Rehabilitation Assessment System for Stroke Patients Based on Fusion-Type Optoelectronic Plethysmography Device and Multi-Modality Fusion Model: Design and Validation.

This study aimed to propose a portable and intelligent rehabilitation evaluation system for digital stroke-patient rehabilitation assessment. Specifically, the study designed and developed a fusion device capable of emitting red, green, and infrared lights simultaneously for photoplethysmography (PPG) acquisition. Leveraging the different penetration depths and tissue reflection characteristics of these light wavelengths, the device can provide richer and more comprehensive physiological information. Furthermore, a Multi-Channel Convolutional Neural Network-Long Short-Term Memory-Attention (MCNN-LSTM-Attention) evaluation model was developed. This model, constructed based on multiple convolutional channels, facilitates the feature extraction and fusion of collected multi-modality data. Additionally, it incorporated an attention mechanism module capable of dynamically adjusting the importance weights of input information, thereby enhancing the accuracy of rehabilitation assessment. To validate the effectiveness of the proposed system, sixteen volunteers were recruited for clinical data collection and validation, comprising eight stroke patients and eight healthy subjects. Experimental results demonstrated the system's promising performance metrics (accuracy: 0.9125, precision: 0.8980, recall: 0.8970, F1 score: 0.8949, and loss function: 0.1261). This rehabilitation evaluation system holds the potential for stroke diagnosis and identification, laying a solid foundation for wearable-based stroke risk assessment and stroke rehabilitation assistance.

An Inkjet-Printed PEDOT:PSS-Based Stretchable Conductor for Wearable Health Monitoring Device Applications.

A stretchable conductor is one of the key components in soft electronics that allows the seamless integration of electronic devices and sensors on elastic substrates. Its unique advantages of mechanical flexibility and stretchability have enabled a variety of wearable bioelectronic devices that can conformably adapt to curved skin surfaces for long-term health monitoring applications. Here, we report a poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS)-based stretchable polymer blend that can be patterned using an inkjet printing process while exhibiting low sheet resistance and accommodating large mechanical deformations. We have systematically studied the effect of various types of polar solvent additives that can help induce phase separation of PEDOT and PSS grains and change the conformation of a PEDOT chain, thereby improving the electrical property of the film by facilitating charge hopping along the percolating PEDOT network. The optimal ink formulation is achieved by adding 5 wt % ethylene glycol into a pristine PEDOT:PSS aqueous solution, which results in a sheet resistance of as low as 58 Ω/□. Elasticity can also be achieved by blending the above solution with the soft polymer poly(ethylene oxide) (PEO). Thin films of PEDOT:PSS/PEO polymer blends patterned by inkjet printing exhibits a low sheet resistance of 84 Ω/□ and can resist up to 50% tensile strain with minimal changes in electrical performance. With its good conductivity and elasticity, we have further demonstrated the use of the polymer blend as stretchable interconnects and stretchable dry electrodes on a thin polydimethylsiloxane (PDMS) substrate for photoplethysmography (PPG) and electrocardiography (ECG) recording applications. This work shows the potential of using a printed stretchable conducting polymer in low-cost wearable sensor patches for smart health applications.

On-Device Reliability Assessment and Prediction of Missing Photoplethysmographic Data Using Deep Neural Networks.

Photoplethysmographic (PPG) measurements from ambulatory subjects may suffer from unreliability due to body movements and missing data segments due to loosening of sensor. This paper describes an on-device reliability assessment from PPG measurements using a stack denoising autoencoder (SDAE) and multilayer perceptron neural network (MLPNN). The missing segments were predicted by a personalized convolutional neural network (CNN) and long-short term memory (LSTM) model using a short history of the same channel data. Forty sets of volunteers' data, consisting of equal share of healthy and cardiovascular subjects were used for validation and testing. The PPG reliability assessment model (PRAM) achieved over 95% accuracy for correctly identifying acceptable PPG beats out of total 5000 using expert annotated data. Disagreement with experts' annotation was nearly 3.5%. The missing segment prediction model (MSPM) achieved a root mean square error (RMSE) of 0.22, and mean absolute error (MAE) of 0.11 for 40 missing beats prediction using only four beat history from the same channel PPG. The two models were integrated in a standalone device based on quad-core ARM Cortex-A53, 1.2 GHz, with 1 GB RAM, with 130 MB memory requirement and latency ∼0.35 s per beat prediction with a 30 s frame. The present method also provides improved performance with published works on PPG quality assessment and missing data prediction using two public datasets, CinC and MIMIC-II under PhysioNet.

