Reflective Photoplethysmography Research Articles

Quarter-Annulus Si-Photodetector with Equal Inner and Outer Radii of Curvature for Reflective Photoplethysmography Sensors.

Reflection-type photoplethysmography (PPG) pulse sensors used in wearable smart watches, true wireless stereo, etc., have been recently considered a key component for monitoring biological signals such as heart rate, SPO3, and blood pressure. Typically, the optical front end (OFE) of these PPG sensors is heterogeneously configured and packaged with light sources and receiver chips. In this paper, a novel quarter-annulus photodetector (NQAPD) with identical inner and outer radii of curvature has been developed using a plasma dicing process to realize a ring-type OFE receiver, which maximizes manufacturing efficiency and increases the detector collection area by 36.7% compared to the rectangular PD. The fabricated NQAPD exhibits a high quantum efficiency of over 90% in the wavelength of 500 nm to 740 nm and the highest quantum efficiency of 95% with a responsivity of 0.41 A/W at the wavelength of 530 nm. Also, the NQAPD is shown to increase the SNR of the PPG signal by 5 to 7.6 dB compared to the eight rectangular PDs. Thus, reflective PPG sensors constructed with NQAPD can be applied to various wearable devices requiring low power consumption, high performance, and cost-effectiveness.

Assessing the accuracy of photoplethysmography for wearable heart rate monitoring based on body location and body motion in uncontrolled outdoor environments

Introduction
 Reflective photoplethysmography (PPG) is the dominant method for heart rate (HR) monitoring consumer wearables. However, motion artifacts and sensor placement impact the accuracy of these HR measurements. Here, we present a study on how these two factors affect the accuracy of PPG-based HR measurements and compare them to ground-truth measurements from electrocardiography (ECG). Our study investigated these measurements in outdoor environments outside controlled laboratory settings.
 Methods
 Our study collected a dataset of 16 participants, each for 13 hours wearing four reflective PPG sensing devices placed at the forehead, sternum, ankle (supramalleolar), and wrist. Participants traveled by train from downtown Zurich to the Jungfraujoch railway station at 3,460 m above sea level in the mountains. PPG measurements were obtained using a MAX86141 optical analog front-end coupled with a green LED and photodiode from an SFH7072 module. Motion was quantified using two accelerometers (LIS2DH, ADXL355). A Lead I ECG was obtained by the device at the sternum using a MAX30003 biopotential sensor connected to gel electrodes on the chest. All devices were synchronized by aligning recorded signals post-hoc (33ms accuracy, Meier & Holz, 2023). The HR was extracted from the ECG by time-domain peak detection. The HR extraction from PPG was both performed by time-domain peak detection and frequency-domain analysis. The HR was computed every 5 seconds (30 seconds window size) resulting in 152,000 HR measurements across the whole dataset.
 Results
 The forehead and chest locations exhibited the highest HR measurement accuracy (median error 7.1% and 7.7%, respectively), while lower accuracies were observed for ankle and wrist placements (9.9% and 18.4% error). At rest, all median errors were below 5% while movements influenced readings at all locations negatively. Adjusted for motion, the HR obtained from the forehead sensor was most accurate. In terms of processing method, time-domain analysis produced better accuracy during periods of low motion while frequency-domain analysis was more reliable during movements.
 Discussion/Conclusion
 The accuracy of PPG-based HR measurements in uncontrolled outdoor settings is affected both by body location and motion artifacts with a clear ranking of site suitability: forehead >> chest >> ankle >> wrist. This is consistent with prior studies in controlled environments, though our study found a higher impact of motion than body location on HR accuracy (Longmore et al., 2019). This may be because participants’ motions in uncontrolled environments are more irregular and diverse, resulting in deteriorated signal quality. Our study shows the importance of further investigations in everyday conditions on the path toward more reliable PPG-based HR monitoring in wearable devices.
 References
 Longmore, S. K., Lui, G. Y., Naik, G., Breen, P. P., Jalaludin, B., & Gargiulo, G. D. (2019). A comparison of reflective photoplethysmography for detection of heart rate, blood oxygen saturation, and respiration rate at various anatomical locations. Sensors, 19(8), Article 1874. https://doi.org/10.3390/s19081874
 Meier, M., & Holz, C. (2023). BMAR: Barometric and Motion-based Alignment and Refinement for offline signal synchronization across devices. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 7(2), Article 69. https://doi.org/10.1145/3596268

