Physiological Monitoring System Research Articles

Stretchable Thermoelectric Generators for Self‐Powered Wearable Health Monitoring

AbstractAs continuous wearable physiological monitoring systems become more ubiquitous in healthcare, there is an increasing need for power sources that can sustainably power wireless sensors and electronics for long durations. Wearable energy harvesting with thermoelectric generators (TEGs), in which body heat is converted to electrical energy, presents a promising way to prolong wireless operation and address battery life concerns. In this work, high performance TEGs are introduced that combine 3D printed elastomers with liquid metal epoxy polymer composites and thermoelectric semiconductors to achieve elastic compliance and mechanical compatibility with the body. The thermoelectric properties are characterized in both energy harvesting (Seebeck) and active heating/cooling (Peltier) modes, and examine the performance of wearable energy harvesting under various conditions such as sitting, walking, and running. When worn on a user's forearm while walking outside, the TEG arrays are able to power circuitry to collect photoplethysmography (PPG) waveform data with a photonic sensor and wirelessly transmit the data to an external PC using an on‐board Bluetooth Low Energy (BLE) radio. This represents a significant step forward on the path to sustainable body‐worn smart electronics.

Combined HRAS and NRAS ablation induces a RASopathy phenotype in mice

BackgroundHRASKO/NRASKO double knockout mice exhibit exceedingly high rates of perinatal lethality due to respiratory failure caused by a significant lung maturation delay. The few animals that reach adulthood have a normal lifespan, but present areas of atelectasis mixed with patches of emphysema and normal tissue in the lung.MethodsEight double knockout and eight control mice were analyzed using micro-X-ray computerized tomography and a Small Animal Physiological Monitoring system. Tissues and samples from these mice were analyzed using standard histological and Molecular Biology methods and the significance of the results analyzed using a Student´s T-test.ResultsThe very few double knockout mice surviving up to adulthood display clear craniofacial abnormalities reminiscent of those seen in RASopathy mouse models, as well as thrombocytopenia, bleeding anomalies, and reduced platelet activation induced by thrombin. These surviving mice also present heart and spleen hyperplasia, and elevated numbers of myeloid-derived suppressor cells in the spleen. Mechanistically, we observed that these phenotypic alterations are accompanied by increased KRAS-GTP levels in heart, platelets and primary mouse embryonic fibroblasts from these animals.ConclusionsOur data uncovers a new, previously unidentified mechanism capable of triggering a RASopathy phenotype in mice as a result of the combined removal of HRAS and NRAS.

A Low-Cost Smart Wearable Glove for Non-Invasive Health Monitoring

Wearable physiological signal monitoring systems hold notable potential in the future of personal healthcare by seamlessly integrating into daily life, providing continuous monitoring, and aiding in the early detection of health issues. This research presents a wearable health monitoring glove, with a focus on cost-effectiveness while maintaining efficiency for developing countries. The wearable glove can track vital physiological indicators like Blood Pressure, Body Temperature, Glucose level, Blood Oxygen Saturation, Hemoglobin level, ECG, Room Temperature, Humidity, and Motion Tracking. A user-friendly interface facilitates easy interaction, while efforts in energy-efficient design and power management aim to prolong battery life. Also, real-time data monitoring ensures precision in signal analysis and the extraction of vital health data of individuals. The proposed wearable hand glove utilizes a collection of sensors and integrates them towards the diverse detection of skin humidity, temperature, blood oxygen, hemoglobin, etc. non-invasively. Apart from its technical features, the research explores potential applications in healthcare, fitness tracking, and research fields, presenting a versatile solution. Beyond its technical attributes, the research explores potential applications in medical and personal healthcare, fitness tracking, sports, etc. Collaborative efforts with regulatory bodies assess the feasibility of obtaining necessary approvals or certifications, while scalability considerations pave the way for potential mass production and market deployment.