Monitoring driver health status in real time.

Nowadays, surveillance systems have evolved significantly; hence, in order to meet the specific needs of the health sector and to monitor the patients' health conditions, intelligent systems have been proposed. These innovations represent a primordial role in road safety, which reduce the risk of traffic accidents. This paper describes an intelligent system design for remote monitoring (tele-monitoring) of a driver's health condition in real time. The measurement using new hardware and software devices is made possible through the contact between the driver contact and an intelligent steering wheel, which is coupled either to an integrated monitor or to a bluetooth link with a local Android smartphone. The driver's heart rate is calculated through the continuous collection of the electrocardiographic signal as well as the blood oxygen saturation SpO2 by using the photoplethysmographic technique. Consequently, it is necessary to monitor the two vital functions of the driver, cardiac and respiratory activity. This information is transmitted to a remote tele-vigilance center in the case of abnormalities in these functions under the transmission control protocol/internet protocol involving a 4G/3G connection. The application is associated with the system that triggers high and low alarms locally and remotely in the events of tachycardia, bradycardia, or cardiac arrhythmia. Furthermore, another alarm is also triggered in the event of respiratory decompensation.

Feasible assessment of recovery and cardiovascular health: accuracy of nocturnal HR and HRV assessed via ring PPG in comparison to medical grade ECG.

OBJECTIVE: To validate the accuracy of the Oura ring in the quantification of resting heart rate (HR) and heart rate variability (HRV). BACKGROUND: Wearable devices have become comfortable, lightweight, and technologically advanced for assessing health behavior. As an example, the novel Oura ring integrates daily physical activity and nocturnal cardiovascular measurements. Ring users can follow their autonomic nervous system responses to their daily behavior based on nightly changes in HR and HRV, and adjust their behavior accordingly after self-reflection. As wearable photoplethysmogram (PPG) can be disrupted by several confounding influences, it is crucial to demonstrate the accuracy of ring measurements. APPROACH: Nocturnal HR and HRV were assessed in 49 adults with simultaneous measurements from the Oura ring and the gold standard ECG measurement. Female and male participants with a wide age range (15-72 years) and physical activity status were included. Regression analysis between ECG and the ring outcomes was performed. MAIN RESULTS: Very high agreement between the ring and ECG was observed for nightly average HR and HRV (r2 = 0.996 and 0.980, respectively) with a mean bias of -0.63 bpm and -1.2 ms. High agreement was also observed across 5 min segments within individual nights in (r2 = 0.869 ± 0.098 and 0.765 ± 0.178 in HR and HRV, respectively). SIGNIFICANCE: Present findings indicate high validity of the Oura ring in the assessment of nocturnal HR and HRV in healthy adults. The results show the utility of this miniaturised device as a lifestyle management tool in long-term settings. High quality PPG signal results prompt future studies utilizing ring PPG towards clinically relevant health outcomes.

In silico and in vivo investigations using an endocavitary photoplethysmography sensor for tissue viability monitoring.

