Brno University of Technology Smartphone PPG Database (BUT PPG): Annotated Dataset for PPG Quality Assessment and Heart Rate Estimation.

To the best of our knowledge, there is no annotated database of PPG signals recorded by smartphone publicly available. This article introduces Brno University of Technology Smartphone PPG Database (BUT PPG) which is an original database created by the cardiology team at the Department of Biomedical Engineering, Brno University of Technology, for the purpose of evaluating photoplethysmographic (PPG) signal quality and estimation of heart rate (HR). The data comprises 48 10-second recordings of PPGs and associated electrocardiographic (ECG) signals used for determination of reference HR. The data were collected from 12 subjects (6 female, 6 male) aged between 21 and 61. PPG data were collected by smartphone Xiaomi Mi9 with sampling frequency of 30 Hz. Reference ECG signals were recorded using a mobile ECG recorder (Bittium Faros 360) with a sampling frequency of 1,000 Hz. Each PPG signal includes annotation of quality created manually by biomedical experts and reference HR. PPG signal quality is indicated binary: 1 indicates good quality for HR estimation, 0 indicates signals where HR cannot be detected reliably, and thus, these signals are unsuitable for further analysis. As the only available database containing PPG signals recorded by smartphone, BUT PPG is a unique tool for the development of smart, user-friendly, cheap, on-the-spot, self-home-monitoring of heart rate with the potential of widespread using.

An Optimizing Dynamic Spectrum Differential Extraction Method for Noninvasive Blood Component Analysis.

Dynamic spectra (DS) can greatly reduce the influence of individual differences and the measurement environment by extracting the absorbance of pulsating blood at multiple wavelengths, and it is expected to achieve noninvasive detection of blood components. Extracting high-quality DS is the prerequisite for improving detection accuracy. This paper proposed an optimizing differential extraction method in view of the deficiency of existing extraction methods. In the proposed method, the sub-dynamic spectrum (sDS) is composed by sequentially extracting the absolute differences of two sample points corresponding to the height of the half peak on the two sides of the lowest point in each period of the logarithm photoplethysmography signal. The study was based on clinical trial data from 231 volunteers. Single-trial extraction method, original differential extraction method, and optimizing differential extraction method were used to extract DS from the volunteers' experimental data. Partial least squares regression (PLSR) and radial basis function (RBF) neural network were used for modeling. According to the effect of PLSR modeling, by extracting DS using the proposed method, the correlation coefficient of prediction set (Rp) has been improved by 17.33% and the root mean square error of prediction set has been reduced by 7.10% compared with the original differential extraction method. Compared with the single-trial extraction method, the correlation coefficient of calibration set (Rc) has increased from 0.747659 to 0.8244, with an increase of 10.26%, while the correlation coefficient of prediction set (Rp) decreased slightly by 3.22%, much lower than the increase of correction set. The result of the RBF neural network modeling also shows that the accuracy of the optimizing differential method is better than the other two methods both in calibration set and prediction set. In general, the optimizing differential extraction method improves the data utilization and credibility compared with the existing extraction methods, and the modeling effect is better than the other two methods.

Pulse transit time estimation of aortic pulse wave velocity and blood pressure using machine learning and simulated training data.

Recent developments in cardiovascular modelling allow us to simulate blood flow in an entire human body. Such model can also be used to create databases of virtual subjects, with sizes limited only by computational resources. In this work, we study if it is possible to estimate cardiovascular health indices using machine learning approaches. In particular, we carry out theoretical assessment of estimating aortic pulse wave velocity, diastolic and systolic blood pressure and stroke volume using pulse transit/arrival timings derived from photopletyshmography signals. For predictions, we train Gaussian process regression using a database of virtual subjects generated with a cardiovascular simulator. Simulated results provides theoretical assessment of accuracy for predictions of the health indices. For instance, aortic pulse wave velocity can be estimated with a high accuracy (r > 0.9) when photopletyshmography is measured from left carotid artery using a combination of foot-to-foot pulse transmit time and peak location derived for the predictions. Similar accuracy can be reached for diastolic blood pressure, but predictions of systolic blood pressure are less accurate (r > 0.75) and the stroke volume predictions are mostly contributed by heart rate.

Noise-Robust Heart Rate Estimation Algorithm from Photoplethysmography Signal with Low Computational Complexity.