Use of artificial intelligence to develop predictive algorithms of cough and PCR-confirmed COVID-19 infections based on inputs from clinical-grade wearable sensors

There have been over 769 million cases of COVID-19, and up to 50% of infected individuals are asymptomatic. The purpose of this study aimed to assess the use of a clinical-grade physiological wearable monitoring system, ANNE One, to develop an artificial intelligence algorithm for (1) cough detection and (2) early detection of COVID-19, through the retrospective analysis of prospectively collected physiological data from longitudinal wear of ANNE sensors in a multicenter single arm study of subjects at high risk for COVID-19 due to occupational or home exposures. The study employed a two-fold approach: cough detection algorithm development and COVID-19 detection algorithm development. For cough detection, healthy individuals wore an ANNE One chest sensor during scripted activity. The final performance of the algorithm achieved an F-1 score of 83.3% in twenty-seven healthy subjects during biomarker validation. In the COVID-19 detection algorithm, individuals at high-risk for developing COVID-19 because of recent exposures received ANNE One sensors and completed daily symptom surveys. An algorithm analyzing vital parameters (heart rate, respiratory rate, cough count, etc.) for early COVID-19 detection was developed. The COVID-19 detection algorithm exhibited a sensitivity of 0.47 and specificity of 0.72 for detecting COVID-19 in 325 individuals with recent exposures. Participants demonstrated high adherence (≥ 4 days of wear per week). ANNE One shows promise for detection of COVID-19. Inclusion of respiratory biomarkers (e.g., cough count) enhanced the algorithm's predictive ability. These findings highlight the potential value of wearable devices in early disease detection and monitoring.

Effect of Ambient Temperature on Impedance-Based Physiological Activity Evaluation of Zelkova Tree

A system has been developed to remotely, continuously, and quantitatively measure the physiological activity of trees. The developed tree physiological activity monitoring (TPAM) system is equipped with electrical impedance, temperature, and light intensity measurement functions. In the two-contact impedance measurement method used in the previous plant impedance measurement, errors due to the polarization impedance of the electrodes could not be avoided. The developed TPAM system adopted a four-contact measurement method that could avoid polarization impedance errors, and, with it, the long-term monitoring of zelkova trees was performed. The monitoring of seasonal changes was conducted from July to November, and an impedance change pattern that repeated on a daily basis was observed in the short term, and an overall increase in the impedance was observed in the long term. Impedance changes related to daily temperature changes were observed even after all the tree leaves had fallen, meaning that this effect should be excluded when using impedance to evaluate tree vitality. For this reason, the influence of temperature fluctuations was excluded by using only the impedance values at the same daily temperature of 25 degrees from July to November. The analysis results at 25 degrees showed that the tree impedance value increased linearly by 8.7 Ω per day. The results of this series of long-term monitoring and analysis revealed that the ambient temperature must be taken into account in the evaluation of tree physiological activity based on electrical impedance.

Single-point curved fiber optic pulse sensor for physiological signal prediction based on the genetic algorithm-support vector regression model

For hypertensive patients, a real-time human physiological signal monitoring system helps to track blood pressure status and provides valuable data to clinicians for early diagnosis and timely intervention. Optical fiber pulse sensing has superior conditions such as resistance to electromagnetic interference and richness of measured pulse characteristics. In this study, a monitoring system based on a single-point curved fiber pulse sensor (CFPS) was used to collect the pulse wave signal of a human radial artery. The features of the pulse wave signal were used to estimate the pulse wave transit time (PTT) and Blood Pressure—systolic blood pressure (SBP) and diastolic blood pressure (DBP)—based on support vector regression (SVR) optimized by a genetic algorithm (GA) (GA-SVR model). The results show that the root mean square error (RMSE) of SBP, DBP and PTT were 1.571 mmHg, 3.250 mmHg and 5.719 ms, respectively, and the results met the Advancement of Medical Instrumentation (AAMI) criteria. Therefore, a real-time pulse wave monitoring system based on a single-point CFPS can well predict human physiological signals such as PTT, SBP and DBP.

Wireless broadband acousto-mechanical sensing system for continuous physiological monitoring.

The human body generates various forms of subtle, broadband acousto-mechanical signals that contain information on cardiorespiratory and gastrointestinal health with potential application for continuous physiological monitoring. Existing device options, ranging from digital stethoscopes to inertial measurement units, offer useful capabilities but have disadvantages such as restricted measurement locations that prevent continuous, longitudinal tracking and that constrain their use to controlled environments. Here we present a wireless, broadband acousto-mechanical sensing network that circumvents these limitations and provides information on processes including slow movements within the body, digestive activity, respiratory sounds and cardiac cycles, all with clinical grade accuracy and independent of artifacts from ambient sounds. This system can also perform spatiotemporal mapping of the dynamics of gastrointestinal processes and airflow into and out of the lungs. To demonstrate the capabilities of this system we used it to monitor constrained respiratory airflow and intestinal motility in neonates in the neonatal intensive care unit (n = 15), and to assess regional lung function in patients undergoing thoracic surgery (n = 55). This broadband acousto-mechanical sensing system holds the potential to help mitigate cardiorespiratory instability and manage disease progression in patients through continuous monitoring of physiological signals, in both the clinical and nonclinical setting.

