Dataset Information

An open-source remote heart rate imaging method with practical apparatus and algorithms.

ABSTRACT: Recent developments in computer science and digital image processing have enabled the extraction of an individual's heart pulsations from pixel changes in recorded video images of human skin surfaces. This method is termed remote photoplethysmography (rPPG) and can be achieved with consumer-level cameras (e.g., a webcam or mobile camera). The goal of the present publication is two-fold. First, we aim to organize future rPPG software developments in a tractable and nontechnical manner, such that the public gains access to a basic open-source rPPG code, comes to understand its utility, and can follow its most recent progressions. The second goal is to investigate rPPG's accuracy in detecting heart rates from the skin surfaces of several body parts after physical exercise and under ambient lighting conditions with a consumer-level camera. We report that rPPG is highly accurate when the camera is aimed at facial skin tissue, but that the heart rate recordings from wrist regions are less reliable, and recordings from the calves are unreliable. Facial rPPG remained accurate despite the high heart rates after exercise. The proposed research procedures and the experimental findings provide guidelines for future studies on rPPG.

SUBMITTER: van der Kooij KM

PROVIDER: S-EPMC6797647 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature

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An open-source remote heart rate imaging method with practical apparatus and algorithms.

van der Kooij Koen M KM Naber Marnix M

Behavior research methods 20191001 5

Recent developments in computer science and digital image processing have enabled the extraction of an individual's heart pulsations from pixel changes in recorded video images of human skin surfaces. This method is termed remote photoplethysmography (rPPG) and can be achieved with consumer-level cameras (e.g., a webcam or mobile camera). The goal of the present publication is two-fold. First, we aim to organize future rPPG software developments in a tractable and nontechnical manner, such that ...[more]

PMID: 31152386

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Project description:ObjectiveOpen research on fetal heart rate (FHR) estimation is relatively rare, and evidence for the utility of metrics derived from Doppler ultrasound devices has historically remained hidden in the proprietary documentation of commercial entities, thereby inhibiting its assessment and improvement. Nevertheless, recent studies have attempted to improve FHR estimation; however, these methods were developed and tested using datasets composed of few subjects and are therefore unlikely to be generalizable on a population level. The work presented here introduces a reproducible and generalizable autocorrelation (AC)-based method for FHR estimation from one-dimensional Doppler ultrasound (1D-DUS) signals.ApproachSimultaneous fetal electrocardiogram (fECG) and 1D-DUS signals generated by a hand-held Doppler transducer in a fixed position were captured by trained healthcare workers in a European hospital. The fECG QRS complexes were identified using a previously published fECG extraction algorithm and were then over-read to ensure accuracy. An AC-based method to estimate FHR was then developed on this data, using a total of 721 1D-DUS segments, each 3.75 s long, and parameters were tuned with Bayesian optimization. The trained FHR estimator was tested on two additional (independent) hand-annotated Doppler-only datasets recorded with the same device but on different populations: one composed of 3938 segments (from 99 fetuses) acquired in rural Guatemala, and another composed of 894 segments (from 17 fetuses) recorded in a hospital in the UK.Main resultsThe proposed AC-based method was able to estimate FHR within 10% of the reference FHR values 96% of the time, with an accuracy of 97% for manually identified good quality segments in both of the independent test sets.SignificanceThis is the first work to publish open source code for FHR estimation from 1D-DUS data. The method was shown to satisfy estimations within 10% of the reference FHR values and it therefore defines a minimum accuracy for the field to match or surpass. Our work establishes a basis from which future methods can be developed to more accurately estimate FHR variability for assessing fetal wellbeing from 1D-DUS signals.

Project description:BackgroundHeart rate variability (HRV) is a popular tool to quantify autonomic function. However, this typically requires an expensive 3-12 lead electrocardiogram (ECG) and BioAmp system. This investigation sought to determine the validity and reliability of an OpenBCI cyton biosensing board (open source) for accurately quantifying HRV.New methodA cyton board with a 3-lead ECG was employed to acquire heart rate waveform data, which was processed to obtain HRV within both time- and frequency-domains. The concurrent validity was compared to a simultaneous recording from an industry-standard 3-lead ECG (ADInstruments) (n = 15). The reliability of the cyton board was compared between three days within a 7-day timespan (n = 10). Upright quiet-stance short-term HRV metrics were quantified in time- and frequency-domains.ResultsThe two devices displayed excellent limits of agreements (all log mean differences ±0.4) and very high between-device variable associations (all r 2 > 0.98). Between the three time points in the same subjects, no differences were noted within time- (all p > 0.71) or frequency-domains (all p > 0.88) across testing points. Finally, all HRV metrics exhibited excellent levels of reliability through high Cronbach's Alpha (all ≥0.916) and intraclass correlation coefficients (all ≥0.930); and small standard error of the measurement (all ≤0.7) and typical error of the measurement (all ≤0.1) metrics.Comparison with existing methodsThe cyton board with 3-lead ECG was compared with an industry-standard ADInstruments ECG during HRV assessments. There were no significant differences between devices with respect to time- and frequency-domains. The cyton board displayed high-levels of between-day reliability and provided values harmonious to previous ECG literature highlighting the applicability for longitudinal studies.ConclusionWith proper background knowledge regarding ECG principles and a small degree of set-up complexity, an open source cyton board can be created and employed to perform multimodal HRV assessments at a fraction of the cost (~4%) of an industry-standard ECG setup.

Dataset Information

An open-source remote heart rate imaging method with practical apparatus and algorithms.

Publications

An open-source remote heart rate imaging method with practical apparatus and algorithms.

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