Classifying Chinese Medicine Constitution Using Multimodal Deep-Learning Model

OBJECTIVE

To develop a multimodal deep-learning model for classifying Chinese medicine constitution, i.e., the balanced and unbalanced constitutions, based on inspection of tongue and face images, pulse waves from palpation, and health information from a total of 540 subjects.

METHODS

This study data consisted of tongue and face images, pulse waves obtained by palpation, and health information, including personal information, life habits, medical history, and current symptoms, from 540 subjects (202 males and 338 females). Convolutional neural networks, recurrent neural networks, and fully connected neural networks were used to extract deep features from the data. Feature fusion and decision fusion models were constructed for the multimodal data.

RESULTS

The optimal models for tongue and face images, pulse waves and health information were ResNet18, Gate Recurrent Unit, and entity embedding, respectively. Feature fusion was superior to decision fusion. The multimodal analysis revealed that multimodal data compensated for the loss of information from a single mode, resulting in improved classification performance.

CONCLUSIONS

Multimodal data fusion can supplement single model information and improve classification performance. Our research underscores the effectiveness of multimodal deep learning technology to identify body constitution for modernizing and improving the intelligent application of Chinese medicine.

Recent Progress of Wearable Triboelectric Nanogenerator-Based Sensor for Pulse Wave Monitoring

Today, cardiovascular diseases threaten human health worldwide. In clinical practice, it has been concluded that analyzing the pulse waveform can provide clinically valuable information for the diagnosis of cardiovascular diseases. Accordingly, continuous and accurate monitoring of the pulse wave is essential for the prevention and detection of cardiovascular diseases. Wearable triboelectric nanogenerators (TENGs) are emerging as a pulse wave monitoring biotechnology due to their compelling characteristics, including being self-powered, light-weight, and wear-resistant, as well as featuring user-friendliness and superior sensitivity. Herein, a comprehensive review is conducted on the progress of wearable TENGs for pulse wave monitoring. Firstly, the four modes of operation of TENG are briefly described. Secondly, TENGs for pulse wave monitoring are classified into two categories, namely wearable flexible film-based TENG sensors and textile-based TENG sensors. Next, the materials, fabrication methods, working mechanisms, and experimental performance of various TENG-based sensors are summarized. It concludes by comparing the characteristics of the two types of TENGs and discussing the potential development and challenges of TENG-based sensors in the diagnosis of cardiovascular diseases and personalized healthcare.

Physical Noninvasive Attacks on Photoplethysmogram by Computer Controlled Blood Pressure Cuff

Sensor data has been used in social security and welfare infrastructures such as insurance and medical care to provide personalized products and services; there is a risk that attackers can alter sensor data to obtain unfair benefits. We consider that one of the attack methods to modify sensor data is to attack the wearer's body to modify biometric information. In this study, we propose a noninvasive attack method to modify the sensor value of a photoplethysmogram. The proposed method can disappear pulse wave peaks by pressurizing the upper arm with air pressure to control blood volume. Seven subjects experiencing a rest environment and five subjects experiencing an after-exercise environment wore five different models of smartwatches, and three pressure patterns were performed. It was confirmed in both situations that the displayed heart rate decreased from the true heart rate.

TRCCBP: Transformer Network for Radar-Based Contactless Continuous Blood Pressure Monitoring

Contactless continuous blood pressure (BP) monitoring is of great significance for daily healthcare. Radar-based continuous monitoring methods typically extract time-domain features manually such as pulse transit time (PTT) to calculate the BP. However, breathing and slight body movements usually distort the features extracted from pulse-wave signals, especially in long-term continuous monitoring, and manually extracted features may have limited performance for BP estimation. This article proposes a Transformer network for Radar-based Contactless Continuous Blood Pressure monitoring (TRCCBP). A heartbeat signal-guided single-beat pulse wave extraction method is designed to obtain pure pulse-wave signals. A transformer network-based blood pressure estimation network is proposed to estimate BP, which utilizes convolutional layers with different scales, a gated recurrent unit (GRU) to capture time-dependence in continuous radar signal and multi-head attention modules to capture deep temporal domain characteristics. A radar signal dataset captured in an indoor environment containing 31 persons and a real medical situation containing five persons is set up to evaluate the performance of TRCCBP. Compared with the state-of-the-art method, the average accuracy of diastolic blood pressure (DBP) and systolic blood pressure (SBP) is 4.49 mmHg and 4.73 mmHg, improved by 12.36 mmHg and 8.80 mmHg, respectively. The proposed TRCCBP source codes and radar signal dataset have been made open-source online for further research.

Noninvasive hemodynamic indices of vascular aging: an in silico assessment

Vascular aging (VA) involves structural and functional changes in blood vessels that contribute to cardiovascular disease. Several noninvasive pulse wave (PW) indices have been proposed to assess the arterial stiffness component of VA in the clinic and daily life. This study investigated 19 of these indices, identified in recent review articles on VA, by using a database comprising 3,837 virtual healthy subjects aged 25-75 yr, each with unique PW signals simulated under various levels of artificial noise to mimic real measurement errors. For each subject, VA indices were calculated from filtered PW signals and compared with the precise theoretical value of aortic Young's modulus (EAo). In silico PW indices showed age-related changes that align with in vivo population studies. The cardio-ankle vascular index (CAVI) and all pulse wave velocity (PWV) indices showed strong linear correlations with EAo (Pearson's rp > 0.95). Carotid distensibility showed a strong negative nonlinear correlation (Spearman's rs < -0.99). CAVI and distensibility exhibited greater resilience to noise compared with PWV indices. Blood pressure-related indices and photoplethysmography (PPG)-based indices showed weaker correlations with EAo (rp and rs < 0.89, |rp| and |rs| < 0.84, respectively). Overall, blood pressure-related indices were confounded by more cardiovascular properties (heart rate, stroke volume, duration of systole, large artery diameter, and/or peripheral vascular resistance) compared with other studied indices, and PPG-based indices were most affected by noise. In conclusion, carotid-femoral PWV, CAVI and carotid distensibility emerged as the superior clinical VA indicators, with a strong EAo correlation and noise resilience. PPG-based indices showed potential for daily VA monitoring under minimized noise disturbances.NEW & NOTEWORTHY For the first time, 19 noninvasive pulse wave indices for assessing vascular aging were examined together in a single database of nearly 4,000 subjects aged 25-75 yr. The dataset contained precise values of the aortic Young's modulus and other hemodynamic measures for each subject, which enabled us to test each index's ability to measure changes in aortic stiffness while accounting for confounding factors and measurement errors. The study provides freely available tools for analyzing these and additional indices.

Arterial Blood Pressure Features of Hypertensive Patients with Typical and Atypical 460 nm Skin Fluorescence Response to Transient Ischaemia

Flow-mediated skin fluorescence (FMSF) at 460 nm is a non-invasive method for assessing dynamic changes in the reduced form of nicotinamide adenine dinucleotide (NADH) and microcirculation in forearm skin under varying conditions of tissue perfusion. Typically, fluorescence increases during ischaemia, but atypical cases show a temporary signal decrease instead of a constant increase. This study aimed to explore the clinical implications of atypical FMSF patterns in patients with newly diagnosed untreated hypertension. NADH fluorescence and pulse wave analysis were performed on 65 patients. Differences in peripheral and arterial pulse pressure profiles were examined based on FMSF curve courses. Patients with atypical curve courses had significantly (p < 0.05 or lower for all) higher heart rate, peripheral and central diastolic pressure, tension time index, central rate pressure product, shorter diastole duration, and reservoir pressure-time integral. Hypertensive patients with atypical FMSF signals had less advantageous blood pressure profiles. Although the underlying factors causing these symptoms are unknown, the atypical FMSF pattern may reflect increased sympathetic stimulation and vascular resistance. The visual assessment of the FMSF curve may have important clinical implications that deserve further investigation.

Sensor-Location-Specific Joint Acquisition of Peripheral Artery Bioimpedance and Photoplethysmogram for Wearable Applications

BACKGROUND

Cardiovascular diseases (CVDs), being the culprit for one-third of deaths globally, constitute a challenge for biomedical instrumentation development, especially for early disease detection. Pulsating arterial blood flow, providing access to cardiac-related parameters, involves the whole body. Unobtrusive and continuous acquisition of electrical bioimpedance (EBI) and photoplethysmography (PPG) constitute important techniques for monitoring the peripheral arteries, requiring novel approaches and clever means.

