

Body Movement ◽

Vital Signs ◽

High Heart Rate ◽

Detection Accuracy ◽

Processing Unit ◽

Real Time Monitoring

Performing real-time monitoring for human vital signs during sleep at home is of vital importance to achieve timely detection and rescue. However, the existing smart equipment for monitoring human vital signs suffers the drawbacks of high complexity, high cost, and intrusiveness, or low accuracy. Thus, it is of great need to develop a simplified, nonintrusive, comfortable and low cost real-time monitoring system during sleep. In this study, a novel intelligent pillow was developed based on a low-cost piezoelectric ceramic sensor. It was manufactured by locating a smart system (consisting of a sensing unit i.e. a piezoelectric ceramic sensor, a data processing unit and a GPRS communication module) in the cavity of the pillow made of shape memory foam. The sampling frequency of the intelligent pillow was set at 1000 Hz to capture the signals more accurately, and vital signs including heart rate, respiratory rate and body movement were derived through series of well established algorithms, which were sent to the user’s app. Validation experimental results demonstrate that high heart-rate detection accuracy (i.e. 99.18%) was achieved in using the intelligent pillow. Besides, human tests were conducted by detecting vital signs of six elder participants at their home, and results showed that the detected vital signs may well predicate their health conditions. In addition, no contact discomfort was reported by the participants. With further studies in terms of validity of the intelligent pillow and large-scale human trials, the proposed intelligent pillow was expected to play an important role in daily sleep monitoring.

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