SIGNIFICANCE: Colorectal cancer is one of the major causes of cancer-related deaths worldwide. Surgical removal of the cancerous growth is the primary treatment for this disease. A colorectal cancer surgery, however, is often unsuccessful due to the anastomotic failure that may occur following the surgical incision. Prevention of an anastomotic failure requires continuous monitoring of intestinal tissue viability during and after colorectal surgery. To date, no clinical technology exists for the dynamic and continuous monitoring of the intestinal perfusion. AIM: A dual-wavelength indwelling bowel photoplethysmography (PPG) sensor for the continuous monitoring of intestinal viability was proposed and characterized through a set of in silico and in vivo investigations. APPROACH: The in silico investigation was based on a Monte Carlo model that was executed to quantify the variables such as penetration depth and detected intensity with respect to the sensor-tissue separations and tissue perfusion. Utilizing the simulated information, an indwelling reflectance PPG sensor was designed and tested on 20 healthy volunteers. Two sets of in vivo studies were performed using the driving current intensities 20 and 40 mA for a comparative analysis, using buccal tissue as a proxy tissue-site. RESULTS: Both simulated and experimental results showed the efficacy of the sensor to acquire good signals through the "contact" to a "noncontact" separation of 5 mm. A very slow wavelength-dependent variation was shown in the detected intensity at the normal and hypoxic states of the tissue, whereas a decay in the intensity was found with the increasing submucosal-blood volume. The simulated detected-to-incident-photon-ratio and the experimental signal-to-noise ratio exhibited strong positive correlations, with the Pearson product-moment correlation coefficient R ranging between 0.65 and 0.87. CONCLUSIONS: The detailed feasibility analysis presented will lead to clinical trials utilizing the proposed sensor.

A Wristwatch-Based Wireless Sensor Platform for IoT Health Monitoring Applications.

A wristwatch-based wireless sensor platform for IoT wearable health monitoring applications is presented. The paper describes the platform in detail, with a particular focus given to the design of a novel and compact wireless sub-system for 868 MHz wristwatch applications. An example application using the developed platform is discussed for arterial oxygen saturation (SpO2) and heart rate measurement using optical photoplethysmography (PPG). A comparison of the wireless performance in the 868 MHz and the 2.45 GHz bands is performed. Another contribution of this work is the development of a highly integrated 868 MHz antenna. The antenna structure is printed on the surface of a wristwatch enclosure using laser direct structuring (LDS) technology. At 868 MHz, a low specific absorption rate (SAR) of less than 0.1% of the maximum permissible limit in the simulation is demonstrated. The measured on-body prototype antenna exhibits a -10 dB impedance bandwidth of 36 MHz, a peak realized gain of -4.86 dBi and a radiation efficiency of 14.53% at 868 MHz. To evaluate the performance of the developed 868 MHz sensor platform, the wireless communication range measurements are performed in an indoor environment and compared with a commercial Bluetooth wristwatch device.

A 2.6 µW Monolithic CMOS Photoplethysmographic (PPG) Sensor Operating With 2 µW LED Power for Continuous Health Monitoring.

Photoplethysmography (PPG) enables wearable vitals monitoring. Nevertheless, it is still limited by the few mA of the LEDs driving current. We present a PPG sensor integrating an array of dedicated pinned-photodiodes (PPD) with a full readout chain integrated in a 0.18 µm CMOS Image Sensor (CIS) process. The sensor features a total input referred noise of 0.68 e-rms per PPD, independently of the input light, and achieves a 4.6 µW total power consumption, including the 2 µW LED power, at 1.38 bpm heart rate average error.

Accuracy of PurePulse photoplethysmography technology of Fitbit Charge 2 for assessment of heart rate during sleep.