This paper introduces a noise-robust HR estimation algorithm using wrist-type PPG signals that consist of preprocessing block, motion artifact reduction block, and frequency tracking block. The proposed algorithm has not only robustness for motion noise but also low computational complexity. The proposed algorithm was tested on a data set of 12 subjects and recorded during treadmill exercise in order to verify and compare with other existing algorithms.

Validation of Polar OH1 optical heart rate sensor for moderate and high intensity physical activities.

BACKGROUND: Optical measurement techniques and recent advances in wearable technology have made heart rate (HR) sensing simpler and more affordable. OBJECTIVES: The Polar OH1 is an arm worn optical heart rate monitor. The objectives of this study are two-fold; 1) to validate the OH1 optical HR sensor with the gold standard of HR measurement, electrocardiography (ECG), over a range of moderate to high intensity physical activities, 2) to validate wearing the OH1 at the temple as an alternative location to its recommended wearing location around the forearm and upper arm. METHODS: Twenty-four individuals participated in a physical exercise protocol, by walking on a treadmill and riding a stationary spin bike at different speeds while the criterion measure, ECG and Polar OH1 HR were recorded simultaneously at three different body locations; forearm, upper arm and the temple. Time synchronised HR data points were compared using Bland-Altman analyses and intraclass correlation. RESULTS: The intraclass correlation between the ECG and Polar OH1, for the aggregated data, was 0.99 and the estimated mean bias ranged 0.27-0.33 bpm for the sensor locations. The three sensors exhibited a 95% limit of agreement (LoA: forearm 5.22, -4.68 bpm; upper arm 5.15, -4.49; temple 5.22, -4.66). The mean of the ECG HR for the aggregated data was 112.15 ± 24.52 bpm. The intraclass correlation of HR values below and above this mean were 0.98 and 0.99 respectively. The reported mean bias ranged 0.38-0.47 bpm (95% LoA: forearm 6.14, -5.38 bpm; upper arm 6.07, -5.13 bpm; temple 6.09, -5.31 bpm), and 0.15-0.16 bpm (95% LoA: forearm 3.99, -3.69 bpm; upper arm 3.90, -3.58 bpm; temple 4.06, -3.76 bpm) respectively. During different exercise intensities, the intraclass correlation ranged 0.95-0.99 for the three sensor locations. During the entire protocol, the estimated mean bias was in the range -0.15-0.55 bpm, 0.01-0.53 bpm and -0.37-0.48 bpm, for the forearm, upper arm and temple locations respectively. The corresponding upper limits of 95% LoA were 3.22-7.03 bpm, 3.25-6.82 bpm and 3.18-7.04 bpm while the lower limits of 95% LoA were -6.36-(-2.35) bpm, -6.46-(-2.30) bpm and -7.42-(-2.41) bpm. CONCLUSION: Polar OH1 demonstrates high level of agreement with the criterion measure ECG HR, thus can be used as a valid measure of HR in lab and field settings during moderate and high intensity physical activities.

Effects of Percutaneous Transluminal Angioplasty of Superficial Femoral Artery on Photoplethysmographic Pulse Transit Times.

We analyze the changes in upper and lower limb pulse transit times (PTT) caused by peripheral artery disease (PAD) and its treatment with percutaneous transluminal angioplasty (PTA) of the superficial femoral artery. PTTs were extracted from the photoplethysmograms (PPG) recorded from an index finger and 2nd toes. PTTs were defined between the R-peaks of the ECG and different reference points of the PPG: foot and peak points, maxima of 1st and 2nd derivative, and by means of intersecting tangents method. Also the PTTs between the toe and finger pulses were analyzed. Our sample consists of 24 subjects examined before and after the PTA and in 1-month follow-up visit. Also 28 older than 65 years controls having normal ankle-to-brachial pressure index (ABI) and no history in cardiovascular diseases as well as 21 younger subjects were examined. The differences between the groups and pre- and post-treatment phases were analyzed by means of non-parametric statistical tests. The changes in the PTTs of upper limb and non-treated lower limb were negligible. The agreement with the reference values, ABI and toe pressures, was studied by kappa-analysis, resulting in kappa-values of 0.33-0.91. Differences in PTTs were found between pre-treatment state of the treated limb, post-treatment state and the follow-up visit, as well as between the pre-treatment state and controls. If patients' age and systolic blood pressure were taken into consideration, the method of lower limb PTT calculation from the peak point turns out feasible in finding the markers of PAD and monitoring post-treatment vascular remodellation.

