Human Vital Signs Research Articles

Research on Intelligent Monitoring and Protection Equipment of Vital Signs of Underground Personnel in Coal Mines: Review.

The coal industry is a high risk, high difficulty industry, and the annual global mine accident rate is high, so the safety of coal mine underground operations has been a concern. With the development of technology, the application of intelligent security technology in coal mine safety has broad prospects. In this paper, the research progress of vital signs monitoring and support equipment for underground personnel in coal mines is reviewed. The two main methods to ensure the safety of miners are discussed. They consist of directly monitoring human vital signs through portable devices such as smart helmets and smartwatches and indirectly monitoring underground environmental parameters. In addition, the application of information technology, sensor technology and artificial intelligence in vital signs monitoring is briefly discussed, and some future research directions are proposed. For example, through big data and artificial intelligence technology, vital signs data can be compared with historical data, individual health trends and potential risks can be analyzed, and we can provide personalized health management programs for miners. These technologies not only improve the safety of underground coal mine operation, but also provide an important guarantee for the realization of intelligent and safe coal mine production.

An innovative approach for FMCW radar vital sign monitoring with removal of respiratory harmonics

Frequency Modulated Continuous Wave (FMCW) radar shows broad research potential in monitoring vital signs. However, the harmonic components generated by the human respiratory process overlap with the frequency band of the heartbeat signal, posing challenges to precisely monitoring the heartbeat signal. To address this issue, this paper introduces the singular spectrum analysis method, which accurately identifies and removes respiratory harmonics by adding a sine signal with the same frequency as the respiratory harmonics to the original time series. Furthermore, the paper introduces energy entropy and the Pearson correlation coefficient to comprehensively decompose physiological signals to optimize the traditional variational mode decomposition algorithm, proposing the EE-VMD and PCC-VMD algorithms. Experimental results demonstrate that the SNR increased, and the accuracy of measuring respiratory rate and heartbeat rate has significantly improved. The results presented in this paper not only advance theoretical methodologies for the monitoring of human vital signs but also underscore the practical applicability of FMCW radar in this domain.

Synergistic fusion of mechanotransduction and power supplying functions towards highly compact and fully self-powered smart wearables

Current smart wearables typically necessitate three key elements including sensing units, signal processing circuits, and power supplying units, leading to complex system configuration, large system volume, and high power consumption. Here, we bypass this canonical form by developing a new device modality with both mechanotransduction and power supplying (MPS) functions, which enables to facilely construct highly compact and fully self-powered smart wearables with much improved energy efficiency. The MPS devices are engineered by synergistic fusion of an all-solid-state power supplying unit with an associated passive mechanotransduction element, resulting in a monolithic, compact, and versatile device modality. More imporatantly, the mechanotransduction and power supplying functions can work independently from each other, allowing the MPS devices to continuously monitor external mechanical stimulations and, simultaneously, to provide stable power for external circuitry. As demonstrations, fully isolated, autonomous, and self-powered smart wearables with much reduced power consumption (≈48 % less than conventional systems) can be facilely constructed just by connecting an MPS device to a custom-designed circuit for wireless monitoring and on-site analysis of diverse human vital signals. This study provides a new design philosophy and methodology to create smart wearables with reduced system complexity, improved energy efficiency, and enhanced deployment convenience.

Radar-based contactless heart beat detection with a modified Pan–Tompkins algorithm

Background.Using radar for non-contact measuring human vital signs has garnered significant attention due to its undeniable benefits. However, achieving reasonably good accuracy in contactless measurement senarios is still a technical challenge.Materials and methods.The proposed method includes two stages. The first stage involves the process of datasegmentation and signal channel selection. In the next phase, the raw radar signal from the chosen channel is subjected to modified Pan-Tompkins.Results.The experimental findings from twelve individuals demonstrated a strong agreement between the contactless radar and contact electrocardiography (ECG) devices for heart rate measurement, with correlation coefficient of 98.74 percentage; and the 95% limits of agreement obtained by radar and those obtained by ECG were 2.4 beats per minute.Conclusion.The results showed high agreement between heart rate calculated by radar signals and heart rate by electrocardiograph. This research paves the way for future applications using non-contact sensors to support and potentially replace contact sensors in healthcare.

Antenna Comparison of Different Antennas in Through-Wall Radar Human Vital Signs Recognition

Abstract Through wall radar (TWR) is an essential technology in the post-disaster rescue of buried individuals. The human vital signs analysis of breathing, heartbeat, and other periodic motions is the information used to identify and classify the human target. In the TWR system, selecting a suitable antenna and processing weak signals due to wall clutter and weak human vital signals is essential. In this abstract, we compare the performance of different antennas in TWR human vital feature recognition. We introduce a threshold pixel-connectivity signal processing method to locate the human body efficiently and accurately and extract the human respiratory frequency. The conclusion is that the Horn antenna has strong directionality, radiation energy, and a high resolution for recognizing the vital features of stationary human targets.