METHODS

In this work, five peripheral arteries were selected for EBI and PPG signal acquisition. The acquisition sites were evaluated based on the signal morphological parameters. A small-data-based deep learning model, which increases the data by dividing them into cardiac periods, was proposed to evaluate the continuity of the signals.

RESULTS

The highest sensitivity of EBI was gained for the carotid artery (0.86%), three times higher than that for the next best, the posterior tibial artery (0.27%). The excitation signal parameters affect the measured EBI, confirming the suitability of classical 100 kHz frequency (average probability of 52.35%). The continuity evaluation of the EBI signals confirmed the advantage of the carotid artery (59.4%), while the posterior tibial artery (49.26%) surpasses the radial artery (48.17%). The PPG signal, conversely, commends the location of the posterior tibial artery (97.87%).

CONCLUSIONS

The peripheral arteries are highly suitable for non-invasive EBI and PPG signal acquisition. The posterior tibial artery constitutes a candidate for the joint acquisition of EBI and PPG signals in sensor-fusion-based wearable devices-an important finding of this research.

Wrinkle Clamp Down on Structure Crack Strain Sensor Based on High Poisson's Ratio Material for Home Health Monitoring and Human-Machine Interaction

Flexible wearable crack strain sensors are currently receiving significant attention because they can be used in a wide range of physiological signal monitoring and human-machine interaction applications. However, sensors with high sensitivity, great repeatability, and wide sensing range remain challenging. Herein, a tunable wrinkle clamp down structure (WCDS) crack strain sensor based on high Poisson's ratio material with high sensitivity, high stability, and wide strain range is proposed. Based on the high Poisson's ratio of the acrylic acid film, the WCDS was prepared by a prestretching process. The wrinkle structures can clamp down the crack to improve the cyclic stability of the crack strain sensor while maintaining its high sensitivity. Moreover, the tensile properties of the crack strain sensor are improved by introducing wrinkles in the bridge-like gold stripes connecting each separated gold flake. Owing to this structure, the sensitivity of the sensor can reach 3627, stable operation over 10 000 cycles is achieved, and the strain range can reach about 9%. In addition, the sensor exhibits low dynamic response and good frequency characteristics. Because of its demonstrated excellent performance, the strain sensor can be used in pulse wave and heart rate monitoring, as well as posture recognition and game control.

Wearable Multi-Channel Pulse Signal Acquisition System Based on Flexible MEMS Sensor Arrays with TSV Structure

Micro-electro-mechanical system (MEMS) pressure sensors play a significant role in pulse wave acquisition. However, existing MEMS pulse pressure sensors bound with a flexible substrate by gold wire are vulnerable to crush fractures, leading to sensor failure. Additionally, establishing an effective mapping between the array sensor signal and pulse width remains a challenge. To solve the above problems, we propose a 24-channel pulse signal acquisition system based on a novel MEMS pressure sensor with a through-silicon-via (TSV) structure, which connects directly to a flexible substrate without gold wire bonding. Firstly, based on the MEMS sensor, we designed a 24-channel pressure sensor flexible array to collect the pulse waves and static pressure. Secondly, we developed a customized pulse preprocessing chip to process the signals. Finally, we built an algorithm to reconstruct the three-dimensional pulse wave from the array signal and calculate the pulse width. The experiments verify the high sensitivity and effectiveness of the sensor array. In particular, the measurement results of pulse width are highly positively correlated with those obtained via infrared images. The small-size sensor and custom-designed acquisition chip meet the needs of wearability and portability, meaning that it has significant research value and commercial prospects.

Arterial pulse wave modelling and analysis for vascular age studies: a review from VascAgeNet

Arterial pulse waves (PWs) such as blood pressure and photoplethysmogram signals contain a wealth of information on the cardiovascular (CV) system that can be exploited to assess vascular age and identify individuals at elevated CV risk. We review the possibilities, limitations, complementarity, and differences of reduced-order, biophysical models of arterial PW propagation, as well as theoretical and empirical methods for analysing PW signals and extracting clinically relevant information for vascular age assessment. We provide detailed mathematical derivations of these models and theoretical methods, showing how they are related to each other. Lastly, we outline directions for future research to realise the potential of modelling and analysis of PW signals for accurate assessment of vascular age in both the clinic and in daily life.

PPG2EMG: Estimating Upper-Arm Muscle Activities and EMG from Wrist PPG Values

The electromyogram (EMG) is a waveform representation of the action potential generated by muscle cells using electrodes. EMG acquired using surface electrodes is called surface EMG (sEMG), and it is the acquisition of muscle action potentials transmitted by volume conduction from the skin. Surface electrodes require disposable conductive gel or adhesive tape to be attached to the skin, which is costly to run, and the tape is hard on the skin when it is removed. Muscle activity can be evaluated by acquiring muscle potentials and analyzing quantitative, temporal, and frequency factors. It is also possible to evaluate muscle fatigue because the frequency of the EMG becomes lower as the muscle becomes fatigued. Research on human activity recognition from EMG signals has been actively conducted and applied to systems that support arm and hand functions. This paper proposes a method for recognizing the muscle activity state of the arm using pulse wave data (PPG: Photoplethysmography) and a method for estimating EMG using pulse wave data. This paper assumes that the PPG sensor is worn on the user's wrist to measure the heart rate. The user also attaches an elastic band to the upper arm, and when the user exerts a force on the arm, the muscles of the upper arm contract. The arteries are then constricted, and the pulse wave measured at the wrist becomes weak. From the change in the pulse wave, the muscle activity of the arm can be recognized and the number of action potentials of the muscle can be estimated. From the evaluation experiment with five subjects, three types of muscle activity were recognized with 80+%, and EMG was estimated with approximately 20% error rate.

Non-invasive hemodynamic diagnosis based on non-linear pulse wave theory applied to four limbs

Introduction: Hemodynamic diagnosis indexes (HDIs) can comprehensively evaluate the health status of the cardiovascular system (CVS), particularly for people older than 50 years and prone to cardiovascular disease (CVDs). However, the accuracy of non-invasive detection remains unsatisfactory. We propose a non-invasive HDIs model based on the non-linear pulse wave theory (NonPWT) applied to four limbs. Methods: This algorithm establishes mathematical models, including pulse wave velocity and pressure information of the brachial and ankle arteries, pressure gradient, and blood flow. Blood flow is key to calculating HDIs. Herein, we derive blood flow equation for different times of the cardiac cycle considering the four different distributions of blood pressure and pulse wave of four limbs, then obtain the average blood flow in a cardiac cycle, and finally calculate the HDIs. Results: The results of the blood flow calculations reveal that the average blood flow in the upper extremity arteries is 10.78 ml/s (clinically: 2.5-12.67 ml/s), and the blood flow in the lower extremity arteries is higher than that in the upper extremity. To verify model accuracy, the consistency between the clinical and calculated values is verified with no statistically significant differences (p < 0.05). Model IV or higher-order fitting is the closest. To verify the model generalizability, considering the risk factors of cardiovascular diseases, the HDIs are recalculated using model IV, and thus, consistency is verified (p < 0.05 and Bland-Altman plot). Conclusion: We conclude our proposed algorithmic model based on NonPWT can facilitate the non-invasive hemodynamic diagnosis with simpler operational procedures and reduced medical costs.

Robust Pulse Rate Measurements from Facial Videos in Diverse Environments

Pulse wave and pulse rate are important indicators of cardiovascular health. Technologies that can check the pulse by contacting the skin with optical sensors built into smart devices have been developed. However, this may cause inconvenience, such as foreign body sensation. Accordingly, studies have been conducted on non-contact pulse rate measurements using facial videos focused on the indoors. Moreover, since the majority of studies are conducted indoors, the error in the pulse rate measurement in outdoor environments, such as an outdoor bench, car and drone, is high. In this paper, to deal with this issue, we focus on developing a robust pulse measurement method based on facial videos taken in diverse environments. The proposed method stably detects faces by removing high-frequency components of face coordinate signals derived from fine body tremors and illumination conditions. It optimizes for extracting skin color changes by reducing illumination-caused noise using the Cg color difference component. The robust pulse wave is extracted from the Cg signal using FFT-iFFT with zero-padding. It can eliminate signal-filtering distortion effectively. We demonstrate that the proposed method relieves pulse rate measurement problems, producing 3.36, 5.81, and 6.09 bpm RMSE for an outdoor bench, driving car, and flying drone, respectively.