Arterial and Venous Pressure Monitoring during Cardiopulmonary Resuscitation for Out-of-Hospital Arrests: Four Case Reports

Background: A new physiological monitoring system that simultaneously measures femoral arterial pressure, femoral venous pressure, and cerebral tissue oxygen saturation during CPR was used to evaluate the quality of cardiopulmonary resuscitation. In this case report, we would like to present four representative cases with this physiological monitoring system during CPR. Cases: We invasively measured femoral arterial pressure and femoral venous pressure if catheters were immediately inserted into the femoral artery and femoral vein for potential candidates who required extracorporeal cardiopulmonary resuscitation but did not receive such interventions. We presented several cases, including two cases in which cardiopulmonary resuscitation resulted in higher femoral arterial pressure compared to femoral venous pressure, an upward trend in cerebral tissue oxygen saturation values was observed, and both instances achieved the return of spontaneous circulation. In contrast, we also presented two patients with significant increases in femoral venous pressure and low cerebral tissue oxygen saturation values. In both cases, the return of spontaneous circulation was not achieved. Conclusions: We presented cases in which the femoral venous pressure exceeded the femoral arterial pressure using a simultaneous physiological monitoring system to monitor arterial pressure, venous pressure, and cerebral tissue oxygen saturation during cardiopulmonary resuscitation. Further case accumulations will be necessary to assess the variations in hemodynamic status during cardiopulmonary resuscitation and the association between each hemodynamic status and outcomes after cardiac arrest.

Lumpy Diseases Detection using Machine Learning

Machine learning algorithms for improving animal health monitoring have accelerated the creation of ML applications for behavioral and physiological monitoring systems, including ML-based animal health monitoring systems. Currently, farm animals are raised all over the world, and it is necessary to monitor their physiological processes. It is suggested in this article to use machine learning models to continuously monitor each animal's vital signs and look for biological changes. In this model, crucial data is gathered via IoT devices, and data analysis is carried out using machine learning techniques to identify potential dangers from changes in an animal's physiological state. The results of the experiments demonstrate that the suggested model is accurate and efficient enough to identify animal situations. For our purposes, the CNN and YOLO accuracy of more than 90% is a promising outcome. Keywords- Lumpy disease , Machine learning, Images

A wireless physiological parameter monitoring system with a treatment feedback function during neonatal phototherapy

Objective. Neonatal jaundice is a common condition in the early stages of newborns, and phototherapy is a fast, safe and effective method that is used to treat it. However, recent studies have shown that phototherapy may elicit side effects in infants, such as hypothermia, hyperthermia and dehydration. To improve the quality of phototherapy and the prognosis of patients, the changes in neonatal physiological parameters during phototherapy should be monitored to give better feedback to pediatricians or the phototherapy system. However, the current standard of clinical care during neonatal phototherapy with hard-wired devices limits this realization. Approach. Here, we developed a prototype of a neonatal wearable device, which can wirelessly potentially monitor the jaundice value, transepidermal water loss, skin wettedness factor and body orientation during phototherapy, and conducted prototype validation experiments. We also set up user-friendly interfaces and an analysis system on custom software, all designed to make the future addition of data interfaces for treatment feedback functions easier. Main results. The preliminary in vitro experiment demonstrated the effectiveness of simultaneous monitoring of the required physiological parameters. And further suggestions and specific operations are discussed in terms of optimization of the treatment of neonatal jaundice. Significance. It is believed that the established system has the potential to provide a basis for future phototherapy nursing guidelines and physiological monitoring standards.

MetaPhys: Contactless Physiological Sensing of Multiple Subjects Using RIS-Based 4-D Radar

Contactless physiological signal sensing is an emerging technology for routine health monitoring, ambient-assisted living, automotive, search and rescue, and public security. In this work, we propose MetaPhys, a reconfigurable intelligent surface (RIS)-based contactless physiological signal monitoring system that can simultaneously sense multiple persons and their respiratory and cardiac signals. The proposed system localizes the human targets by utilizing RIS to dynamically manipulate the electromagnetic waves in the environment for beamforming and 3D radar imaging in the spatial dimension. Then it extracts the respiration and cardiac signals from the sequential echoes in the temporal dimension. The high-resolution information in the four dimensions as “3D space + 1D time" makes it comprehensively perceive the targets and environment. The beamforming allows the radiated energy to focus on the thoraxes, which helps reduce interference and distortion caused by stationary reflectors (i.e., clutters, static body parts, and multipath), thereby improving the signal-to-noise ratio and enabling long-range measurements. We also verify the measured data in a real indoor environment, and the experimental results show that the proposed system can accurately monitor the physiological signals of multiple subjects. The root mean square errors of respiratory rate and heart rate at a distance of 3 meters are 0.2 breaths per minute and 1.1 beats per minute, respectively.

