Physiological Measurement System Research Articles

Non-Contact Physiological Measurement System for Wearing Masks During the Epidemic

Physiological signals indicate a person’s physical and mental state at any given time. Accordingly, many studies extract physiological signals from the human body with non-contact methods, and most of them require facial feature points. However, under COVID-19, wearing a mask has become a must in many places, so how non-contact physiological information measurements can still be performed correctly even when a mask covers the facial information has become a focus of research. In this study, RGB and thermal infrared cameras were used to execute non-contact physiological information measurement systems for heart rate, blood pressure, respiratory rate, and forehead temperature for people wearing masks due to the pandemic. Using the green (G) minus red (R) signal in the RGB image, the region of interest (ROI) is established in the forehead and nose bridge regions. The photoplethysmography (PPG) waveforms of the two regions are obtained after the acquired PPG signal is subjected to the optical flow method, baseline drift calibration, normalization, and bandpass filtering. The relevant parameters in Deep Neural Networks (DNN) for the regression model can correctly predict the heartbeat and blood pressure. In addition, the temperature change in the ROI of the mask after thermal image processing and filtering can be used to correctly determine the number of breaths. Meanwhile, the thermal image can be used to read the temperature average of the ROI of the forehead, and the forehead temperature can be obtained smoothly. The experimental results show that the above-mentioned physiological signals of a subject can be obtained in 6-s images with the error for both heart rate and blood pressure within 2%~3% and the error of forehead temperature within ±0.5°C.

Using Mobile Technology to Construct a Network Medical Health Care System

In this study, a multisensory physiological measurement system was built with wireless transmission technology, using a DSPIC30F4011 as the master control center and equipped with physiological signal acquisition modules such as an electrocardiogram module, blood pressure module, blood oxygen concentration module, and respiratory rate module. The physiological data were transmitted wirelessly to Android-based mobile applications via the TCP/IP or Bluetooth serial ports of Wi-Fi. The Android applications displayed the acquired physiological signals in real time and performed a preliminary abnormity diagnosis based on the measured physiological data and built-in index diagnostic data provided by doctors, such as blood oxygen concentration, systolic pressure, and diastolic pressure. In addition, in this study, the R waves, which are the highest peaks of the PQRST waves in electrocardiograms, were analyzed and detected using the heart rate variability (HRV) for time-frequency analysis and calculation of the RR interval time series. In this study, the heart rate data in the same age group were collected, and the optimal value of the standard deviation of normal to normal (SDNN) during the time domain of a normal heartbeat was found using the particle swarm optimization (PSO) algorithm and set as the risk level of the SDNN time domain analysis. A spectral analysis on the activity of the autonomic nervous system (ANS) was performed and the preliminary analysis results were displayed on the Android handheld devices for comprehensive physiological data analysis and HRV time-frequency analysis. Healthcare needs are distributed at all levels, therefore user-friendly software interfaces have been written to meet the healthcare needs at all ages.

Measuring behavior in sport and exercise

Whether it is how equipment interacts with the human body, or how a player perceives equipment, sports equipment development is ultimately linked to the measurement of human behavior. Indeed, measuring behavior is key to sports equipment design and uptake. Measuring behavior is different from the mature discipline of sports biomechanics, since it focuses specifically on the methodological development of measurement techniques, with a close alignment to engineering and technology. As well as being methods based, measuring behavior has a broad scope, including physiological, psychological or movement measurement systems, all of which are pertinent to the field of sports engineering. Subsequently, when we hosted the 11th International Conference of Measuring Behavior, in June 2018 at Manchester Metropolitan University, sport was included as one of the main themes for the conference for the first time. This theme was the focus of the final day of the conference, which started with a keynote lecture on the classification of swimmers with physical impairments, followed by two sessions on sport. These sessions were on: (1) Measuring behavior in elite sport and (2) Monitoring and encouraging participation in sport and physical activity (see Conference Proceedings [1]). Following these sessions, the conference concluded with a visit to the National Cycling Centre in Manchester, hosted by British Cycling. These activities were funded by an Engaging Sports Engineering Grant from the ISEA (International Sports Engineering Association).