Intelligent medical IoT health monitoring system based on VR and wearable devices

Abstract In order to improve the shortcomings of the traditional monitoring equipment that is difficult to measure the daily physical parameters of the elderly and improve the accuracy of parameter measurement, this article designs wearable devices through the Internet of Things technology and virtual reality technology. With this device, four daily physical parameters of the elderly, such as exercise heart rate, blood pressure, plantar health, and sleep function, are measured. The feasibility of the measurement method and equipment is verified by experiments. The experimental results showed that the accuracy of the measurement method based on the reflective photoplethysmography signal was high, with the mean and difference values of the subjects’ heart rate basically lying around 0 BPM and in good agreement between the estimated heart rate and the reference value. In the blood pressure measurements, the correlation coefficient between the P r s {P}_{rs} estimate and the reference value was 0.81. The estimation accuracy of the device used in the article was high, with the highest correlation coefficient of 0.96 ± 0.02 for subjects’ heart rate at rest, and its estimation error rate was 0.02 ± 0.01. The P n t h {P}_{{n}th} value for subject B8 exceeded the threshold of 0.5 before subject B21, and subject B8 had more severe symptoms, which was consistent with the actual situation. The wearable device was able to identify the subject’s eye features and provide appropriate videos to help subjects with poor sleep quality to fall asleep. The article provides a method and device that facilitates healthcare professionals to make real-time enquiries and receive user health advice.

Experimental blood glucose estimation from photoplethysmography recordings on distal finger phalange

Blood glucose concentration shows the quality and health of an individual. High glucose levels in the blood flow indicate atypical behavior of the human system. Currently, there is an acceptable test method to estimate glucose level; it consists in taking out a blood sample by the finger with a pin prick. However, the blood sample test has some disadvantages because it can produce some non-desired issues, such as infections, especially a typical case in people living with diabetes. Therefore, this work is motivated by applying reflective Photoplethysmography (PPG), a non-invasive technique based on a light source and a photodetector near the human body's skin. In this case, we propose two different blood glucose sensors using the infrared diodes LTE-302 and COM-09349 with a photodetector FDS-100. It is worth noting that both designs have multiple development stages, and all of them are self-designed and validated through various test samples with three healthy volunteers, one woman and two men. The results present an error of about 14 % for the first sensor, while for the second sensor is about 7.9 %. Moreover, the sensor measurements are compared against a commercial glucometer, the One Touch Select Plus Flex, and the specifications of the NORM ISO 15197:2013 standard. Finally, the reflective PPG technique could be applied as a non-invasive method to estimate the blood glucose level in the human body.

Stretchable Textile Bands for Ambulatory Electrocardiogram and Oximetry

This work presents a vital sign monitoring interface combining electrocardiogram (ECG) and reflective photoplethysmography (PPG) acquisition on stretchable kinesiology tapes (KTs). The integrated textile bands are less prone to electrode misplacement and deliver high-quality diagnostic ECG signals with dry electrodes. The reflective PPG measured over the subclavian artery is used to track blood oxygen saturation, and in combination with ECG, enables the determination of pulse transit time and inference of blood pressure. This multimodal interface improves clinical workflows because it is easy to don, reduces motion artifacts, and facilitates more efficient and accurate diagnosis in emergency settings.