Feasibility of Brachial Occlusion Technique for Beat-to-Beat Pulse Wave Analysis

Czech physiologist Penaz tried to overcome limitations of invasive pulse-contour methods (PCM) in clinical applications by a non-invasive method (finger mounted BP cuff) for continuous arterial waveform detection and beat-to-beat analysis. This discovery resulted in significant interest in human physiology and non-invasive examination of hemodynamic parameters, however has limitations because of the distal BP recording using a volume-clamp method. Thus, we propose a validation of beat-to-beat signal analysis acquired by novel a brachial occlusion-cuff (suprasystolic) principle and signal obtained from Finapres during a forced expiratory effort against an obstructed airway (Valsalva maneuver). Twelve healthy adult subjects [2 females, age = (27.2 ± 5.1) years] were in the upright siting position, breathe through the mouthpiece (simultaneously acquisition by brachial blood pressure monitor and Finapres) and at a defined time were asked to generate positive mouth pressure for 20 s (Valsalva). For the purpose of signal analysis, we proposed parameter a “Occlusion Cuff Index” (OCCI). The assumption about similarities between measured signals (suprasystolic brachial pulse waves amplitudes and Finapres’s MAP) were proved by averaged Pearson’s correlation coefficient (r- = 0.60, p < 0.001). The averaged Pearson’s correlation coefficient for the comparative analysis of OCCI between methods was r- = 0.88, p < 0.001. The average percent change of OCCI during maneuver: 8% increase, 19% decrease and percent change of max/min ratio is 35%. The investigation of brachial pulse waves measured by novel brachial blood pressure monitor shows positive correlation with Finapres and the parameter OCCI shows promise as an index, which could describe changes during beat-to-beat cardiac cycles.

Detecting beats in the photoplethysmogram: benchmarking open-source algorithms

The photoplethysmogram (PPG) signal is widely used in pulse oximeters and smartwatches. A fundamental step in analysing the PPG is the detection of heartbeats. Several PPG beat detection algorithms have been proposed, although it is not clear which performs best.

OBJECTIVE

This study aimed to: (i) develop a framework with which to design and test PPG beat detectors; (ii) assess the performance of PPG beat detectors in different use cases; and (iii) investigate how their performance is affected by patient demographics and physiology.

APPROACH

Fifteen beat detectors were assessed against electrocardiogram-derived heartbeats using data from eight datasets. Performance was assessed using the F1 score, which combines sensitivity and positive predictive value.

MAIN RESULTS

Eight beat detectors performed well in the absence of movement, with F1 scores of ≥90\% on hospital data and wearable data collected at rest. Their performance was poorer during exercise, with F1 scores of 55-91\%; poorer in neonates than adults with F1 scores of 84-96\% in neonates compared to 98-99\% in adults; and poorer in atrial fibrillation (AF), with F1 scores of 92-97\% in AF, compared to 99-100\% in normal sinus rhythm.

SIGNIFICANCE

Two PPG beat detectors denoted 'MSPTD' and 'qppg' performed best, with complementary performance characteristics. This evidence can be used to inform the choice of PPG beat detector algorithm. The algorithms, datasets, and assessment framework are freely available.

The Hemodynamic Parameters Values Prediction on the Non-Invasive Hydrocuff Technology Basis with a Neural Network Applying

The task to develop a mechanism for predicting the hemodynamic parameters values based on non-invasive hydrocuff technology of a pulse wave signal fixation is described in this study. The advantages and disadvantages of existing methods of recording the ripple curve are noted in the published materials. This study proposes a new hydrocuff method for hemodynamic parameters and blood pressure values measuring. A block diagram of the device being developed is presented. Algorithms for processing the pulse wave contour are presented. A neural network applying necessity for the multiparametric feature space formation is substantiated. The pulse wave contours obtained using hydrocuff technology of oscillation formation for various age groups are presented. According to preliminary estimates, by the moment of the dicrotic surge formation, it is possible to judge the ratio of the heart and blood vessels work, which makes it possible to form an expanded feature space of significant parameters based on neural network classifiers. This study presents the characteristics accounted for creating a database for training a neural network.

Flexible Pressure Sensor Array with Multi-Channel Wireless Readout Chip

Flexible sensor arrays are widely used for wearable physiological signal recording applications. A high density sensor array requires the signal readout to be compatible with multiple channels. This paper presents a highly-integrated remote health monitoring system integrating a flexible pressure sensor array with a multi-channel wireless readout chip. The custom-designed chip features 64 voltage readout channels, a power management unit, and a wireless transceiver. The whole chip fabricated in a 65 nm complementary metal-oxide-semiconductor (CMOS) process occupies 3.7 × 3.7 mm², and the core blocks consume 2.3 mW from a 1 V supply in the wireless recording mode. The proposed multi-channel system is validated by measuring the ballistocardiogram (BCG) and pulse wave, which paves the way for future portable remote human physiological signals monitoring devices.

Statistical Analysis of the Consistency of HRV Analysis Using BCG or Pulse Wave Signals

Ballistocardiography (BCG) is considered a good alternative to HRV analysis with its non-contact and unobtrusive acquisition characteristics. However, consensus about its validity has not yet been established. In this study, 50 healthy subjects (26.2 ± 5.5 years old, 22 females, 28 males) were invited. Comprehensive statistical analysis, including Coefficients of Variation (CV), Lin’s Concordance Correlation Coefficient (LCCC), and Bland-Altman analysis (BA ratio), were utilized to analyze the consistency of BCG and ECG signals in HRV analysis. If the methods gave different answers, the worst case was taken as the result. Measures of consistency such as Mean, SDNN, LF gave good agreement (the absolute value of CV difference < 2%, LCCC > 0.99, BA ratio < 0.1) between J-J (BCG) and R-R intervals (ECG). pNN50 showed moderate agreement (the absolute value of CV difference < 5%, LCCC > 0.95, BA ratio < 0.2), while RMSSD, HF, LF/HF indicated poor agreement (the absolute value of CV difference ≥ 5% or LCCC ≤ 0.95 or BA ratio ≥ 0.2). Additionally, the R-R intervals were compared with P-P intervals extracted from the pulse wave (PW). Except for pNN50, which exhibited poor agreement in this comparison, the performances of the HRV indices estimated from the PW and the BCG signals were similar.

Wearable Photoplethysmography for Cardiovascular Monitoring

Smart wearables provide an opportunity to monitor health in daily life and are emerging as potential tools for detecting cardiovascular disease (CVD). Wearables such as fitness bands and smartwatches routinely monitor the photoplethysmogram signal, an optical measure of the arterial pulse wave that is strongly influenced by the heart and blood vessels. In this survey, we summarize the fundamentals of wearable photoplethysmography and its analysis, identify its potential clinical applications, and outline pressing directions for future research in order to realize its full potential for tackling CVD.

Calibration-Free Cuffless Blood Pressure Estimation Based on a Population With a Diverse Range of Age and Blood Pressure

This study presents a new blood pressure (BP) estimation algorithm utilizing machine learning (ML). A cuffless device that can measure BP without calibration would be precious for portability, continuous measurement, and comfortability, but unfortunately, it does not currently exist. Conventional BP measurement with a cuff is standard, but this method has various problems like inaccurate BP measurement, poor portability, and painful cuff pressure. To overcome these disadvantages, many researchers have developed cuffless BP estimation devices. However, these devices are not clinically applicable because they require advanced preparation before use, such as calibration, do not follow international standards (81060-1:2007), or have been designed using insufficient data sets. The present study was conducted to combat these issues. We recruited 127 participants and obtained 878 raw datasets. According to international standards, our diverse data set included participants from different age groups with a wide variety of blood pressures. We utilized ML to formulate a BP estimation method that did not require calibration. The present study also conformed to the method required by international standards while calculating the level of error in BP estimation. Two essential methods were applied in this study: (a) grouping the participants into five subsets based on the relationship between the pulse transit time and systolic BP by a support vector machine ensemble with bagging (b) applying the information from the wavelet transformation of the pulse wave and the electrocardiogram to the linear regression BP estimation model for each group. For systolic BP, the standard deviation of error for the proposed BP estimation results with cross-validation was 7.74 mmHg, which was an improvement from 17.05 mmHg, as estimated by the conventional pulse-transit-time-based methods. For diastolic BP, the standard deviation of error was 6.42 mmHg for the proposed BP estimation, which was an improvement from 14.05mmHg. The purpose of the present study was to demonstrate and evaluate the performance of the newly developed BP estimation ML method that meets the international standard for non-invasive sphygmomanometers in a population with a diverse range of age and BP.