Thermophysiological responses to capacitive resistive monopolar radiofrequency electromagnetic radiation in patients with osteoarthritis of the knee joint: A randomised controlled experimental study

ABSTRACT This study investigated the effect of 448 kHz capacitive resistive monopolar radiofrequency (CRMRF) on the superficial and deep physiological responses of patients with osteoarthritis (OA) of the knee(s). Forty-five patients diagnosed with OA in their knee(s) were enrolled into a three-group randomised controlled study, from the waiting list of a local hospital. They received localized treatment with either CRMRF, CRMRF placebo or a control (no treatment) to the knee for 15 minutes. Pre, post, and 20 min follow-up measurements of skin temperature (SKT) and skin blood flow (SBF) were obtained from the knee using the FlexComp Infiniti (SA7550) physiological measurement system. Pre and post-treatment deep blood flow were recorded using Doppler ultrasound. Core temperature, blood pressure (BP) and pulse rate (PR) were concurrently monitored. Group data were compared using the ANOVA model. Statistical significance was set at p ≤ 0.05, 0.8 power, and 95% CI. Significant increases and sustenance of SKT and SBF, and significant increases in volume and intensity of deep blood flow were demonstrated with CRMRF over the placebo and control interventions in all comparisons (p< .001). No meaningful changes in blood flow velocity, core temperature, BP, or PR were noted for any condition. The findings were markedly more pronounced than those previously reported in asymptomatic adults. However, the patients had received a higher average dose of CRMRF (mean (SD): 46.87 (4.08) W) compared to the asymptomatic sample (mean (SD): 42.37 (4.64) W); therefore, further research is needed to better understand the differences in physiological responses between patients and asymptomatic people.

Vision-Based Instant Measurement System for Driver Fatigue Monitoring

In this paper, a vision-based physiological signal measurement system is proposed to instantly measure driver fatigue. A remote photoplethysmography (rPPG) signal is a type of physiological signal measured by a camera without any contact device, and it also retains the characteristics of the PPG, which is useful to evaluate fatigue. To solve the inconvenience caused by the traditional contact-based physiological fatigue detection system and to improve the accuracy, the system measures both the motional and physiological information by using one image sensor. In a practical application, the environmental noise would affect the measured signal, and therefore, we performed a preprocessing step on the signal to extract a clear signal. The experiment was designed in collaboration with Taipei Medical University, and a questionnaire-based method was used to define fatigue. The questionnaire that could directly react to the feeling of the subject was treated as our ground truth. The evaluated correlation was 0.89 and the root mean square error was 0.65 for ten-fold cross-validation on the dataset. The trend of driver fatigue could be evaluated without a contact device by the proposed system. This advantage ensures the safety of the driver and reliability of the system.

Carbon nanotube, poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) and Ag nanoparticle doped gelatin based electro-active hydrogel systems

In this study, gelatin-based conductive hydrogels doped with carbon nanotube (CNT), poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS) and silver (Ag) nanoparticle were prepared for use in biopotential measurements. Gelatin was modified by various concentrations of methacrylic anhydride (MA) to obtain photo-crosslinkable gelatin methacrylate (GelMA) polymer with low (21%), medium (44%) and high (78%) methacrylation degree. Chemical modification of gelatin was characterized by 1H-NMR spectroscopy. It was observed that mechanical properties of the GelMA hydrogels were highly dependent on methacrylation degree. Ultimate compressive stress of low, medium and high methacrylated gelatin hydrogel was measured to be 9.97 ± 0.14 kPa, 17.83 ± 1.73 kPa and 38.23 ± 2.96 kPa, respectively. Surface morphology of hydrogels was visualized by scanning electron microscope (SEM). The pore size of methacrylated gelatin hydrogel significantly reduced with the addition of CNT, PEDOT:PSS and Ag nanoparticle into the hydrogel matrix. The results of thermal gravimetric analysis showed that conductive hydrogels were of higher thermal stability than nonconductive GelMA hydrogel. The suitability of the prepared hydrogels for biopotential measurements was determined by equivalent impedance measurements. Impedance values of hydrogel samples were obtained in the frequency range of 20 Hz–500 Hz. The hydrogel materials prepared in this study exhibited high impedance at low frequencies and low impedance at high frequencies. The results of this study showed that the hydrogels produced with Ag nanoparticle are more suitable electrode materials for physiological measurement systems such as electrocardiography (ECG) and electroencephalography (EEG).