Time to consider the contact force during photoplethysmography measurement during pediatric anesthesia: A prospective, nonrandomized interventional study.

BACKGROUND: Respiratory variations in photoplethysmography amplitude enable volume status assessment. However, the contact force between the measurement site and sensor can affect photoplethysmography waveforms. We aimed to evaluate contact force effects on respiratory variations in photoplethysmography waveforms in children under general anesthesia. METHODS: Children aged 3-5 years were enrolled. After anesthetic induction, mechanical ventilation commenced at a tidal volume of 10 mL/kg. Photoplethysmographic signals were obtained in the supine position from the index finger using a force sensor-integrated clip-type photoplethysmography sensor that increased the contact force from 0-1.4 N for 20 respiratory cycles at each force. The AC amplitude (pulsatile component), DC amplitude (nonpulsatile component), AC/DC ratio, and respiratory variations in photoplethysmography amplitude were calculated. RESULTS: Data from 34 children were analyzed. Seven contact forces at 0.2-N increments were evaluated for each patient. The normalized AC amplitude increased maximally at a contact force of 0.4-0.6 N and decreased with increasing contact force. However, the normalized DC amplitude increased with a contact force exceeding 0.4 N. ΔPOP decreased slightly and increased from the point when the AC amplitude started to decrease as contact force increased. In a 0.2-1.2 N contact force range, significant changes in the normalized AC amplitude, normalized DC amplitude, AC/DC ratio, and respiratory variations in photoplethysmography amplitude were observed. CONCLUSION: Respiratory variations in photoplethysmography amplitude changed according to variable contact forces; therefore, these measurements may not reflect respiration-induced stroke volume variations. Clinicians should consider contact force bias when interpreting morphological data from photoplethysmography signals.

Recent advances in respiratory monitory in nonoperating room anesthesia.

PURPOSE OF REVIEW: Sedation for nonoperating room procedures is experiencing a considerable increase in demand. Respiratory compromise is one of the most common adverse events seen in sedation. Capnography is a modality that has been widely adopted in this area, but may not be well suited to the special demands of nonoperating room sedation. This review is an assessment of new technologies that may improve outcomes beyond those achievable with capnography. RECENT FINDINGS: New devices for detecting the onset of apnea and for assessing respiratory depression have emerged which have advantages over conventional capnography for detecting apnea without excessive false positive and false negative rates. In addition, monitors that assess respiratory drive have become available, and these may prove useful in regulating depth of sedation. SUMMARY: No single monitor is ideal for all settings. During brief endoscopic sedation, detection of apnea is paramount, while during longer procedures, avoiding excessive respiratory depression is more critical. The clinician must choose the appropriate monitor based on an understanding of the challenges of the particular environment.

Utility of photoplethysmography for heart rate estimation among inpatients.

The accuracy of photoplethysmography (PPG) for heart rate (HR) estimation in cardiac arrhythmia is unknown. PPG-HR was evaluated in 112 hospitalised inpatients (cardiac arrhythmias (n = 60), sinus rhythm (n = 52)) using a continuous electrocardiogram monitoring as a reference standard. Strong agreement was observed in sinus rhythm HR < 100 and atrial flutter (bias 1 beat), modest agreement in sinus tachycardia (bias 24 beats) and complete heart block (bias -6 beats) and weak agreement with significant HR underestimation was seen in atrial fibrillation (bias 23 beats). Routine utilisation of PPG for HR estimation may delay early recognition of clinical deterioration in certain arrhythmias and sinus tachycardia.

Video-based heart rate monitoring across a range of skin pigmentations during an acute hypoxic challenge.