Assessing hemodynamics from the photoplethysmogram to gain insights into vascular age: A review from VascAgeNet

The photoplethysmogram (PPG) signal is widely measured by clinical and consumer devices, and it is emerging as a potential tool for assessing vascular age. The shape and timing of the PPG pulse wave are both influenced by normal vascular aging, changes in arterial stiffness and blood pressure, and atherosclerosis. This review summarizes research into assessing vascular age from the PPG. Three categories of approaches are described: 1) those which use a single PPG signal (based on pulse wave analysis), 2) those which use multiple PPG signals (such as pulse transit time measurement), and 3) those which use PPG and other signals (such as pulse arrival time measurement). Evidence is then presented on the performance, repeatability and reproducibility, and clinical utility of PPG-derived parameters of vascular age. Finally, the review outlines key directions for future research to realize the full potential of photoplethysmography for assessing vascular age.

Filtering-induced time shifts in photoplethysmography pulse features measured at different body sites: the importance of filter definition and standardization

Objective.The waveform of a photoplethysmography (PPG) signal depends on the measurement site and individual physiological conditions. Filtering can distort the morphology of the original PPG signal waveform and change the timing of pulse feature points on PPG signals. We aim to quantitatively investigate the effect of PPG signal morphology (related to measurement site) and type of pulse feature on the filtering-induced time shift (TS).Approach.60 s PPG signals were measured from six body sites (finger, wrist under (volar), wrist upper (dorsal), earlobe, and forehead) of 36 healthy adults. Using infinite impulse response digital filters which are common in PPG signal processing, PPG signals were prefiltered (band-pass, pass and stop bands: >0.5 Hz and <0.2 Hz for high-pass filter, <20 Hz and >30 Hz for low-pass filter) and then filtered (low-pass, pass and stop bands: <3 Hz and >5 Hz). Four pulse feature points were defined and extracted (peak, valley, maximal first derivative, and maximal second derivative). For each subject, overall TS and intra-subject TS variability in feature points were calculated as the mean and standard deviation of TS between prefiltered and filtered PPG signals in 50 cardiac cycles. Statistical testing was performed to investigate the effect of measurement site and type of pulse feature on overall TS and intra-subject TS variability.Main results.Measurement site, type of pulse feature, and their interaction had significant impacts on the overall TS and intra-subject TS variability (p < 0.001 for all). Valley and maximal second derivative showed higher overall TS than peak and maximal first derivative. Finger had higher overall TS and lower intra-subject TS variability than other measurement sites.Significance. Measurement site and type of pulse feature can significantly influence the timing of feature points on filtered PPG signals. Filtering parameters should be quoted to support the reproducibility of PPG-related studies.

Mask-Type Sensor for Pulse Wave and Respiration Measurements and Eye Blink Detection

This paper reports on a mask-type sensor for simultaneous pulse wave and respiration measurements and eye blink detection that uses only one sensing element. In the proposed sensor, a flexible air bag-shaped chamber whose inner pressure change can be measured by a microelectromechanical system-based piezoresistive cantilever was used as the sensing element. The air bag-shaped chamber is fabricated by wrapping a sponge pad with plastic film and polyimide tape. The polyimide tape has a hole to which the substrate with the piezoresistive cantilever adheres. By attaching the sensor device to a mask where it contacts the nose of the subject, the sensor can detect the pulses and eye blinks of the subject by detecting the vibration and displacement of the nose skin caused by these physiological parameters. Moreover, the respiration of the subject causes pressure changes in the space between the mask and the face of the subject as well as slight vibrations of the mask. Therefore, information about the respiration of the subject can be extracted from the sensor signal using either the low-frequency component (<1 Hz) or the high-frequency component (>100 Hz). This paper describes the sensor fabrication and provides demonstrations of the pulse wave and respiration measurements as well as eye blink detection using the fabricated sensor.

High Precision Human Skin Temperature Fluctuations Measuring Instrument

This paper describes the experimental results of testing a prototype of a high precision human skin rapid temperature fluctuations measuring instrument. Based on the author’s work, an original circuit solution on a miniature semiconductor diode sensor has been designed. The proposed circuitry provides operation in the full voltage range with automatic setting and holding the operating point, as well as the necessary slope of the conversion coefficient (up to 2300 mV/°C), which makes it possible to register fast temperature oscillations from the surface of the human body and other biological objects. Simulation results in the Microcap 12 software and laboratory tests have confirmed all declared design specifications: temperature resolution of 0.01 °C, transducer thermal time constant of 0.05 s. An original thermostat and an experimental setup for the simultaneous registration of the electrocardiogram, pulse wave signals from the Biopac polygraph MP36 and a signal of temperature oscillations from the prototype thermometer have been designed for further investigations. The preliminary test results indicates that using the designed measuring instrument gives a possibility to provide an in-depth study of the relationship between micro- and macro-blood circulations manifested in skin temperature fluctuations.

Spontaneous extension wave for in vivo assessment of arterial wall anisotropy

Another type of natural wave, traced from longitudinal wall motion and propagation along the artery, is observed in our in vivo human carotid artery experiments. We coin it as extension wave (EW) and hypothesize that EW velocity (EWV) is associated with arterial longitudinal stiffness. The EW is thus assumed to complement the pulse wave (PW), whose velocity (PWV) is tracked from the radial wall displacement and linked to arterial circumferential stiffness through the Moens-Korteweg equation, as indicators for arterial mechanical anisotropy quantification by noninvasive high-frame-rate ultrasound. The relationship between directional arterial stiffnesses and the two natural wave speeds was investigated in wave theory, finite-element simulations based on isotropic and anisotropic arterial models, and in vivo human common carotid artery (n = 10) experiments. Excellent agreement between the theory and simulations showed that EWV was 2.57 and 1.03 times higher than PWV in an isotropic and an anisotropic carotid artery model, respectively, whereas in vivo EWV was consistently lower than PWV in all 10 healthy human subjects. A strong linear correlation was substantiated in vivo between EWV and arterial longitudinal stiffness quantified by a well-validated vascular-guided wave imaging technique (VGWI). We thereby proposed a novel index calculated as EWV²/PWV² as an alternative to assess arterial mechanical anisotropy. Simulations and in vivo results corroborated the effect of mechanical anisotropy on the propagation of spontaneous waves along the arterial wall. The proposed anisotropy index demonstrated the feasibility of the concurrent EW and PW imaged by high frame-rate ultrasound in grading of arterial wall anisotropy.NEW & NOTEWORTHY An extension wave formed by longitudinal wall displacements was observed by high-frame-rate ultrasound in the human common carotid artery in vivo. A strong correlation between extension wave velocity and arterial longitudinal stiffness complements the well-established pulse wave, which is linked to circumferential stiffness, to noninvasively assess direction-dependent wall elasticity of the major artery. The proposed anisotropy index, which directly reflects arterial wall microstructure and function, might be a potential risk factor for screening (sub-) clinical cardiovascular diseases.

Effect of Brain and Pulse Waves on Safety Consciousness and Safety Commitment of Workers at Construction Sites

Even though individual mental and health status largely affects the safety in industrial sites, most studies for preventing industrial accidents are mainly focused on external factors such as regulations, education, etc. In this study, the effect of individual factors on safety (i.e., safety consciousness and safety commitment) was analyzed by collecting brainwave and pulse data at construction sites where industrial accidents have occurred with the highest percentage. The effects of brain stress, concentration, brain activity, and left and right brain imbalance on safety accidents were evaluated through brain wave measurements. In addition, the effects of cumulative fatigue, physical vitality, autonomic nerve health, and autonomic balance were identified through pulse wave measurements. Data were acquired for 180 construction workers at various construction sites, and the workers were classified into three grades according to factors that affected safety accidents at construction sites. Then, the safety consciousness and safety commitment levels of workers corresponding to each grade of the influence factors were evaluated by conducting a questionnaire on safety consciousness and safety commitment. As a result, the characteristics of brain and pulse waves required to improve safety consciousness and safety commitment ability of workers at construction sites were explored.