An EMG Patch for the Real-Time Monitoring of Muscle-Fatigue Conditions During Exercise.

In recent years, wearable monitoring devices have been very popular in the health care field and are being used to avoid sport injuries during exercise. They are usually worn on the wrist, the same as sport watches, or on the chest, like an electrocardiogram patch. Common functions of these wearable devices are that they use real time to display the state of health of the body, and they are all small sized. The electromyogram (EMG) signal is usually used to show muscle activity. Thus, the EMG signal could be used to determine the muscle-fatigue conditions. In this study, the goal is to develop an EMG patch which could be worn on the lower leg, the gastrocnemius muscle, to detect real-time muscle fatigue while exercising. A micro controller unit (MCU) in the EMG patch is part of an ARM Cortex-M4 processor, which is used to measure the median frequency (MF) of an EMG signal in real time. When the muscle starts showing tiredness, the median frequency will shift to a low frequency. In order to delete the noise of the isotonic EMG signal, the EMG patch has to run the empirical mode decomposition algorithm. A two-electrode circuit was designed to measure the EMG signal. The maximum power consumption of the EMG patch was about 39.5 mAh. In order to verify that the real-time MF values measured by the EMG patch were close to the off-line MF values measured by the computer system, we used the root-mean-square value to estimate the difference in the real-time MF values and the off-line MF values. There were 20 participants that rode an exercise bicycle at different speeds. Their EMG signals were recorded with an EMG patch and a physiological measurement system at the same time. Every participant rode the exercise bicycle twice. The averaged root-mean-square values were 2.86 ± 0.86 Hz and 2.56 ± 0.47 Hz for the first and second time, respectively. Moreover, we also developed an application program implemented on a smart phone to display the participants’ muscle-fatigue conditions and information while exercising. Therefore, the EMG patch designed in this study could monitor the muscle-fatigue conditions to avoid sport injuries while exercising.

Guest Editorial The 2018 IEEE International Symposium on Medical Measurements and Applications Special Section

The IEEE International Symposium on Medical Measurement and Applications—MeMeA 2018, which took place in Rome, Italy, on June 11–13, 2018, was a real and concrete opportunity for presenting recent developments in measurement and instrumentation related to medicine. The 13th edition of the Symposium concretely promoted discussion on electrical, chemical, and physiological sensors and measurement systems, which delivers trustable measurement data for prevention, diagnosis, or treatment of different diseases. Other aspects related to the measurement sciences were also presented during the event, such as biosignal processing, quality control of medical devices, medical instrumentation uncertainty/calibration, e-health technologies, wearable devices, and biomechanics/rehabilitation systems.

Photoplethysmogram Signal Quality Assessment Using Support Vector Machine and Multi-Feature Fusion

Background: Noise is unavoidable in the physiological signal measurement system. Poor quality signals can affect the results of analysis and disable the following clinical diagnosis. Thus, it is necessary to perform signal quality assessment before we interpreting the signal. Objective: In this work, we describe a method combing support vector machine (SVM) and multi-feature fusion for assessing the signal quality of pulsatile waveforms, concentrating on the photoplethysmogram (PPG). Methods: PPG signals from 53 healthy volunteers were recorded. Each had a 5 min length. Signal quality in each heart beat was manual annotated by clinical expert, and then the signal quality in 5 s episode was automatically calculated according to the results from each beat segments, resulting in a total of 13,294 5-s PPG segments. Then a SVM was trained to classify clean/noisy PPG recordings by inputting a set of twelve signal quality features. Further experiments were carried out to verify the proposed SVM based signal quality classifier method. Results: An average accuracy of 87.90%, a sensitivity of 88.10% and a specificity of 87.66% were found on the 10-fold cross validation. Conclusions: The signal quality of PPGs can be accurately classified by using the proposed method.