The robust monitoring of heart rate from the video-photoplethysmogram (video-PPG) during challenging conditions requires new analysis techniques. The work reported here extends current research in this area by applying a motion tolerant algorithm to extract high quality video-PPGs from a cohort of subjects undergoing marked heart rate changes during a hypoxic challenge, and exhibiting a full range of skin pigmentation types. High uptimes in reported video-based heart rate (HRvid) were targeted, while retaining high accuracy in the results. Ten healthy volunteers were studied during a double desaturation hypoxic challenge. Video-PPGs were generated from the acquired video image stream and processed to generate heart rate. HRvid was compared to the pulse rate posted by a reference pulse oximeter device (HRp). Agreement between video-based heart rate and that provided by the pulse oximeter was as follows: Bias = - 0.21 bpm, RMSD = 2.15 bpm, least squares fit gradient = 1.00 (Pearson R = 0.99, p < 0.0001), with a 98.78% reporting uptime. The difference between the HRvid and HRp exceeded 5 and 10 bpm, for 3.59 and 0.35% of the reporting time respectively, and at no point did these differences exceed 25 bpm. Excellent agreement was found between the HRvid and HRp in a study covering the whole range of skin pigmentation types (Fitzpatrick scales I-VI), using standard room lighting and with moderate subject motion. Although promising, further work should include a larger cohort with multiple subjects per Fitzpatrick class combined with a more rigorous motion and lighting protocol.

Respiratory variations in the photoplethysmographic waveform amplitude depend on type of pulse oximetry device.

Respiratory variations in the photoplethysmographic waveform amplitude predict fluid responsiveness under certain conditions. Processing of the photoplethysmographic signal may vary between different devices, and may affect respiratory amplitude variations calculated by the standard formula. The aim of the present analysis was to explore agreement between respiratory amplitude variations calculated using photoplethysmographic waveforms available from two different pulse oximeters. Analysis of registrations before and after fluid loads performed before and after open-heart surgery (aortic valve replacement and/or coronary artery bypass grafting) with patients on controlled mechanical ventilation. Photoplethysmographic (Nellcor and Masimo pulse oximeters) and arterial pressure waveforms were recorded. Amplitude variations induced by ventilation were calculated and averaged over ten respiratory cycles. Agreements for absolute values are presented in scatterplots (with least median square regression through the origin, LMSO) and Bland-Altman plots. Agreement for trending presented in a four-quadrant plot. Agreement between respiratory photoplethysmographic amplitude variations from the two pulse oximeters was poor with LMSO ΔPOPNellc = 1.5 × ΔPOPMas and bias ± limits of agreement 7.4 ± 23 %. Concordance rate with a fluid load was 91 %. Agreement between respiratory variations in the photoplethysmographic waveform amplitude calculated from the available signals output by two different pulse oximeters was poor, both evaluated by LMSO and Bland-Altman plot. Respiratory amplitude variations from the available signals output by these two pulse oximeters are not interchangeable.

Photoplethysmography variability as an alternative approach to obtain heart rate variability information in chronic pain patient.

Heart rate variability (HRV) is a well-known method for the assessment of autonomic nervous function of the heart. Previous study suggested that pulse rate variability (PRV) determined by photoplethysmography could be used instead of HRV to more simply assess autonomic nervous function. However, most research studies included healthy subjects. Thus, the aim of this study was to investigate the feasibility for PRV as a surrogate index for patients with chronic pain. This study investigated the correlation coefficient (by Pearson correlation) and agreement (by Bland-Altman analysis) between PRV and HRV in chronic pain patients in the clinical setting. The results showed high significant correlations (p < 0.001, r > 0.86) between all the HRV and PRV parameters and good agreements (ratio < 0.1) between the parameters in terms of HR, mean RR, VLF, LF, nLF, nHF, and SD1/SD2. Our study suggests that HRV can also be reliably estimated using the photoplethysmography-based PP interval in elderly patients with chronic pain.

Recording system and data fusion algorithm for enhancing the estimation of the respiratory rate from photoplethysmogram.

The respiratory rate is a vital parameter that can provide valuable information about the health condition of a patient. The extraction of respiratory information from photoplethysmographic signal (PPG) was actually encouraged by the reported results, our main goal being to obtain accurate respiratory rate estimation from the PPG signal. We developed a fusion algorithm that identifies the best derived respiratory signals, from which is possible to extract the respiratory rate; based on these, a global respiratory rate is computed using the proposed fusion algorithm. The algorithm is qualitatively tested on real PPG signals recorded by an acquisition system we implemented, using a reflection pulse oximeter sensor. Its performance is also statistically evaluated using benchmark dataset publically available from CapnoBase.Org.

Multiscale cross-approximate entropy analysis as a measurement of complexity between ECG R-R interval and PPG pulse amplitude series among the normal and diabetic subjects.