[The new theory CPET guides the overall plan of individualized precision exercise to effectively improve the overall functional status of "frailty"]

Objective: Under the guidance of the new theory of holistic integrated physiology and medicine, the effect of individualized accurate exercise program on the overall functional state was studied according to cardiopulmonary exercise testing (CPET). Methods: Li xx, female, 31 years old, has a fast heart rate since childhood (90~100 bpm), usually feel cold, especially in autumn and winter, and general health good. CPET was performed after signing the informed consent form at Fuwai Hospital in September 2019. Peak oxygen uptake, anaerobic threshold (AT), and peak cardiac output were (69~72)% pred, respectively, and the oxygen uptake ventilation efficiency and carbon dioxide exhaust ventilation efficiency were basically normal (96~100)% pred. The resting heart rate was fast, the blood pressure was low, the blood pressure response was weak during exercise, and the heart rate was mainly increased. The holistic integrated physiology medical theory pointed out that she was in weak health and heart weakness was the main manifestation. CPET was used to guide individualized precise exercise intensity titration, combine continuous beat-by-beat blood pressure, ECG, pulse and blood glucose dynamic monitoring to formulate an holisticplan of individualized quantitative exercise .Reexamine CPET after 8 weeks' strengthening management. Results: After 8 weeks of intensive holistic management, the limbs were warm and the cold symptoms disappeared. Re-examination of CPET peak oxygen uptake, AT and peak cardiac output were (90~98)% pred, which increased by (30~36)% respectively, and the holistic weak functional status was significantly improved; basically normal oxygen uptake ventilation efficiency and carbon dioxide exhaust ventilation efficiency also increased by (10~37)% respectively; resting heart rate and blood pressure basically returned to normal, and blood pressure and heart rate response during exercise were normal. Continuous ambulatory blood glucose monitoring indicated that the average blood glucose level decreased slightly and became more stable. Repeated measurement results of continuous ECG and beat-to-beat blood pressure also indicated a decrease in heart rate and an increase in blood pressure during rest, exercise and during sleep, and radial pulse wave. The amplitude of the dicrotic wave increases and becomes more pronounced. Conclusion: The new theoretical system to guide CPET to formulate an holistic plan for individualized precision exercise can safely and effectively enhance myocardial contractility, increase stroke volume, increase blood pressure, lower heart rate, stabilize and slightly lower blood glucose, and improve holistic functional status.

Pulse Wave Modeling Using Bio-Impedance Simulation Platform Based on a 3D Time-Varying Circuit Model

Cardiovascular disease (CVD) threatens the lives of many and affects their productivity. Wearable sensors can enable continuous monitoring of hemodynamic parameters to improve the diagnosis and management of CVD. Bio-Impedance (Bio-Z) is an effective non-invasive sensor for arterial pulse wave monitoring based on blood volume changes in the artery due to the deep penetration of its current signal inside the tissue. However, the measured data are significantly affected by the placement of electrodes relative to the artery and the electrode configuration. In this work, we created a Bio-Z simulation platform that models the tissue, arterial pulse wave, and Bio-Z sensing configuration using a 3D circuit model based on a time-varying impedance grid. A new method is proposed to accurately simulate the different tissue types such as blood, fat, muscles, and bones in a 3D circuit model in addition to the pulsatile activity of the arteries through a variable impedance model. This circuit model is simulated in SPICE and can be used to guide design decisions (i.e. electrode placement relative to the artery and electrode configuration) to optimize the monitoring of pulse wave prior to experimentation. We present extensive simulations of the arterial pulse waveform for different sensor locations, electrode sizes, current injection frequencies, and artery depths. These simulations are validated by experimental Bio-Z measurements.

[Cardio-ankle vascular index (CAVI) in diagnostics, risk and severity evaluation of magistral vessels lesion in patients with cardio-vascular diseases and type 2 diabetes]

Assesment of arterial stiffness the substantional prognostic factor for evaluating complications of cardiovascular diseases (CVD) in patients with atherosclerosis, hypertension and type 2 diabetes, may be performed using different parameters, including cardio-ankle vascular index (CAVI). The main purpose of this review is to analyze data from studies where CAVI is used to test the arterial wall stiffness in magistral vessels. CAVI measurement is non-invasive and performed by portable devices which makes it comfortable for ambulatory use in patients who come for a check-up and also in those who already are hospitalized. It does not require any special knowledge from investigator and the test lasts a couple of minutes long. CAVI does not depend on blood pressure changes and is more specific in structural changes of arterial wall assessment than brachial-ankle pulse wave velocity (baPWV). CAVI shows considerable correlation with markers of CVD like atherosclerotic plaques in vessels, diastolic disfunction of left ventricle and angina pectoris. CAVI may be used for early monitoring and assessing the lesions of target organs in patients with atherosclerosis, chronic hypertension and type 2 diabetes. Establishing CAVI as a standart parameter in assessing patients who are at risk of CVD can help to improve complications prevention, reduce mortality and prolong their lifespan.

A new noninvasive method for measurement of dynamic lung compliance from fluctuations on photoplethysmography in respiration

Lung compliance is important in interstitial lung disease (ILD). However, the measurement requires placement of an esophageal pressure probe and is therefore not done in routine clinic practice. This study was performed to develop and verify a new noninvasive method for estimation of dynamic lung compliance (Cdyn) with a photoplethysmograph (PPG) of pulse wave represented as the changes of absorbance of green LED for hemoglobin and to examine its usefulness. A system for measuring Cdyn in combination with changes in estimated pleural pressure (Ppl) from the fluctuations on PPG with respiration and lung volume measured simultaneously by spirometry was developed and verified to show correspondence with the estimated Ppl and the esophageal pressure (Pes), estimated Cdyn, and Cdyn measured with an esophageal balloon. Furthermore, the estimated percentage of predicted Cdyn (%Cdyn) was compared among healthy subjects (HS) (n = 33) and patients with chronic obstructive pulmonary disease (COPD) (n = 31) and ILD (n = 30). Both estimated Ppl and Cdyn were significantly correlated with Pes (r = 0.89) and measured Cdyn (r = 0.63), respectively. The estimated %Cdyn in ILD showed significantly lower values than those in HS and COPD. The estimated %Cdyn was significantly related to percentage of predicted vital capacity (VC) (r = 0.57, P < 0.01) and percentage of predicted diffusion capacity of carbon monoxide (Dl_CO) (r = 0.50, P < 0.01) in patients with ILD. These findings suggested that the newly developed noninvasive and convenient method for Cdyn estimation using a combination of PPG and spirometry may be useful for the assessment of lung fibrosis in ILD.NEW & NOTEWORTHY Our newly developed method for measuring dynamic lung compliance (Cdyn) in combination with changes in estimated intrathoracic pressure from fluctuations on photoplethysmography with respiration and lung volume measured simultaneously by spirometry showed good linear regression between the estimated Cdyn and the Cdyn measured with an esophageal balloon, and the estimated percentage of predicted Cdyn (%Cdyn) showed significantly lower values in patients with interstitial lung disease (ILD) than in healthy subjects and chronic obstructive pulmonary disease (COPD) patients and significant correlations with vital capacity and lung diffusion capacity.

Automatic Classification of Adult Males With and Without Autism Spectrum Disorder by Non-contact Measurement of Autonomic Nervous System Activation

People with autism spectrum disorder (ASD) exhibit atypicality in various domains of behavior. Previous psychophysiological studies have revealed an atypical pattern of autonomic nervous system (ANS) activation induced by psychosocial stimulation. Thus, it might be feasible to develop a novel assessment tool to evaluate the risk of ASD by measuring ANS activation in response to emotional stimulation. The present study investigated whether people with ASD could be automatically classified from neurotypical adults based solely on physiological data obtained by the recently introduced non-contact measurement of pulse wave. We video-recorded faces of adult males with and without ASD while watching emotion-inducing video clips. Features reflective of ANS activation were extracted from the temporal fluctuation of facial skin coloration and entered into a machine-learning algorithm. Though the performance was modest, the gradient boosting classifier succeeded in classifying people with and without ASD, which indicates that facial skin color fluctuation contains information useful for detecting people with ASD. Taking into consideration the fact that the current study recruited only high-functioning adults who have relatively mild symptoms and probably developed some compensatory strategies, ASD screening by non-contact measurement of pulse wave could be a promising assessment tool to evaluate ASD risk.