Models to predict both sensible and latent heat transfer in the respiratory tract of Morada Nova sheep under semiarid tropical environment.

The aim of this study was to build a prediction model both sensible and latent heat transfer by respiratory tract for Morada Nova sheep under field conditions in a semiarid tropical environment, using easily measured physiological and environmental parameters. Twelve dry Morada Nova ewes with an average of 3±1.2years old and average body weight of 32.76±3.72kg were used in a Latin square design 12×12 (12days of records and 12 schedules). Tidal volume, respiratory rate, expired air temperature, and partial vapor pressure of the expired air were obtained from the respiratory facial mask and using a physiological measurement system. Ewes were evaluated from 0700 to 1900h in each day under shade. A simple nonlinear model to estimate tidal volume as a function of respiratory rate was developed. Equation to estimate the expired air temperature was built, and the ambient air temperature was the best predictor together with relative humidity and ambient vapor pressure. In naturalized Morada Nova sheep, respiratory convection seems to be a mechanism of heat transfer of minor importance even under mild air temperature. Evaporation from the respiratory system increased together with ambient air temperature. At ambient air temperature, up to 35°C respiratory evaporation accounted 90% of the total heat lost by respiratory system, on average. Models presented here allow to estimate the heat flow from the respiratory tract for Morada Nova sheep bred in tropical region, using easily measured physiological and environmental traits as respiratory rate, ambient air temperature, and relative humidity.

Inter-unit variability in two ParvoMedics TrueOne 2400 automated metabolic gas analysis systems

Knowing the inter-unit variability, especially the technological error, is important when using many physiological measurement systems, yet no such inter-unit analysis has been undertaken on duplicate automated gas analysis systems. This study investigated the inter-unit performance of two identical ParvoMedics TrueOne 2400 automated gas analysis systems during a range of submaximal steady-state exercises performed on an electromagnetic cycle ergometer. Fifteen adult males were tested on two separate days a rest, 30, 60, 90, and 120 Watts with the duplicate gas analysis units arranged (1) collaterally (2 min of steady-state expired gas was alternately passed through each system), and (2) simultaneously (identical steady-state expired gas was passed simultaneously through both systems). Total within-subject variation (biological + technological) was determined from the collateral tests, but the unique inter-unit variability (technological error between identical systems) was shown by the simultaneous tests. Absolute percentage errors (APE), coefficient of variations (CV), effect sizes and Bland–Altman analyses were undertaken on the metabolic data, including expired ventilation (V E), oxygen consumption (VO2) and carbon dioxide production (VCO2). The few statistically significant differences detected between the two duplicate systems were determined to have small or trivial effect sizes, and their magnitudes to be of little physiological importance. The total within-subject variations for VO2, VCO2 and V E each equated to a mean CV and mean APE value of ~4 and ~6 %, whilst the respective inter-unit technological errors equated to ~1.5 and ~2.1 %. The two ParvoMedics TrueOne 2400 systems demonstrated excellent inter-unit agreement.

A Real-Time Multi-Channel Monitoring System for Stem Cell Culture Process

A novel, up to 128 channels, multi-parametric physiological measurement system suitable for monitoring hematopoietic stem cell culture processes and cell cultures in general is presented in this paper. The system aims to measure in real-time the most important physical and chemical culture parameters of hematopoietic stem cells, including physicochemical parameters, nutrients, and metabolites, in a long-term culture process. The overarching scope of this research effort is to control and optimize the whole bioprocess by means of the acquisition of real-time quantitative physiological information from the culture. The system is designed in a modular manner. Each hardware module can operate as an independent gain programmable, level shift adjustable, 16 channel data acquisition system specific to a sensor type. Up to eight such data acquisition modules can be combined and connected to the host PC to realize the whole system hardware. The control of data acquisition and the subsequent management of data is performed by the system's software which is coded in LabVIEW. Preliminary experimental results presented here show that the system not only has the ability to interface to various types of sensors allowing the monitoring of different types of culture parameters. Moreover, it can capture dynamic variations of culture parameters by means of real-time multi-channel measurements thus providing additional information on both temporal and spatial profiles of these parameters within a bioreactor. The system is by no means constrained in the hematopoietic stem cell culture field only. It is suitable for cell growth monitoring applications in general.