Near-IR Embedded in a Physiological Signal Monitoring System

Near-IR Embedded in a Physiological Signal Monitoring System

Multifunctional Biosensing Platform Based on Nickel-Modified Laser-Induced Graphene.

Nickel plating electrolytes prepared by using a simple salt solution can achieve nickel plating on laser-induced graphene (LIG) electrodes, which greatly enhances the electrical conductivity, electrochemical properties, wear resistance, and corrosion resistance of LIG. This makes the LIG-Ni electrodes well suited for electrophysiological, strain, and electrochemical sensing applications. The investigation of the mechanical properties of the LIG-Ni sensor and the monitoring of pulse, respiration, and swallowing confirmed that the sensor can sense insignificant deformations to relatively large conformal strains of skin. Modulation of the nickel-plating process of LIG-Ni, followed by chemical modification, may allow for the introduction of glucose redox catalyst Ni2Fe(CN)6 with interestingly strong catalytic effects, which gives LIG-Ni impressive glucose-sensing properties. Additionally, the chemical modification of LIG-Ni for pH and Na+ monitoring also confirmed its strong electrochemical monitoring potential, which demonstrates application prospects in the development of multiple electrochemical sensors for sweat parameters. A more uniform LIG-Ni multi-physiological sensor preparation process provides a prerequisite for the construction of an integrated multi-physiological sensor system. The sensor was validated to have continuous monitoring performance, and its preparation process is expected to form a system for non-invasive physiological parameter signal monitoring, thus contributing to motion monitoring, disease prevention, and disease diagnosis.

Human Physiological Condition Monitoring System based on Microcontrollers

With the rise in living standards, people are increasingly focusing on their health, and monitoring their physiological condition has become a popular trend. Sudden illnesses or hidden chronic conditions can cause abnormal fluctuations in temperature and heart rate, which can be difficult to detect without continuous monitoring. The main objective of this project is to develop a cost-effective and efficient system to monitor vital signs such as heart rate, body temperature, and steps taken, based on systematic experimental studies. The system utilizes a pulse sensor DS18B20, and ADXL345 to monitor the heart rate, body temperature, and motion status of the human body. The circuit and the HC-05 work together to transmit the detected data from the sensor to the MCU, which further transmits it to the LCD1602 or mobile phone interface for real-time display. The system provides a user-friendly interface and real-time monitoring, making it easier for individuals to keep track of their health status. This paper presents an innovative approach to human physiological condition monitoring using a microcontroller-based system, which has significant potential for improving healthcare by enabling early detection and prevention of medical conditions, ultimately leading to better quality of life.

Recent Advances in Polymer Composites for Flexible Pressure Sensors.

Pressure sensors show significant potential applications in health monitoring, bio-sensing, electronic skin, and tactile perception. Consequently, tremendous research interest has been devoted to the development of high-performance pressure sensors. In this paper, recent progress on the polymer composite-based flexible pressure sensor is reviewed. The parameters of pressure sensors, including sensitivity, linear response range, detection limit, response speed, and reliability, are first introduced. Secondly, representative types of pressure sensors and relevant working principles are introduced and discussed. After that, the applications in human physiology monitoring, health monitoring, artificial skin, and self-powered smart system are listed and discussed in detail. Finally, the remaining challenges and outlook of polymer composite-based flexible sensors are summarized at the end of this review paper. This work should have some impact on the development of high-performance flexible pressure sensors.

Self-Assembled Porous-Reinforcement Microstructure-Based Flexible Triboelectric Patch for Remote Healthcare

HighlightsThe porous-reinforcement microstructure is constructed by the self-assembly of silicone rubber adhering to the porous framework of the PU sponge.With the excellent performance both for tiny pressure and large mechanical stimuli, the flexible triboelectric patch can be used to monitor pulse wave and plantar pressure.A remote healthcare system for real-time physiological signal monitoring is proposed.