Physiological signals often show complex fluctuation (CF) under the dual influence of temporal and spatial scales, and CF can be used to assess the health of physiologic systems in the human body. This study applied multiscale cross-approximate entropy (MC-ApEn) to quantify the complex fluctuation between R-R intervals series and photoplethysmography amplitude series. All subjects were then divided into the following two groups: healthy upper middle-aged subjects (Group 1, age range: 41-80 years, n = 27) and upper middle-aged subjects with type 2 diabetes (Group 2, age range: 41-80 years, n = 24). There are significant differences of heart rate variability, LHR, between Groups 1 and 2 (1.94 ± 1.21 versus 1.32 ± 1.00, P = 0.031). Results demonstrated differences in sum of large scale MC-ApEn (MC-ApEn(LS)) (5.32 ± 0.50 versus 4.74 ± 0.78, P = 0.003). This parameter has a good agreement with pulse-pulse interval and pulse amplitude ratio (PAR), a simplified assessment for baroreflex activity. In conclusion, this study employed the MC-ApEn method, integrating multiple temporal and spatial scales, to quantify the complex interaction between the two physical signals. The MC-ApEn(LS) parameter could accurately reflect disease process in diabetics and might be another way for assessing the autonomic nerve function.

The analysis of transesophageal oxygen saturation photoplethysmography from different signal sources.

The photoplethysmography (PPG) signals detected by transesophageal oximetry sensor toward aorta arch (AA), descending aorta (DA), and left ventricle (LV) under the guidance of transesophageal echocardiography (TEE) were investigated, and the effects of filter application on PPG signals were evaluated. Eleven cardiac surgical patients were involved. After anesthesia was induced, the TEE probe with a modified pulse oximetry sensor was inserted. Under the guidance of TEE, the AA PPG, DA PPG and LV PPG were detected respectively when ventilator was on and off. The mean alternating current (AC) amplitudes and direct current (DC) values of original and filtered PPG signals were measured. The ratio of AC and DC value (AC/DC) and ventilation-induced AC variations were calculated. Satisfactory PPG waveforms were obtained in all patients under the guidance of TEE. The AC amplitude in LV PPG was significant larger than in AA and DA PPG, and both AC/DC and ventilation-induced AC variation in LV PPG were significantly higher than in AA PPG or DA PPG either. There were no significant differences of AC amplitude between filtered and ventilation off PPG signals. The AC amplitudes and AC/DC toward LV are significantly higher than transesophageal oximeter toward AA or DA, and the effect of mechanical ventilation on transesophageal PPG can be obviously reduced by filtering techniques.

Influence of skin type and wavelength on light wave reflectance.

PURPOSE: A new application of photoplethysmography (PPG) has emerged recently to provide the possibility of heart rate monitoring without a telemetric chest strap. The aim of this study was to determine if a new device could detect pulsation over a broad range of skin types, and what light wavelength would be most suitable for detecting the signals. A light emitting diode-based PPG system was used to detect changes in pulsatile blood flow on 23 apparently healthy individuals (11 male and 12 female, 20-59 years old) of varying skin types classified according to a questionnaire in combination with digital photographs with a skin type chart. Four different light wavelengths (470, 520, 630, and 880 nm) were tested. Normalized modulation level is calculated as the AC/DC component ratio and represents the change in flow over the underlying constant state of flow or perfusion. RESULTS: In the resting condition, green light wavelength (520 nm) displayed greater modulation (p < 0.001) than all the other wavelengths analyzed regardless of skin types. Type V (dark brown) skin type was significantly lower in modulation than all other skin types. In the exercise condition, both blue (470 nm) and green (520 nm) light wavelengths displayed greater signal-to-noise ratios than red (630 nm) or infrared (880 nm) light wavelengths (p < 0.001). CONCLUSIONS: We concluded that a PPG-based device can detect pulsation across all skin types and that a greater resolution was obtained using a green light wavelength at rest and a green or blue light wavelength during exercise.

Reducing motion artifacts in photoplethysmograms by using relative sensor motion: phantom study.