Accuracy enhancement in reflective pulse oximetry by considering wavelength-dependent pathlengths

Objective. Noninvasive measurement of oxygen saturation (SpO 2) using transmissive photoplethysmography (tPPG) is clinically accepted and widely employed. However, reflective photoplethysmography (rPPG)—currently present in smartwatches—has not become equally accepted, partially because the pathlengths of the red and infrared PPGs are patient-dependent. Thus, even the most popular ‘Ratio of Modulation’ (R) method requires patient-dependent calibration to reduce the errors in the measurement of SpO 2 using rPPGs. Approach. In this paper, a correction factor or ‘pathlength ratio’ β is introduced in an existing calibration-free algorithm that compensates the patient-dependent pathlength variations, and improved accuracy is obtained in the measurement of SpO 2 using rPPGs. The proposed pathlength ratio β is derived through the analytical model of a rPPG signal. Using the new expression and data obtained from a human hypoxia study wherein arterial oxygen saturation values acquired through Blood Gas Analysis were employed as a reference, β is determined. Main results. The results of the analysis show that a specific combination of the β and the measurements on the pulsating part of the natural logarithm of the red and infrared PPG signals yields a reduced root-mean-square error (RMSE). It is shown that the average RMSE in measuring SpO 2 values reduces to 1 %. Significance. The human hypoxia study data used for this work, obtained in a previous study, covers SpO 2 values in the range from 70 % to 100 %, and thus shows that the pathlength ratio β proposed here works well in the range of clinical interest. This work demonstrates that the calibration-free method applicable for transmission type PPGs can be extended to determine SpO 2 using reflective PPGs with the incorporation of the correction factor β. Our algorithm significantly reduces the number of parameters needed for the estimation, while keeping the RMSE below the clinically accepted 2 %.

Comparison of Ring Pulse Oximetry Using Reflective Photoplethysmography and PSG in the Detection of OSA in Chinese Adults: A Pilot Study.

ObjectiveA novel ring-worn oximeter (Circul) uses reflective photoplethysmography and automated signal processing to calculate oxygen desaturations. We evaluated the ability of Circul to detect obstructive sleep apnea in Chinese adults.MethodsWe recruited 207 Chinese Han subjects: 70% males, mean age 48.2±14.7 years, mean BMI 27.6±4.8 kg/m2 and mean AHI 28.6±25.2 events/h. All participants underwent simultaneous polysomnography (PSG) and Circul testing in a sleep laboratory. Oxygen desaturation index (ODI), mean oxygen saturation (MSpO2), cumulative time at SpO2<90% (CT90), cumulative percentage of sleep time spent with SpO2<90% (CT90/TST) were derived and compared for the Circul and the PSG.ResultsThe ODI was 25.3±24.5 events/h using PSG and 22.2±24.5 events/h using Circul (P<0.0001), with an intraclass correlation coefficient (ICC) of 0.884. CT90 and CT90/TST between the two methods were not different; the MSpO2 level calculated by PSG was slightly lower than Circul, 95.0% (93.0–96.0%) vs 95.3% (93.9–96.6%), P<0.0001. Circul-ODI had a good correlation (r=0.91, p<0.0001) and close agreement with PSG-AHI (Bland-Altman analysis: Mean Difference 6.4, 95% CI −14.8 to 27.5 events/h). Using a threshold of AHI ≥5 events/h, the Circul had 87% sensitivity, 83% specificity, 5.09 positive likelihood ratio (LR+), 86% accuracy, and 0.929 area under the curve (AUC).ConclusionCircul ring pulse oximetry can detect OSA with reasonable reliability. The Circul system is a reliable and comfortable choice for OSA assessment.

In-Vitro Investigation of Flow Profiles in Arteries Using the Photoplethysmograph.

The flow profile in the artery reflects the health status of the vessel and generally the arterial system. The aim of this pilot study was to investigate in-vitro the effect of flow profiles on reflective photoplethysmography (PPG) signals at different steady state flow rates and levels of vessel constrictions. A simplified model of an arterial system was built, consisting of a steady state flow gear pump, PVC vinyl tubing, reservoir and a clamp with a micrometer gauge. The blood mimicking fluid (2.5% India ink and water solution) was pumped through the model. It was found that the waveforms of the PPG signals fluctuate irregularly and the magnitude of the frequency components was increased below 60 Hz in cases of turbulent flow (Re = 2503). These preliminary results suggest that PPG could be the basis for new technologies for assessing the profile of the blood flow in the artery. Future studies have to be carried out with pulsatile flow and more complex models that are more similar to the human arterial system.Clinical Relevance- The PPG signal reflects changes in the flow profile caused by the stenotic rigid vessel.