Elevated asleep heart rate (HR) is a risk factor for cardiovascular disease and other-cause morbidity and mortality. We assessed the accuracy of Fitbit Inc. PurePulse® photoplethysmography with reference to three-lead electrocardiography (ECG) in determining HR during sleep. HR of 35 (17 female) healthy adults 25.1 ± 10.6 years of age (mean ± SD) was continuously recorded throughout a single night of sleep. There was no significant difference in asleep HR mean (0.09 beats per minute [bpm], P = 0.426) between Fitbit photoplethysmography and ECG; plus, there was excellent intraclass correlation (0.998) and narrow Bland-Altman agreement range (2.67 bpm). The regression analysis of Bland-Altman plot of mean asleep HR indicates Fitbit tends to slightly overestimate reference values in the lower range of HR (HR < 50 bpm) by 0.51 bpm and slightly underestimate reference values in the higher range of HR (HR > 80 bpm) by 0.63 bpm. Mixed model analysis of epoch-by-epoch (5-min epochs) asleep HR showed significant "U" shape trend (P < 0.001) in amount of Fitbit error (absolute amount of difference between ECG and Fitbit values regardless of overestimation or underestimation) in regard to HR, i.e. smaller error in the medium range of HR (60-80 bpm) and slightly larger error for lower (<60 bpm) and higher (>80 bpm) ranges of HR. However, effect of age, body mass index, gender, and subjective sleep quality measured by Pittsburgh sleep quality index (good/poor sleepers) on error in estimating HR by the Fitbit method was not significant. It is concluded that Fitbit photoplethysmography suitably tracks HR during sleep in healthy young adults.

Low-Cost Mobile Device for Screening of Atherosclerosis and Coronary Arterial Disease.

In the context of global health, telemedicine, and low-resource settings, we present a non-invasive smart-phone based device that can be used to screen for atherosclerosis,which is the leading factor for ischemic heart attacks and strokes. Using acustom Android mobile application, our device computes Pulse Wave Velocity(PWV) using the pulse signals from photo-plethysmographic (PPG) probes, which are simultaneously clipped onto the ear, index finger, and big toe of a human subject. Unlike other designs which require the use of an ECG reference, our mobile device uses only PPG signals and is entirely powered by the mobile phone via the USB port. Using the ear signal as a reference, we derived PWV values from two locations: the right index finger, and the right big toe.We present data from a recent clinical study with 78 participants (age 26 to 74) who were divided into three groups: Coronary Arterial Disease ("CAD"), hypertensive group ("PreCAD"), and Healthy controls. The CAD group was clinically diagnosed and confirmed with a CT-scan and calcium scoring. PWV values derived from the finger was found to have too much variance to be clinically useful. However, PWV values derived from the toe location showed significant differences between the groups, even after accounting for age. Measured PWV values were: 10.07 (8.51-12.01) for the older CAD group, 9.39 (7.44-9.75) for the younger CAD group, 8.26 (7.26-9.22) for the older Pre-CAD group, 10.57 m/s (8.5-11.2) for the younger Pre-CAD group, 7.13 m/s (5.97-7.69) for older healthy controls, and 6.71 m/s (4.86-7.26) for the younger healthy control subjects. These results demonstrate good potential value of this mobile PWV device as a simple low-cost screening tool for atherosclerosis and coronary arterial disease.

Cardiovascular assessment by imaging photoplethysmography - a review.

Over the last few years, the contactless acquisition of cardiovascular parameters using cameras has gained immense attention. The technique provides an optical means to acquire cardiovascular information in a very convenient way. This review provides an overview on the technique's background and current realizations. Besides giving detailed information on the most widespread application of the technique, namely the contactless acquisition of heart rate, we outline further concepts and we critically discuss the current state.

New insights into the origin of remote PPG signals in visible light and infrared.

Remote photoplethysmography (PPG) is an optical measurement technique with established applications in vital signs monitoring. Recently, the consensual understanding of blood volume variations (BVVs) as the origin of PPG signals was challenged, raising validity concerns about the remote SpO2 methodology. Recognizing the imperative for new opto-physiological evidence, this investigation supports the volumetric hypothesis with living skin experiments and Monte Carlo simulations of remote PPG-amplitude in visible light (VIS) and infrared (IR). Multilayered models of the skin were developed to simulate the separate contributions from skin layers containing pulsatile arterioles to the PPG signal in the 450-1000 nm range. The simulated spectra were qualitatively compared with observations of the resting and compressed finger pad, and complemented with videocapillaroscopy. Our results indicate that remote PPG systems indeed probe arterial blood. Green wavelengths probe dermal arterioles while red-IR wavelengths also reach subcutaneous BVVs. Owing to stable penetration depths, the red-IR diagnostic window promotes the invariance of SpO2 measurements to skin non-homogeneities.