Correlation between Sarcopenia and Arteriosclerosis in Elderly Community Dwellers: A Multicenter Study

BACKGROUND

Evidence suggests that arteriosclerosis and sarcopenia (decreased muscle mass) share some of their many causes. However, after controlling for confounding factors, it is unclear whether the presence of arteriosclerosis correlates with sarcopenia.

OBJECTIVES

The aim of this paper is to explore whether sarcopenia is associated with arteriosclerosis.

DESIGN

A multicenter cross-sectional community-based study.

MATERIALS AND METHODS

A total of 2511 elderly subjects from six Chinese community health service centers in Anhui province were surveyed through an e-health promotion system to collect basic data and measurements of brachial-ankle pulse wave (baPWV), body composition, and handgrip strength (HGS). Pearson's correlation and binary logistic regression analyses were performed to identify associations between sarcopenia and high baPWV.

RESULTS

The prevalence rates of sarcopenia were 12.9% in men and 15.3% in women according to the 2019 standard of Asian Working Group for Sarcopenia. Among subjects with high baPWV, the proportion of sarcopenia was higher compared to those with normal baPWV (men: 17.7% vs. 3.7%; women: 20.4% vs. 4.9%, both p<0.001). Binary logistic regression analysis revealed that sarcopenia was associated with high baPWV (p<0.0001, odds ratio=1.619) after adjusting for confounding factors. HGS slightly and negatively correlated with baPWV (-0.19 in men and -0.18 in women).

CONCLUSIONS

The intertwined pathophysiological mechanisms shared by arteriosclerosis and sarcopenia are potential targets for future interventions to reduce morbimortality in subjects with both disorders. Upcoming prospective studies and clinical trials are expected to advance these findings.

Acquiring Wearable Photoplethysmography Data in Daily Life: The PPG Diary Pilot Study †

The photoplethysmogram (PPG) signal is widely measured by smart watches and fitness bands for heart rate monitoring. New applications of the PPG are also emerging, such as to detect irregular heart rhythms, track infectious diseases, and monitor blood pressure. Consequently, datasets of PPG signals acquired in daily life are valuable for algorithm development. The aim of this pilot study was to assess the feasibility of acquiring PPG data in daily life. A single subject was asked to wear a wrist-worn PPG sensor six days a week for four weeks, and to keep a diary of daily activities. The sensor was worn for 75.0% of the time, signals were acquired for 60.6% of the time, and signal quality was high for 30.5% of the time. This small pilot study demonstrated the feasibility of acquiring PPG data during daily living. Key lessons were learnt for future studies: (i) devices which are waterproof and require charging less frequently may provide signals for a greater proportion of the time; (ii) data should either be stored on the device or streamed via a reliable connection to a second device for storage; (iii) it may be beneficial to acquire signals during the night or during periods of low activity to achieve high signal quality; and (iv) there are several promising areas for PPG algorithm development including the design of pulse wave analysis techniques to track changes in cardiovascular properties in daily life.

Comparison of arterial wave intensity analysis by pressure-velocity and diameter-velocity methods in a virtual population of adult subjects

Pressure-velocity-based analysis of arterial wave intensity gives clinically relevant information about the performance of the heart and vessels, but its utility is limited because accurate pressure measurements can only be obtained invasively. Diameter-velocity-based wave intensity can be obtained noninvasively using ultrasound; however, due to the nonlinear relationship between blood pressure and arterial diameter, the two wave intensities might give disparate clinical indications. To test the magnitude of the disagreement, we have generated an age-stratified virtual population to investigate how the two dominant nonlinearities viscoelasticity and strain-stiffening cause the two formulations to differ. We found strong agreement between the pressure-velocity and diameter-velocity methods, particularly for the systolic wave energy, the ratio between systolic and diastolic wave heights, and older subjects. The results are promising regarding the introduction of noninvasive wave intensities in the clinic.

Machine Learning-Based Signal Quality Evaluation of Single-Period Radial Artery Pulse Waves: Model Development and Validation

BACKGROUND

The radial artery pulse wave is a widely used physiological signal for disease diagnosis and personal health monitoring because it provides insight into the overall health of the heart and blood vessels. Periodic radial artery pulse signals are subsequently decomposed into single pulse wave periods (segments) for physiological parameter evaluations. However, abnormal periods frequently arise due to external interference, the inherent imperfections of current segmentation methods, and the quality of the pulse wave signals.

OBJECTIVE

The objective of this paper was to develop a machine learning model to detect abnormal pulse periods in real clinical data.

METHODS

Various machine learning models, such as k-nearest neighbor, logistic regression, and support vector machines, were applied to classify the normal and abnormal periods in 8561 segments extracted from the radial pulse waves of 390 outpatients. The recursive feature elimination method was used to simplify the classifier.

RESULTS

It was found that a logistic regression model with only four input features can achieve a satisfactory result. The area under the receiver operating characteristic curve from the test set was 0.9920. In addition, these classifiers can be easily interpreted.

CONCLUSIONS

We expect that this model can be applied in smart sport watches and watchbands to accurately evaluate human health status.

MEMS-Based Pulse Wave Sensor Utilizing a Piezoresistive Cantilever

This paper reports on a microelectromechanical systems (MEMS)-based sensor for pulse wave measurement. The sensor consists of an air chamber with a thin membrane and a 300-nm thick piezoresistive cantilever placed inside the chamber. When the membrane of the chamber is in contact with the skin above a vessel of a subject, the pulse wave of the subject causes the membrane to deform, leading to a change in the chamber pressure. This pressure change results in bending of the cantilever and change in the resistance of the cantilever, hence the pulse wave of the subject can be measured by monitoring the resistance of the cantilever. In this paper, we report the sensor design and fabrication, and demonstrate the measurement of the pulse wave using the fabricated sensor. Finally, measurement of the pulse wave velocity (PWV) is demonstrated by simultaneously measuring pulse waves at two points using the two fabricated sensor devices. Furthermore, the effect of breath holding on PWV is investigated. We showed that the proposed sensor can be used to continuously measure the PWV for each pulse, which indicates the possibility of using the sensor for continuous blood pressure measurement.

Quantitative Comparison of the Performance of Piezoresistive, Piezoelectric, Acceleration, and Optical Pulse Wave Sensors

The accurate measurement of the arterial pulse wave is beneficial to clinical health assessment and is important for the effective diagnosis of many types of cardiovascular disease. A variety of sensors have been developed for the non-invasive detection of these waves, but the type of sensor has an impact on the measurement results. Therefore, it is necessary to compare and analyze the signals obtained under a range of conditions using various pulse sensors to aid in making an informed choice of the appropriate type. From the available types we have selected four: a piezoresistive strain gauge sensor (PESG) and a piezoelectric Millar tonometer (the former with the ability to measure contact force), a circular film acceleration sensor, and an optical reflection sensor. Pulse wave signals were recorded from the left radial, carotid, femoral, and digital arteries of 60 subjects using these four sensors. Their performance was evaluated by analyzing their susceptibilities to external factors (contact force, measuring site, and ambient light intensity) and by comparing their stability and reproducibility. Under medium contact force, the peak-to-peak amplitude of the signals was higher than that at high and low force levels and the variability of signal waveform was small. The optical sensor was susceptible to ambient light. Analysis of the intra-class correlation coefficients (ICCs) of the pulse wave parameters showed that the tonometer and accelerometer had good stability (ICC > 0.80), and the PESG and optical sensor had moderate stability (0.46 < ICC < 0.86). Intra-observer analysis showed that the tonometer and accelerometer had good reproducibility (ICC > 0.75) and the PESG and optical sensor had moderate reproducibility (0.42 < ICC < 0.91). Inter-observer analysis demonstrated that the accelerometer had good reproducibility (ICC > 0.85) and the three other sensors had moderate reproducibility (0.52 < ICC < 0.96). We conclude that the type of sensor and measurement site affect pulse wave characteristics and the careful selection of appropriate sensor and measurement site are required according to the research and clinical need. Moreover, the influence of external factors such as contact pressure and ambient light should be fully taken into account.