Comparison of Slate Safety Wearable Device to Ingestible Pill and Wearable Heart Rate Monitor.

With the increase in concern for deaths and illness related to the increase in temperature globally, there is a growing need for real-time monitoring of workers for heat stress indicators. The purpose of this study was to determine the usability of the Slate Safety (SS) wearable physiological monitoring system. Twenty nurses performed a common task in a moderate or hot environment while wearing the SS device, the Polar 10 monitor, and having taken the e-Celsius ingestible pill. Data from each device was compared for correlation and accuracy. High correlation was determined between the SS wearable device and the Polar 10 system (0.926) and the ingestible pill (0.595). The SS was comfortable to wear and easily monitored multiple participants from a distance. The Slate Safety wearable device demonstrated accuracy in measuring core temperature and heart rate while not restricting the motion of the worker, and provided a remote monitoring platform for physiological parameters.

Self-powered and wireless physiological monitoring system with integrated power supply and sensors

With the increase in people’s concern for personal health, the demand for convenient health monitoring electronics has grown noticeably. Wearable physiological sensors with multi-functionality and continuous power supply are constructed through system-level integration and delicate circuit design for energy management and low-power sensing. Energy harvested from body motion and solar or domestic lighting has great potential in powering wearable electronics, eliminating the need of batteries or plug-in power sources. Triboelectric nanogenerators readily fabricated with digital ink-jet printing display a high-power output of 30.96 mW/cm2 after integration with a flexible thin-film solar cell, which ensures unremitting work of the sensors. The self-powered physiological monitoring system can continuously monitor and wirelessly transmit the electrocardiogram, blood pressure, temperature, and motion parameters of the human in real-time without the need for an external power source, providing the wearer with a reliable monitoring means.

Wearable Optical Fiber Beat Frequency Digital Sensing System for Real-Time Non-Invasive Multiple Human Physiological Parameters Monitoring

An optical fiber beat frequency sensing system (BFSS) for multiple human physiological parameters monitoring is proposed. To the best of the authors' knowledge, this is the first BFSS ever reported for multiple human physiological parameters monitoring. By utilizing both fiber Bragg grating (FBG) and fiber laser sensor, not only a low frequency vibration detection with the lowest detectable frequency of 0.25 Hz can be achieved for respiration, heartbeat and pulse signals monitoring, but also human body temperature can be monitored at the same time. Two kinds of beat frequency signals (BFS) are generated in the sensing systems including both polarization laser modes' beat frequency (PMBF) signals and longitudinal mode beat frequency (LMBF) signals. The PMBF signal is utilized for respiration, heartbeat and pulse signals monitoring. Variational mode decomposition (VMD) algorithm is utilized to decompose the monitored time-frequency PMBF signals into single-component respiration, heartbeat and pulse signals. The central frequencies of those signals are obtained by fast Fourier transform (FFT). The LMBF signal is utilized for human body temperature sensing. Measurement results demonstrate that the wearable optical fiber beat frequency digital monitoring system has a simple structure, high signal-to-noise ratio (SNR), stability, accuracy and muti-parameters sensing capability including respiration, heartbeat, pulse and human body temperature without mutual interference.

Real-time tree physiology monitoring system

Electronic devices have been developed to operate in real time with an alarm on the streets of Diptychs. The devices are IoT-platforms based on the ESP-32 microprocessor, equipped with a LoRa transceiver to transmit data to a module that collects tree data and sends it to the cloud using GSM/GPRS. Pilot implementation will take place in 2023 on the territory of the Botanical Garden of Petrozavodsk State University (Republic of Karelia, Russia). The work was carried out with the aim of studying the seasonal dynamics of Malus domestica under growing conditions in the extreme territories of Northern Russia. The research results show that on May 16-18, during the characteristic phenological phase «The beginning of reddening of leaves» (ВВСН 11) at an average daily air temperature of +5.7°C, a sum of temperatures of 487°C and an average daily temperature of 325°C. The phenophase «Beginning of flowering» (ВВСН 61) was noted on May 28 at an air temperature of +13.3 °C. The phenophase «Beginning of fruit ripening» (ВВСН 81-86) was noted on August 16. The beginning of the increase in trunk diameter, according to the distant number, was noted on June 15-20, the growth lasted until July 20-25 and amounted to about 3 mm. The research results showed that the species Malus Domestica may be preferable for introduction into the culture of northern fruit growing.