Diagnostic assessment of a deep learning system for detecting atrial fibrillation in pulse waveforms.

OBJECTIVE: To evaluate the diagnostic performance of a deep learning system for automated detection of atrial fibrillation (AF) in photoplethysmographic (PPG) pulse waveforms. METHODS: We trained a deep convolutional neural network (DCNN) to detect AF in 17 s PPG waveforms using a training data set of 149 048 PPG waveforms constructed from several publicly available PPG databases. The DCNN was validated using an independent test data set of 3039 smartphone-acquired PPG waveforms from adults at high risk of AF at a general outpatient clinic against ECG tracings reviewed by two cardiologists. Six established AF detectors based on handcrafted features were evaluated on the same test data set for performance comparison. RESULTS: In the validation data set (3039 PPG waveforms) consisting of three sequential PPG waveforms from 1013 participants (mean (SD) age, 68.4 (12.2) years; 46.8% men), the prevalence of AF was 2.8%. The area under the receiver operating characteristic curve (AUC) of the DCNN for AF detection was 0.997 (95% CI 0.996 to 0.999) and was significantly higher than all the other AF detectors (AUC range: 0.924-0.985). The sensitivity of the DCNN was 95.2% (95% CI 88.3% to 98.7%), specificity was 99.0% (95% CI 98.6% to 99.3%), positive predictive value (PPV) was 72.7% (95% CI 65.1% to 79.3%) and negative predictive value (NPV) was 99.9% (95% CI 99.7% to 100%) using a single 17 s PPG waveform. Using the three sequential PPG waveforms in combination (<1 min in total), the sensitivity was 100.0% (95% CI 87.7% to 100%), specificity was 99.6% (95% CI 99.0% to 99.9%), PPV was 87.5% (95% CI 72.5% to 94.9%) and NPV was 100% (95% CI 99.4% to 100%). CONCLUSIONS: In this evaluation of PPG waveforms from adults screened for AF in a real-world primary care setting, the DCNN had high sensitivity, specificity, PPV and NPV for detecting AF, outperforming other state-of-the-art methods based on handcrafted features.

A new method for the assessment of endothelial function with peripheral arterial volume.

BACKGROUND: Currently, many methodological approaches have been developed to assess peripheral endothelial function. However, a development of the noninvasive and automated technique for routinely assessing endothelial function is still required. We evaluated the potential value of a new method to measure peripheral endothelial function with reactive hyperemia peripheral arterial volume (RH-PAV) in patients with chest pain. METHODS: We used a novel oximeter-like probe to detect the peripheral arterial volume (PAV) of the finger and compared it with brachial flow-mediated dilation (FMD) performed in 93 consecutive patients with chest pain. The RH-PAV index was defined as the ratio of the digital pulse volume during reactive hyperemia relative to the baseline. RESULTS: Ninety-three patients (53 men, 58 ± 5 years) completed the study, and 53 patients demonstrated coronary artery disease (CAD) following scheduled coronary angiography. There was a moderate linear relationship between PAV and FMD (r = 0.69, p < 0.01). Similar to FMD, PAV was more impaired in patients who have more cardiovascular risk factors (CRFs). The subjects with CAD had lower PAV and FMD, compared with those without CAD (1.05 ± 0.23 VS. 1.41 ± 0.37, p < 0.01; 6.7% ± 2.9% VS. 10.4% ± 2.9%, p < 0.01, respectively), and the relationships between FMD and PAV were also significant in both CAD (r = 0.54, p < 0.01) and non-CAD (r = 0.62, p < 0.01) patients. CONCLUSIONS: Endothelial function of digital artery assessed with the novel PAV method demonstrated a profile similar to that of brachial artery measured with FMD. The hyperemia PAV was decreased by factors which were considered to impair endothelial function, suggesting that PAV has the potential to be a novel method to study endothelial function.

Photoplethysmography using a smartphone application for assessment of ulnar artery patency: a randomized clinical trial.