MEMS-Based Sensor for Simultaneous Measurement of Pulse Wave and Respiration Rate

The continuous measurements of vital signs (body temperature, blood pressure, pulse wave, and respiration rate) are important in many applications across various fields, including healthcare and sports. To realize such measurements, wearable devices that cause minimal discomfort to the wearers are highly desired. Accordingly, a device that can measure multiple vital signs simultaneously using a single sensing element is important in order to reduce the number of devices attached to the wearer's body, thereby reducing user discomfort. Thus, in this study, we propose a device with a microelectromechanical systems (MEMS)-based pressure sensor that can simultaneously measure the blood pulse wave and respiration rate using only one sensing element. In particular, in the proposed device, a thin silicone tube, whose inner pressure can be measured via a piezoresistive cantilever, is attached to the nose pad of a pair of eyeglasses. On wearing the eyeglasses, the tube of sensor device is in contact with the area above the angular artery and nasal cavity of the subject, and thus, both pulse wave and breath of the subject cause the tube's inner pressure to change. We experimentally show that it is possible to extract information related to pulse wave and respiration as the low-frequency and high-frequency components of the sensor signal, respectively.

Multi-Site Photoplethysmography Technology for Blood Pressure Assessment: Challenges and Recommendations

Hypertension is one of the most prevalent diseases and is often called the “silent killer” because there are usually no early symptoms. Hypertension is also associated with multiple morbidities, including chronic kidney disease and cardiovascular disease. Early detection and intervention are therefore important. The current routine method for diagnosing hypertension is done using a sphygmomanometer, which can only provide intermittent blood pressure readings and can be confounded by various factors, such as white coat hypertension, time of day, exercise, or stress. Consequently, there is an increasing need for a non-invasive, cuff-less, and continuous blood pressure monitoring device. Multi-site photoplethysmography (PPG) is a promising new technology that can measure a range of features of the pulse, including the pulse transit time of the arterial pulse wave, which can be used to continuously estimate arterial blood pressure. This is achieved by detecting the pulse wave at one body site location and measuring the time it takes for it to reach a second, distal location. The purpose of this review is to analyze the current research in multi-site PPG for blood pressure assessment and provide recommendations to guide future research. In a systematic search of the literature from January 2010 to January 2019, we found 13 papers that proposed novel methods using various two-channel PPG systems and signal processing techniques to acquire blood pressure using multi-site PPG that offered promising results. However, we also found a general lack of validation in terms of sample size and diversity of populations.

Modeling arterial pulse waves in healthy aging: a database for in silico evaluation of hemodynamics and pulse wave indexes

The arterial pulse wave (PW) is a rich source of information on cardiovascular (CV) health. It is widely measured by both consumer and clinical devices. However, the physical determinants of the PW are not yet fully understood, and the development of PW analysis algorithms is limited by a lack of PW data sets containing reference CV measurements. Our aim was to create a database of PWs simulated by a computer to span a range of CV conditions, representative of a sample of healthy adults. The typical CV properties of 25-75 yr olds were identified through a literature review. These were used as inputs to a computational model to simulate PWs for subjects of each age decade. Pressure, flow velocity, luminal area, and photoplethysmographic PWs were simulated at common measurement sites, and PW indexes were extracted. The database, containing PWs from 4,374 virtual subjects, was verified by comparing the simulated PWs and derived indexes with corresponding in vivo data. Good agreement was observed, with well-reproduced age-related changes in hemodynamic parameters and PW morphology. The utility of the database was demonstrated through case studies providing novel hemodynamic insights, in silico assessment of PW algorithms, and pilot data to inform the design of clinical PW algorithm assessments. In conclusion, the publicly available PW database is a valuable resource for understanding CV determinants of PWs and for the development and preclinical assessment of PW analysis algorithms. It is particularly useful because the exact CV properties that generated each PW are known.NEW & NOTEWORTHY First, a comprehensive literature review of changes in cardiovascular properties with age was performed. Second, an approach for simulating pulse waves (PWs) at different ages was designed and verified against in vivo data. Third, a PW database was created, and its utility was illustrated through three case studies investigating the determinants of PW indexes. Fourth, the database and tools for creating the database, analyzing PWs, and replicating the case studies are freely available.

Diagnostic accuracy of an algorithm for detecting atrial fibrillation in a wrist-type pulse wave monitor

We evaluated the diagnostic value of atrial fibrillation (AF) measured by a wrist-type pulse wave monitor in this case-control study. Six serial pulse wave values (three in the left and three in the right wrist) were measured using a wrist-type monitor in 29 AF patients and 30 subjects with sinus rhythm. We defined "monitor AF in irregular pulse peak (IPP) 15/20/25" as follows: (a) IPP: |interval of pulse peak - the average of the interval of the pulse peak| ≥ the average of the interval of the pulse peak × 15/20/25%; (b) irregular heartbeat (IHB): beats of IPP ≥ total pulse × 20%; and (c) monitor AF: ≥4 IHBs of the six pulse wave measurements. In IPP 15, the sensitivity and specificity were 0.97 and 1.00, respectively. Pulse wave analysis by a wrist-type monitor was shown to have high sensitivity and specificity for the diagnosis of AF.

Wireless, Portable Fiber Bragg Grating Interrogation System Employing Optical Edge Filter

A small-size, high-precision fiber Bragg grating interrogator was developed for continuous plethysmograph monitoring. The interrogator employs optical edge filters, which were integrated with a broad-band light source and photodetector to demodulate the Bragg wavelength shift. An amplifier circuit was designed to effectively amplify the plethysmograph signal, obtained as a small vibration of optical power on the large offset. The standard deviation of the measured Bragg wavelength was about 0.1 pm. The developed edge filter module and amplifier circuit were encased with a single-board computer and communicated with a laptop computer via Wi-Fi. As a result, the plethysmograph was clearly obtained remotely, indicating the possibility of continuous vital sign measurement.

Laser speckle flowgraphy can also be used to show dynamic changes in the blood flow of the skin of the foot after surgical revascularization

Objectives

Laser speckle flowgraphy is a new method that enables the rapid evaluation of foot blood flow without contact with the skin. We used laser speckle flowgraphy to evaluate foot blood flow in peripheral arterial disease patients before and after surgical revascularization.

Materials and methods

A prospective single-center study. Thirty-one patients with 33 limbs that underwent surgical revascularization for peripheral arterial disease were included. Pre- and postoperative foot blood flows were measured on the plantar surface via laser speckle flowgraphy and skin perfusion pressure. The laser speckle flowgraphy device was used to visualize the blood flow distribution of the target skin and processed the pulse wave velocity of synchronized heart beats. The mean blood flow, which was expressed as the area of the pulse wave as the beat strength of skin perfusion on laser speckle flowgraphy converted into a numerical value, was assessed as dynamic changes following surgery. Beat strength of skin perfusion was also investigated in non-peripheral arterial disease controls (23 patients/46 limbs).

Results

The suitability of beat strength of skin perfusion in non-peripheral arterial disease controls was achieved; the beat strength of skin perfusion value was significantly higher in every area of interest in non-peripheral arterial disease controls compared to that in peripheral arterial disease limbs at the preoperative stage (105.8 ± 8.2 vs. 26.3 ± 8.2; P < 0.01). Although the pulse wave before surgery was visually flat in peripheral arterial disease patients, the pulse wave was remarkably and immediately improved through surgical revascularization. Beat strength of skin perfusion showed a dynamic change in foot blood flow (26.3 ± 8.2 at preoperation, 98.5 ± 6.7 immediately after surgery, 107.6 ± 5.7 at seven days after surgery, P < 0.01 for each compared to preoperation) that correlated with an improvement in skin perfusion pressure.

Conclusions

Laser speckle flowgraphy is a noninvasive, contact-free modality that is easy to implement, and beat strength of skin perfusion is a useful indicator of foot circulation during the perioperative period. Further analysis with a larger number of cases is necessary to establish appropriate clinical use.