It is All in the Wrist: Wearable Sleep Staging in a Clinical Population versus Reference Polysomnography.

PurposeThere is great interest in unobtrusive long-term sleep measurements using wearable devices based on reflective photoplethysmography (PPG). Unfortunately, consumer devices are not validated in patient populations and therefore not suitable for clinical use. Several sleep staging algorithms have been developed and validated based on ECG-signals. However, translation from these techniques to data derived by wearable PPG is not trivial, and requires the differences between sensing modalities to be integrated in the algorithm, or having the model trained directly with data obtained with the target sensor. Either way, validation of PPG-based sleep staging algorithms requires a large dataset containing both gold standard measurements and PPG-sensor in the applicable clinical population. Here, we take these important steps towards unobtrusive, long-term sleep monitoring.MethodsWe developed and trained an algorithm based on wrist-worn PPG and accelerometry. The method was validated against reference polysomnography in an independent clinical population comprising 244 adults and 48 children (age: 3 to 82 years) with a wide variety of sleep disorders.ResultsThe classifier achieved substantial agreement on four-class sleep staging with an average Cohen’s kappa of 0.62 and accuracy of 76.4%. For children/adolescents, it achieved even higher agreement with an average kappa of 0.66 and accuracy of 77.9%. Performance was significantly higher in non-REM parasomnias (kappa = 0.69, accuracy = 80.1%) and significantly lower in REM parasomnias (kappa = 0.55, accuracy = 72.3%). A weak correlation was found between age and kappa (ρ = −0.30, p<0.001) and age and accuracy (ρ = −0.22, p<0.001).ConclusionThis study shows the feasibility of automatic wearable sleep staging in patients with a broad variety of sleep disorders and a wide age range. Results demonstrate the potential for ambulatory long-term monitoring of clinical populations, which may improve diagnosis, estimation of severity and follow up in both sleep medicine and research.

Accuracy of heart rate variability estimated with reflective wrist-PPG in elderly vascular patients

Optical heart rate monitoring (OHR) with reflective wrist photoplethysmography is a technique mainly used in the wellness application domain for monitoring heart rate levels during exercise. In the absence of motion, OHR technique is also able to estimate individual beat-to-beat intervals relatively well and can therefore also be used, for example, in monitoring of cardiac arrhythmias, stress, or sleep quality through heart rate variability (HRV) analysis. HRV analysis has also potential in monitoring the recovery of patients, e.g. after a medical intervention. However, in order to detect subtle changes, the calculated HRV parameters should be sufficiently accurate and very few studies exist that asses the accuracy of OHR derived HRV in non-healthy subjects. In this paper, we present a method to estimate beat-to-beat-intervals (BBIs) from reflective wrist PPG signal and evaluated the accuracy of the proposed method in estimating BBIs in a cross-sectional study with 29 hospitalized patients (mean age 70.6 years) in 24-h recordings performed after peripheral vascular surgery or endovascular interventions. Finally, we evaluate the accuracy of more than 30 commonly used HRV parameters and find that the accuracy of certain metrics, for example SDNN and triangular index, shown in the literature to be associated with the deterioration of the status of the patients during recovery from surgical intervention, could be adequate for patient monitoring. On the other hand, the parameters more affected by the high-frequency content of the HRV and especially the LF/HF-ratio should be used with caution.