BACKGROUND: Radial artery access is commonly performed for coronary angiography and invasive hemodynamic monitoring. Despite limitations in diagnostic accuracy, the modified Allen test (manual occlusion of radial and ulnar arteries followed by release of the latter and assessment of palmar blush) is used routinely to evaluate the collateral circulation to the hand and, therefore, to determine patient eligibility for radial artery access. We sought to evaluate whether a smartphone application may provide a superior alternative to the modified Allen test. METHODS: We compared the modified Allen test with a smartphone heart rate-monitoring application (photoplethysmography readings detected using a smartphone camera lens placed on the patient's index finger) in patients undergoing a planned cardiac catheterization. Test order was randomly assigned in a 1:1 fashion. All patients then underwent conventional plethysmography of the index finger, followed by Doppler ultrasonography of the radial and ulnar arteries (the diagnostic standard). The primary outcome was diagnostic accuracy of the heart rate-monitoring application. RESULTS: Among 438 patients who were included in the study, we found that the heart rate-monitoring application had a superior diagnostic accuracy compared with the modified Allen test (91.8% v. 81.7%, p = 0.002), attributable to its greater specificity (93.0% v. 82.8%, p = 0.001). We also found that this application had greater diagnostic accuracy for assessment of radial or ulnar artery patency in the ipsilateral and contralateral wrist (94.0% v. 84.0%, p < 0.001). INTERPRETATION: A smartphone application used at the bedside was diagnostically superior to traditional physical examination for confirming ulnar patency before radial artery access. This study highlights the potential for smartphone-based diagnostics to aid in clinical decision-making at the patient's bedside. Trial registration: Clinicaltrials.gov, no. NCT02519491.

Assessment of a noninvasive optical photoplethysmography imaging device with dynamic tissue phantom models.

Noncontact photoplethysmography (PPG) has been studied as a method to provide low-cost, noninvasive, two-dimensional blood oxygenation measurements and medical imaging for a variety of near-surface pathologies. To evaluate this technology in a laboratory setting, dynamic tissue phantoms were developed with tunable parameters that mimic physiologic properties of the skin, including blood vessel volume change, pulse wave frequency, and tissue scattering and absorption. Tissue phantoms were generated using an elastic tubing to represent a blood vessel where the luminal volume could be modulated with a pulsatile fluid flow. The blood was mimicked with a scattering and absorbing motility standard, and the tissue with a gelatin-lipid emulsion hydrogel. A noncontact PPG imaging system was then evaluated using the phantoms. Noncontact PPG imaging accurately identified pulse frequency, and PPG signals from these phantoms suggest that the phantoms can be used to evaluate noncontact PPG imaging systems. Such information may be valuable to the development of future PPG imaging systems.

Photoplethysmography for the Assessment of Haemorheology.

Haemorheology has been long identified as an early biomarker of a wide range of diseases, especially cardiovascular diseases. This study investigates for the first time the suitability of Photoplethysmography (PPG) as a non-invasive diagnostic method for haemorheological changes. The sensitivity of both PPG components (AC and DC) to changes in haemorheology were rigorously investigated in an in vitro experimental setup that mimics the human circulation. A custom-made reflectance PPG sensor, a pressure transducer and an ultrasonic Doppler flowmeter were used to map changes in flow dynamics and optical responses in an arterial model. The study investigated the effect of shear rates by varying fluid pumping frequencies using 4 set-points and the effect of clot formation using a chemical trigger. Both PPGAC amplitudes and PPGDC levels showed significant (p < 0.001) changes during the increase in shear rates and an immediate change after thromboplastin activation. The findings highlight that PPG has the potential to be used as a simple non-invasive method for the detection of blood characteristics, including disaggregation, radial migration and cross-linking fibrin formations. Such capability will enable the assessment of the effects of clotting-activators and anticoagulants (including non-pharmacological methods) and might aid in the early non-invasive assessment of cardiovascular pathologies.

Active and Passive Optical Imaging Modality for Unobtrusive Cardiorespiratory Monitoring and Facial Expression Assessment.