Performance of an atrial fibrillation detection algorithm using continuous pulse wave monitoring

BACKGROUND

Detecting asymptomatic and undiagnosed atrial fibrillation (AF) is increasingly important. Recently, we developed a wristwatch-based pulse wave monitor (PWM; Seiko Epson, Japan) capable of long-term recording, with an automatic diagnosis algorithm that uses frequency-based pulse wave analysis. The aim of this study was to evaluate the validity of continuous pulse wave monitoring for detection of AF.

METHODS

During the electrophysiological study (EPS) in patients with AF, simultaneous pulse wave monitoring and Holter electrocardiograms (ECG) were recorded (n = 136, mean age 62.7 ± 10.9 years). The diagnostic accuracy of the PWM for AF was compared to the Holter ECG diagnosis. Standard performance metrics (sensitivity [Se], specificity [Sp], positive predictive value [PPV], and negative predictive value [NPV]) were calculated. The duration-based measurements were based on the diagnosis concordance ratios for the duration of time between diagnosis detected by the PWM and true diagnosis by the Holter ECG (AF or not AF). The episode-based performance metrics were based on the proportion of episodes appropriately detected with the PWM relative to episodes determined by the Holter ECG.

RESULTS

The total recording time was 1,542,770 s (AF: 270,945 s). A high diagnostic Sp (patient average: 96.4%, cumulative: 97.7%) and NPV (patient average: 95.1%, cumulative: 96.8%) were obtained in the duration-based results. In the episode-based metrics, all indices significantly improved with longer AF episode durations.

CONCLUSIONS

Continuous pulse wave monitoring can provide accurate and dependable information to aid in AF diagnosis. A high validity in confirming freedom from AF was shown by a high NPV.

An experimental study of pulse wave measurements with magnetic induction phase shift method

BACKGROUND

Pulse wave monitoring is widely used to evaluate the physiological and pathological states of the cardiovascular system.

OBJECTIVE

High-sensitivity ring sensors were designed, and a simultaneous acquisition platform based on National Instruments T-Clock technology (NI-TCLK) was used to achieve simultaneous pulse detection using both the traditional method and the magnetic induction phase shift (MIPS) method.

METHODS

The excitation signal had a frequency of approximately 10.7 MHz and power of about 20 dBm. A total of 30 volunteers (adults, aged 20-30 y) were selected to corroborate the feasibility of our measurement system. The subjects wore the proposed sensor on their right-hand forefingers and for reference, the piezoelectric pulse sensor on the left-hand forefinger. The pulse waves of these 30 subjects were measured over 2 min each.

RESULTS

The phase shift of the magnetic induction detection signal ranged from 0.6-0.8 degrees. Comparison of detection results for the same subject between the two methods showed that the pulse rate measured by magnetic induction exhibited fewer deviations and better stability than the traditional method. In addition, spectral analysis indicated that the pulse frequencies obtained using the 2 methods were concentrated between 1-3 Hz and were regular in the 1.5 Hz frequency region.

CONCLUSIONS

These results prove that the magnetic induction pulse wave can be used to accurately measure pulse wave features.

Wearable Pulse Wave Monitoring System Based on MEMS Sensors

Pulse wave monitoring is critical for the evaluation of human health. In this paper, a wearable multi-sensor pulse wave monitoring system is proposed and demonstrated. The monitoring system consists of a measuring unit and an analog circuit processing unit. The main part of the measuring unit is a flexible printed circuit board (PCB) with a thickness of 0.15 mm, which includes three micro-electromechanical system (MEMS) pressure sensors softly packaged by polydimethylsiloxane (PDMS), a blood oxygen detector and a MEMS three-axis accelerometer. The MEMS pressure sensors，the blood oxygen detector and the accelerometer are fixed on the expected locations of the flexible PCB. The analog circuit processing unit includes a power supply module, a filter and an amplifier. The pulse waves of two volunteers are detected by the monitoring system in this study. The output signals of the analog circuit processing module are processed and analyzed. In the preliminary test, the time delay of the three pressure pulse waves has been detected and the calculated pulse wave velocities (PWVs) are 12.50 and 11.36 m/s, respectively. The K value, related to the area of the pulse wave, can be obtained. Both the PWV and K value meet the health parameter standards.

[Research on vigilance detection based on pulse wave]

This paper studied the rule for the change of vigilance based on pulse wave. 10 participants were recruited in a 95-minute Mackworth clock test (MCT) experiment. During the experiment, the vigilance of all participants were evaluated by Karolinska sleepiness scale (KSS) and Stanford sleepiness scale (SSS), and behavior data (the reaction time and the accuracy of target) and pulse wave signal of the participants were recorded simultaneously. The result indicated that vigilance of the participants can be divided into 3 classes: the first 30 minutes for high vigilance level, the middle 30 minutes for general vigilance level, and the last 30 minutes for low vigilance level. Besides, time domain features such as amplitude of secondary peak, amplitude of peak and the latency of secondary peak decreased with the decrease of vigilance, while the amplitude of troughs increased. In terms of frequency domain features, the energy of 4 frequency band including 8.600 ~ 9.375 Hz, 11.720 ~ 12.500 Hz, 38.280 ~ 39.060 Hz and 39.060 ~ 39.840 Hz decreased with the decrease of vigilance. Finally, under the recognition model established by the 8 characteristics mentioned above, the average accuracy of three-classification results over the 10 participants was as high as 88.7%. The results of this study confirmed the feasibility of pulse wave in the evaluation of vigilance, and provided a new way for the real-time monitoring of vigilance.

Suicidal Ideation Is Associated with Altered Variability of Fingertip Photo-Plethysmogram Signal in Depressed Patients

Physiological and psychological underpinnings of suicidal behavior remain ill-defined and lessen timely diagnostic identification of this subgroup of patients. Arterial stiffness is associated with autonomic dysregulation and may be linked to major depressive disorder (MDD). The aim of this study was to investigate the association between arterial stiffness by photo-plethysmogram (PPG) in MDD with and without suicidal ideation (SI) by applying multiscale tone entropy (T-E) variability analysis. Sixty-one 10-min PPG recordings were analyzed from 29 control, 16 MDD patients with (MDDSI+) and 16 patients without SI (MDDSI-). MDD was based on a psychiatric evaluation and the Mini-International Neuropsychiatric Interview (MINI). Severity of depression was assessed using the Hamilton Depression Rating Scale (HAM-D). PPG features included peak (systole), trough (diastole), pulse wave amplitude (PWA), pulse transit time (PTT) and pulse wave velocity (PWV). Tone (Diastole) at all lags and Tone (PWA) at lags 8, 9, and 10 were found to be significantly different between the MDDSI+ and MDDSI- group. However, Tone (PWA) at all lags and Tone (PTT) at scales 3-10 were also significantly different between the MDDSI+ and CONT group. In contrast, Entropy (Systole), Entropy (Diastole) and Tone (Diastole) were significantly different between MDDSI- and CONT groups. The suicidal score was also positively correlated (r = 0.39 ~ 0.47; p < 0.05) with systolic and diastolic entropy values at lags 2-10. Multivariate logistic regression analysis and leave-one-out cross-validation were performed to study the effectiveness of multi-lag T-E features in predicting SI risk. The accuracy of predicting SI was 93.33% in classifying MDDSI+ and MDDSI- with diastolic T-E and lag between 2 and 10. After including anthropometric variables (Age, body mass index, and Waist Circumference), that accuracy increased to 96.67% for MDDSI+/- classification. Our findings suggest that tone-entropy based PPG variability can be used as an additional accurate diagnostic tool for patients with depression to identify SI.

[ARM-based Embedded Detection System of Cardiovascular Function Parameters]

A cardiovascular function testing system was designed in platform which was built with ARM microprocessor s3c2440 and Linux system, to achieve pulse wave acquisition, feature extraction, index calculation and so on. This article mainly describes the hardware circuit, and describes the touchscreen driver, external ADC driver, and visualization QT-based applications in detail. The system is easy to use, with real-time, low power consumption. Compared with common cardiovascular function test instrument, the results shows that the system can better assess the cardiovascular function, expecially in several key indicators like subendocardial myocardial viability rate and augmentation index, the indicators show good correlations.