Physiological measurements in smart clothing: a case study of total body water estimation with bioimpedance

A wearable physiological bioimpedance measurement system has been designed and implemented. Measured bioimpedance values can be utilized for total body water (TBW) estimation. This information can be useful for, eg, athletes whose performance weakens due to dehydration. The system is integrated into a sport suit and its functionality has been tested by performing walking, fitness cycling and running tests. Also reference tests in a sauna have been performed. Altogether, nine persons have been participating in tests. During long-term exercising, TBW values were decreased. However, more tests are needed in order to analyse the measurement results accurately.

Impact of Brown Ring Disease on the energy budget of the Manila clam Ruditapes philippinarum

Brown Ring Disease (BRD) is a bacterial disease caused by the pathogen, Vibrio tapetis. The disease induces formation of a brown deposit on inner shell of the Manila clam, Ruditapes philippinarum. Development of this disease is correlated with a decrease in the condition index of infected clams. Experiments were conduced in order to assess the effect of the development of BRD on two parameters affecting the energy balance of the clams: the clearance and the respiration rates. Experiments were performed in a physiological measurement system that allowed simultaneous measures of clearance and respiration rates. During both acclimation and measurements clams were fed with cultured T-iso and temperature was close to seasonal field temperature (10°C). Our results showed that severely diseased clams (conchiolin deposit stage, CDS ≥ 4) are subject to weight loss in comparison to uninfected ones, indicating that BRD induces a disequilibrium in the energy balance. We demonstrated a reduction of the clearance rate of severely diseased clams which led to a decrease in energy acquisition. Respiration rate showed a significant decrease with BRD symptoms, but evidence in the literature allowed us to hypothesize that energy mobilised for an immune response and lesion repair increases overall organism maintenance costs. Both factors should thus contribute to the degradation of the energy balance of diseased clams. Because effects of BRD on naturally infected clams only appears significant for CDS ≥ 4, when brown ring assumes a significant place on the inner shell, we consider that the Manila clam is tolerant of low disease levels.

Non-invasive measurement of pulse wave velocity using transputer-based analysis of Doppler flow audio signals

A system for the measurement of arterial pulse wave velocity is described. A personal computer (PC) plug-in transputer board is used to process the audio signals from two pocket Doppler ultrasound units. The transputer is used to provide a set of bandpass digital filters on two channels. The times of excursion of power through thresholds in each filter are recorded and used to estimate the onset of systolic flow. The system does not require an additional spectrum analyser and can work in real time. The transputer architecture provides for easy integration into any wider physiological measurement system.

Virtual Reality System Using Psychological and Physiological Data An Application to Sports Image Training System

The authors propose a new Virtual Reality (VR) system using psychological and physiological data which reflect users’ mental state and voluntary and involuntary reactions. The VR system consists of a psychological and physiological data measurement system, human information processing model units, and an intelligent feedback system. This VR system can provide users with a more comfortable environment in virtual space. As a case study, the authors have applied the system to Sports CAI, in particular a Sports Image Training System for skiing, and an experimental prototype system has been developed. The system consists of weight measurement devices, ski scene display, and data display. According to the movement of the skier displayed on the screen, trainees can control their weight positioning for skiing. The system gives some instructions for improving skiing on the basis of weight data. The new image training method was realized by displaying psychological and physiological data in a virtual environment and by feedback of the data through real time visual information.

Experimental determination of the frequency response characteristics of physiological pressure measurement systems.

Experimental determination of the frequency response characteristics of physiological pressure measurement systems.