Because of their obvious advantages, active and passive optoelectronic sensor concepts are being investigated by biomedical research groups worldwide, particularly their camera-based variants. Such methods work noninvasively and contactless, and they provide spatially resolved parameter detection. We present 2 techniques: the active photoplethysmography imaging (PPGI) method for detecting dermal blood perfusion dynamics and the passive infrared thermography imaging (IRTI) method for detecting skin temperature distribution. PPGI is an enhancement of classical pulse oximetry. Approved algorithms from pulse oximetry for the detection of heart rate, heart rate variability, blood pressure-dependent pulse wave velocity, pulse waveform-related stress/pain indicators, respiration rate, respiratory variability, and vasomotional activity can easily be adapted to PPGI. Although the IRTI method primarily records temperature distribution of the observed object, information on respiration rate and respiratory variability can also be derived by analyzing temperature change over time, for example, in the nasal region, or through respiratory movement. Combined with current research areas and novel biomedical engineering applications (eg, telemedicine, tele-emergency, and telemedical diagnostics), PPGI and IRTI may offer new data for diagnostic purposes, including assessment of peripheral arterial and venous oxygen saturation (as well as their differences). Moreover, facial expressions and stress and/or pain-related variables can be derived, for example, during anesthesia, in the recovery room/intensive care unit and during daily activities. The main advantages of both monitoring methods are unobtrusive data acquisition and the possibility to assess vital variables for different body regions. These methods supplement each other to enable long-term monitoring of physiological effects and of effects with special local characteristics. They also offer diagnostic advantages for intensive care patients and for high-risk patients in a homecare/outdoor setting. Selected applications have been validated at our laboratory using optical PPGI and IRTI techniques in a stand-alone or hybrid configuration. Additional research and validation is required before these preliminary results can be introduced for clinical applications.

Peripheral vasomotor activity assessment using a continuous wavelet analysis on webcam photoplethysmographic signals.

BACKGROUND: Vasoconstriction and vasodilation phenomena reflect the relative changes in the vascular bed. They induce particular modifications in the pulse wave magnitude. Webcams correspond to remote sensors that can be employed to measure the pulse wave in order to compute the pulse frequency. OBJECTIVE: Record and analyze pulse wave signal with a low-cost webcam to extract the amplitude information and assess the vasomotor activity of the participant. METHODS: Photoplethysmographic signals obtained from a webcam are analyzed through a continuous wavelet transform. The performance of the proposed filtering technique was evaluated using approved contact probes on a set of 12 healthy subjects after they perform a short but intense physical exercise. During the rest period, a cutaneous vasodilation is observable. RESULTS: High degrees of correlation between the webcam and a reference sensor were obtained. CONCLUSIONS: Webcams are low-cost and non-contact devices that can be used to reliably estimate both heart rate and peripheral vasomotor activity, notably during physical exertion.

Imaging photoplethysmography for clinical assessment of cutaneous microcirculation at two different depths.

The feasibility of bispectral imaging photoplethysmography (iPPG) system for clinical assessment of cutaneous microcirculation at two different depths is proposed. The iPPG system has been developed and evaluated for in vivo conditions during various tests: (1) topical application of vasodilatory liniment on the skin, (2) skin local heating, (3) arterial occlusion, and (4) regional anesthesia. The device has been validated by the measurements of a laser Doppler imager (LDI) as a reference. The hardware comprises four bispectral light sources (530 and 810 nm) for uniform illumination of skin, video camera, and the control unit for triggering of the system. The PPG signals were calculated and the changes of perfusion index (PI) were obtained during the tests. The results showed convincing correlations for PI obtained by iPPG530 nm and LDI at (1) topical liniment (r = 0.98) and (2) heating (r = 0.98) tests. The topical liniment and local heating tests revealed good selectivity of the system for superficial microcirculation monitoring. It is confirmed that the iPPG system could be used for assessment of cutaneous perfusion at two different depths, morphologically and functionally different vascular networks, and thus utilized in clinics as a cost-effective alternative to the LDI.