Wearable monitoring of sleep-disordered breathing: estimation of the apnea\u2013hypopnea index using wrist-worn reflective photoplethysmography

A large part of the worldwide population suffers from obstructive sleep apnea (OSA), a disorder impairing the restorative function of sleep and constituting a risk factor for several cardiovascular pathologies. The standard diagnostic metric to define OSA is the apnea–hypopnea index (AHI), typically obtained by manually annotating polysomnographic recordings. However, this clinical procedure cannot be employed for screening and for long-term monitoring of OSA due to its obtrusiveness and cost. Here, we propose an automatic unobtrusive AHI estimation method fully based on wrist-worn reflective photoplethysmography (rPPG), employing a deep learning model exploiting cardiorespiratory and sleep information extracted from the rPPG signal trained with 250 recordings. We tested our method with an independent set of 188 heterogeneously disordered clinical recordings and we found it estimates the AHI with a good agreement to the gold standard polysomnography reference (correlation = 0.61, estimation error = 3±10 events/h). The estimated AHI was shown to reliably assess OSA severity (weighted Cohen’s kappa = 0.51) and screen for OSA (ROC–AUC = 0.84/0.86/0.85 for mild/moderate/severe OSA). These findings suggest that wrist-worn rPPG measurements that can be implemented in wearables such as smartwatches, have the potential to complement standard OSA diagnostic techniques by allowing unobtrusive sleep and respiratory monitoring.

Blood Pressure Estimation Algorithm Based on Photoplethysmography Pulse Analyses

Though small wrist-type blood pressure (BP) measurement devices using simple sensors have recently been developed, they lack accuracy and require the input of personal user data. To miniaturize BP measurement devices, this study proposes the use of algorithms that can calculate BP using sensors that utilize only two photoplethysmographies (PPGs), without the need for electrocardiograms. To reduce the error of indirect BP measurement, specific values representing individual blood vessel conditions are improved via the application of an algorithm developed using mean arterial pressure and PPG phase difference. To reduce the error that occurs when measuring BP using PPG, a specific value algorithm used to develop a miniaturized BP measuring device using two PPGs is proposed along with a new model. The developed ultra-small PPG measuring device uses a reflective photoplethysmography measurement circuit. This is presented as a PPG-only model that deviates from the method of additionally linking existing electrocardiography (ECG). The measurement device developed in this study is compared with the air-pressurized automatic BP measurement device in terms of the BP measurement value; the result of maintaining the error stably at 5% is derived to prove the superiority of the algorithm.

Respiratory activity extracted from wrist-worn reflective photoplethysmography in a sleep-disordered population

Objective: Respiratory activity is an essential parameter to monitor healthy and disordered sleep, and unobtrusive measurement methods have important clinical applications in diagnostics of sleep-related breathing disorders. We propose a respiratory activity surrogate extracted from wrist-worn reflective photoplethysmography validated on a heterogeneous dataset of 389 sleep recordings. Approach: The surrogate was extracted by interpolating the amplitude of the PPG pulses after evaluation of pulse morphological quality. Subsequent multistep post-processing was applied to remove parts of the surrogate with low quality and high motion levels. In addition to standard respiration rate performance, we evaluated the similarity between surrogate respiratory activity and reference inductance plethysmography of the thorax, using Spearman’s correlations and spectral coherence, and assessed the influence of PPG signal quality, motion levels, sleep stages and obstructive sleep apnea. Main results: Prior to post-processing, the surrogate already had a strong similarity with the reference (correlation = 0.54, coherence = 0.81), and reached respiration rate estimation performance in line with the literature (estimation error = 0.76± 2.11 breaths/min). Detrimental effects of low PPG quality, high motion levels and sleep-dependent physiological phenomena were significantly mitigated by the proposed post-processing steps (correlation = 0.62, coherence = 0.88, estimation error = 0.53± 1.85 breaths/min). Significance: Wrist-worn PPG can be used to extract respiratory activity, thus allowing respiration monitoring in real-world sleep medicine applications using (consumer) wearable devices.