Currently, photoplethysmograms (PPGs) are mostly used to determine a patient's blood oxygenation and pulse rate. However, PPG morphology conveys more information about the patient's cardiovascular status. Extracting this information requires measuring clean PPG waveforms that are free of artifacts. PPGs are highly susceptible to motion, which can distort the PPG-derived data. Part of the motion artifacts are considered to result from sensor-tissue motion and sensor deformation. It is hypothesized that these motion artifacts correlate with movement of the sensor with respect to the skin. This hypothesis has been proven true in a laboratory setup. In vitro PPGs have been measured in a skin perfusion phantom that is illuminated by a laser diode. Optical motion artifacts are generated in the PPG by translating the laser diode with respect to the PPG photodiode. The optical motion artifacts have been reduced significantly in vitro, by using a normalized least-mean-square algorithm with only a single coefficient that uses the laser's displacement as a reference for the motion artifacts. Laser displacement has been measured accurately via self-mixing interferometry by a compact laser diode with a ball lens integrated into the package, which can be easily integrated into a commercial sensor.

Responses of the second derivative of the finger photoplethysmogram indices and hemodynamic parameters to anesthesia induction.

The finger photoplethysmogram (PTG) is a non-invasive method for pulse-wave analysis. The second derivative wave of the PTG (SDPTG) enables evaluation of atherosclerosis and cardiovascular aging. Responses of SDPTG indices and hemodynamic parameters to anesthesia induction are unknown. A total of 42 patients aged 40 years, who may have had atherosclerotic change, and who underwent elective oral surgery, were analyzed. Patients were divided into sevoflurane (S group; N=22) and sevoflurane with remifentanil (R group; N=20) groups. Systolic and diastolic blood pressure (SBP, DBP), heart rate (HR) and SDPTG were measured at four time points: before induction, after loss of consciousness, after tracheal intubation and 30 min after induction. At postintubation, b/a was elevated (that is, large arterial stiffness was increased), and d/a was reduced (that is, peripheral vascular resistance was increased) in the S group compared with the R group. SBP, DBP and HR were increased in the S group compared with those in the R group. In the S group, preanesthetic b/a and the aging index (AGI) were positively correlated with SBP at immediate postintubation, and preanesthetic d/a was negatively correlated with SBP and DBP at immediate postintubation. It is suggested that usage of remifentanil, a potent µ-opioid analgesic, with sevoflurane anesthesia prevented an increase in blood pressure and HR in response to laryngoscopy and tracheal intubation, which was accompanied by suppression of both elevation of b/a and the AGI and reduction of d/a. SDPTG indices are useful for predicting hypertension during induction of sevoflurane anesthesia, regardless of a history of hypertension or hypertensive factors.

Photoplethysmographic measurements from the esophagus using a new fiber-optic reflectance sensor.

A prototype fiber-optic reflectance-mode pulse oximetry sensor and measurement system is developed for the purposes of estimating arterial oxygen saturation in the esophagus. A dedicated probe containing miniature right-angled glass prisms coupled to light sources and a photodetector by means of optical fibers is designed and used to record photoplethysmographic (PPG) signals from the esophageal epithelium in anesthetized patients. The probe is inserted simply by an anesthesiologist in all cases, and signals are recorded successfully in all but one of 20 subjects, demonstrating that esophageal PPG signals can be reliably obtained. The mean value of the oxygen saturation recorded from the esophagus for all subjects is 94.0 ± 4.0%. These results demonstrate that SpO(2) may be estimated in the esophagus using a fiber-optic probe.

Motion-compensated noncontact imaging photoplethysmography to monitor cardiorespiratory status during exercise.

With the advance of computer and photonics technology, imaging photoplethysmography [(PPG), iPPG] can provide comfortable and comprehensive assessment over a wide range of anatomical locations. However, motion artifact is a major drawback in current iPPG systems, particularly in the context of clinical assessment. To overcome this issue, a new artifact-reduction method consisting of planar motion compensation and blind source separation is introduced in this study. The performance of the iPPG system was evaluated through the measurement of cardiac pulse in the hand from 12 subjects before and after 5 min of cycling exercise. Also, a 12-min continuous recording protocol consisting of repeated exercises was taken from a single volunteer. The physiological parameters (i.e., heart rate, respiration rate), derived from the images captured by the iPPG system, exhibit functional characteristics comparable to conventional contact PPG sensors. Continuous recordings from the iPPG system reveal that heart and respiration rates can be successfully tracked with the artifact reduction method even in high-intensity physical exercise situations. The outcome from this study thereby leads to a new avenue for noncontact sensing of vital signs and remote physiological assessment, with clear applications in triage and sports training.