271: Continuous maternal hemodynamics monitoring at delivery using a novel, noninvasive, wireless, PPG-based sensor

Existing means of hemodynamic monitoring are invasive, expensive, complex to use and associated with complications. In this study, we utilized an innovative, noninvasive, reflective photoplethysmography based device (Biobeat Technologies Ltd.) that enables maternal hemodynamics continuous monitoring to assess cardiovascular changes during labor and delivery. The Biobeat Monitoring Platform includes a wearable watch, placed on parturient wrist, that automatically samples cardiac output (CO), cardiac index (CI), blood pressure (BP), stroke volume (SV), systemic vascular resistance (SVR), heart rate (HR) and more every 5 seconds and uploads all data to a smartphone-based app and to the cloud, where it can be monitored and analyzed remotely. Eight unselected term parturients (age 29.2±8, years; 4 nullipara; BMI 28.4±5.9 Kg/m2) were recruited after initial calibration to maternal weight and height. Overall, over 150,000 measurements were retrieved. Data was normalized to visual presentation using Excel Data Analysis and regression tool. Average measurements were compared 30 minutes before rupture of membranes (first stage of labor), 30 minutes before delivery (second stage of labor) and 30 minutes after delivery. Cardiac output increases with labor reaching a peak of 8 L/min with delivery, after which, it rapidly declines (5.4 vs. 6.1 vs. 5.8, L/min, p< 0.001). This is mainly due to marked changes in HR up to 110 bpm (78 vs. 90 vs. 86, bpm, p< 0.0001) and a slight change in SV (69.3 vs. 67.6 vs. 68.5, ml/beat, p=0.006)(Figure 1). Mean BP remains relatively stable throughout delivery with a slight increase at delivery, reflecting the increase in CO and decrease in SVR with delivery (Figure 2). This study serves as a proof of concept for application of noninvasive maternal hemodynamic monitoring throughout labor and delivery for research and clinical use. Further studies will implement technology to assess maternal hemodynamics and cardiovascular adaptation during labor and delivery in women with cardiovascular risk factors and pregnancy complications. View Large Image Figure ViewerDownload Hi-res image Download (PPT)

A Comparison of Reflective Photoplethysmography for Detection of Heart Rate, Blood Oxygen Saturation, and Respiration Rate at Various Anatomical Locations.

Monitoring of vital signs is critical for patient triage and management. Principal assessments of patient conditions include respiratory rate heart/pulse rate and blood oxygen saturation. However, these assessments are usually carried out with multiple sensors placed in different body locations. The aim of this paper is to identify a single location on the human anatomy whereby a single 1 cm × 1 cm non-invasive sensor could simultaneously measure heart rate (HR), blood oxygen saturation (SpO2), and respiration rate (RR), at rest and while walking. To evaluate the best anatomical location, we analytically compared eight anatomical locations for photoplethysmography (PPG) sensors simultaneously acquired by a single microprocessor at rest and while walking, with a comparison to a commercial pulse oximeter and respiration rate ground truth. Our results show that the forehead produced the most accurate results for HR and SpO2 both at rest and walking, however, it had poor RR results. The finger recorded similar results for HR and SpO2, however, it had more accurate RR results. Overall, we found the finger to be the best location for measurement of all three parameters at rest; however, no site was identified as capable of measuring all parameters while walking.

Evaluation of the effect of posture on carotid-to-toe pulse transit time values estimated using system identification

Pulse transit time (PTT) is defined as the time a pulse wave needs to travel from one point of the blood circulation to another point. Monitoring PTT values of a person is useful in non-invasive, cuff-less estimation of blood pressure measurement. In this paper, PTT values estimated from two PPG signals from the reflective photoplethysmography of carotid and toe that are collected from 12 healthy subjects (eight males and four females) age 23.8 ± 1.5 years. PTT has been estimated using an auto-regressive (ARX) model. PTT values were estimated for all subjects in three different positions; sit, stand and supine. Results show that the PTT in sit and stand positions are statistically no different (84.5 ± 19.6 ms versus 78 ± 15.9 ms, p = 0.44). However, the PTT in the supine position is significantly higher than the two other positions (145.7 ± 18.4 ms versus 84.5 ± 19.6 ms and 145.7 ± 18.4 ms versus 78 ± 15.9 ms respectively, p < 0.01 for both situations).

Meditation smartphone application effects on prehypertensive adults' blood pressure: Dose-response feasibility trial.

Essential hypertension (EH) is the most common chronic disease in the United States and a major cause of morbidity and mortality. Lifestyle interventions (e.g., diet, exercise, stress management) to reduce blood pressure (BP) are often complex with varying effectiveness. Breathing awareness meditation (BAM) is a stress management strategy with encouraging effects on BP, though widespread dissemination is hampered by the lack of an easy-to-use methodology to train and monitor BAM practices. A smartphone application (Tension Tamer [TT]) that implements BAM and tracks adherence has shown promise in addressing these gaps. This 6-month dose-response feasibility trial evaluated effects of the app on BP to further optimize BAM user guidelines. Sixty-four adults with prehypertension were randomized to complete TT-guided BAM sessions for 5-, 10-, or 15-min intervals twice daily over 6 months. Continuous heart rate readings derived from the phone's video camera via reflective photoplethysmography were used as feedback and as an index of time-stamped adherence. Outcomes (resting BP, HR) were collected at baseline, 1-, 3-, and 6-months. Mixed modeling results showed a significant time effect for systolic BP (SBP) with a dose-response effect at Months 3 and 6. Adherence declined over time and was lowest in the 15-min dose condition, though SBP reductions were maintained. Generally, adherence was negatively associated with dose as the study progressed. Smartphone-implemented BAM appears to reduce SBP and can be a low-cost method to reach large populations. (PsycINFO Database Record

Fusing non-contact vital sign sensing modalities - first results.

A wearable multi-sensor system allowing synchronized unobtrusive measurements of 4 vital signs at a dedicated location of interest is presented. The 4×U sensor is capable of synchronously measuring magnetic impedance, reflective photoplethysmography, capacitive electrocardiogram and seismocardiography (ballistocardiography). The hardware of all modalities is described and some preliminary results are reported.

Motion Artifact Quantification and Sensor Fusion for Unobtrusive Health Monitoring.

Sensors integrated into objects of everyday life potentially allow unobtrusive health monitoring at home. However, since the coupling of sensors and subject is not as well-defined as compared to a clinical setting, the signal quality is much more variable and can be disturbed significantly by motion artifacts. One way of tackling this challenge is the combined evaluation of multiple channels via sensor fusion. For robust and accurate sensor fusion, analyzing the influence of motion on different modalities is crucial. In this work, a multimodal sensor setup integrated into an armchair is presented that combines capacitively coupled electrocardiography, reflective photoplethysmography, two high-frequency impedance sensors and two types of ballistocardiography sensors. To quantify motion artifacts, a motion protocol performed by healthy volunteers is recorded with a motion capture system, and reference sensors perform cardiorespiratory monitoring. The shape-based signal-to-noise ratio SNR is introduced and used to quantify the effect on motion on different sensing modalities. Based on this analysis, an optimal combination of sensors and fusion methodology is developed and evaluated. Using the proposed approach, beat-to-beat heart-rate is estimated with a coverage of 99.5% and a mean absolute error of 7.9 ms on 425 min of data from seven volunteers in a proof-of-concept measurement scenario.

A Motion Heart-Rate Monitor Watch with Improved Grey Differential Equation Model Based on Reflective Photoplethysmography

With the advantage of noninvasive measurement, reflective photoplethysmography (PPG) has been adopted by a group of gadgets to estimate heart rate (HR) from the wrists. Challenges include PPG artifacts reduction and comfortable type design. Aimed at improving the accuracy of measurement during wrist movements such as handshake or exercises, in this paper, a motion HR monitor watch has presented. The work mainly focused on two categories: the HR extraction algorithm derived from grey differential equation model (abbreviated as GM(1, 1) model) combined with acceleration model and the enhanced hardware structure designed with 523 nm green leds. The tests have been carried out and results analysis show high correlation among the values measured respectively from this watch, HR chest belt (taken as HR gold standard) and commercial motion HR watch in various intensities of exercises.