An image enhancement based method for improving rPPG extraction under low-light illumination

Remote photoplethysmography (rPPG) has gained significant attention as a non-invasive approach for measuring human vital signs from videos. However, the reliance on capturing the reflection of ambient lighting causes it to be susceptible to the adverse effects of low illumination levels, leading to deterioration in the signal quality. The preliminary study introduces a novel methodology for enhancing rPPG signal extraction in low-light conditions through the integration of an Image Enhancement Model (IEM) inspired by Retinex theory, which significantly improved signal quality by preprocessing video frames to better capture the subtle changes in facial blood flow. Recognizing the challenge posed by the generalization capacity over different deep-learning models and unseen examples from various datasets, this study further evaluated the efficacy of the IEM + rPPG extraction model across multiple datasets (UBFC-rPPG, BH-rPPG, MMPD-rPPG, and VIPL-HR) by integrating IEM with existing deep-learning based rPPG extraction models including DeepPhys, PhysNet, and PhysFormer and traditional POS rPPG extraction method. Our experiments demonstrate a consistent improvement for all the methods in heart rate estimation accuracy across all datasets, underscoring the IEM’s adaptability and effectiveness. The paper also explores the application of our method to traditional rPPG extraction techniques, further validating its potential for broader usage. Through comprehensive analysis, this research not only confirms the impact of lighting conditions on rPPG signal quality but also provides a robust solution for more reliable non-invasive vital sign monitoring in diverse environments.

Nanocomposite Multimodal Sensor Array Integrated with Auxetic Structure for an Intelligent Biometrics System.

A multimodal sensor array, combining pressure and proximity sensing, has attracted considerable interest due to its importance in ubiquitous monitoring of cardiopulmonary health- and sleep-related biometrics. However, the sensitivity and dynamic range of prevalent sensors are often insufficient to detect subtle body signals. This study introduces a novel capacitive nanocomposite proximity-pressure sensor (NPPS) for detecting multiple human biometrics. NPPS consists of a carbon nanotube-paper composite (CPC) electrode and a percolating multiwalled carbon nanotube (MWCNT) foam enclosed in a MWCNT-coated auxetic frame. The fractured fibers in the CPC electrode intensify an electric field, enabling highly sensitive detection of proximity and pressure. When pressure is applied to the sensor, the synergic effect of MWCNT foam and auxetic deformation amplifies the sensitivity. The simple and mass-producible fabrication protocol allows for building an array of highly sensitive sensors to monitor human presence, sleep posture, and vital signs, including ballistocardiography (BCG). With the aid of a machine learning algorithm, the sensor array accurately detects blood pressure (BP) without intervention. This advancement holds promise for unrestricted vital sign monitoring during sleep or driving.

Skin‐Inspired High‐Performance E‐Skin With Interlocked Microridges for Intelligent Perception

AbstractElectronic skin is increasingly receiving tremendous attention for its potential applications in medical rehabilitation and human‐machine interaction. However, the trade‐off between detection range and sensitivity of e‐skin has not been well addressed, although various strategies have been proposed. Interlocked microridges between the epidermis and dermis can effectively transfer stress to mechanoreceptors, allowing human skin to exhibit excellent sensitivity even upon both subtle and large external stimuli. Herein, inspired by human skin, a novel bionic e‐skin is developed in which interlocked microridges are introduced between the sensitive layer and interdigitated electrode. Thanks to the interlocked microridges, excellent compression capability and remarkable change of contact area between sensitive layer and interdigitated electrode can be achieved and the e‐skin exhibits an ultrahigh sensitivity (≈1502.5 kPa−1), excellent durability (10 000 cycles), a short response time (10 ms) as well as a wide detection range (≈160 kPa). Moreover, due to the effective transmission of external stress from a sensitive layer to an interdigitated electrode, such bionic e‐skin has ability to detect a wide range of human vital signs and vibrations caused by sound waves. Such facile preparation of bionic interlocked microridges opens a new pathway to achieve high‐performance e‐skins and extend their application prospects in future wearable intelligent systems.

Enhancing frost-resistant and electrically conductive properties of bacterial cellulose-based IPN hydrogel wound dressings via photopolymerization: Towards epidermal sensor applications

Conventional wound dressings are limited in their application due to the difficulty of maintaining normal use in cold conditions and a lack of functionality. In this study, photopolymerization was employed to fabricate a wound dressing with the capacity to monitor vital signs in cold environments. Utilizing bacterial cellulose (BC) to form an Interpenetrating Network (IPN) structure, the dressing exhibits enhanced water retention and mechanical properties, with a notable increase in mechanical strength to 540.37 KPa. Moreover, it maintains excellent mechanical resilience and electrical conductivity (9.01 × 10−3 S/cm) even at temperatures as low as −20 ℃. Incorporation of positively charged quaternary ammonium salts imparts potent antibacterial properties to the hydrogel against Staphylococcus aureus and Escherichia coli by electrostatically adsorbing to and disrupting negatively charged bacterial cell membranes, resulting in the leakage of internal fluids. The efficacy of the hydrogel in promoting wound healing was validated through rat-infected wound models. Hematoxylin and eosin (H&E) staining confirmed a reduction in inflammation at the wound site, improved wound healing, and a marked increase in the wound healing rate. Moreover, the hydrogel has remarkable electrical conductivity (1.25 × 10−2 S/cm), enabling the detection of subtle signals (e.g., strain 0.25 %) crucial for emergency wound management to prevent infections. Of significant importance, these hydrogels can function as electrodes for monitoring electrocardiogram (ECG) signals and respiratory status, facilitating timely assessment of vital signs in casualties. This innovative hydrogel wound dressing holds promise for simultaneously monitoring human vital signs and treating wounds in cold outdoor settings, thus offering broad applications in the realms of wound management and dressing for cold outdoor sports.

Cutting-Edge Microwave Sensors for Vital Signs Detection and Precise Human Lung Water Level Measurement

In this article, a comprehensive review is presented of recent technological advancements utilizing electromagnetic sensors in the microwave range for detecting human vital signs and lung water levels. With the main objective of improving detection accuracy and system robustness, numerous advancements in front-end architecture, detection techniques, and system-level integration have been reported. The benefits of non-contact vital sign detection have garnered significant interest across a range of applications, including healthcare monitoring and search and rescue operations. Moreover, some integrated circuits and portable systems have lately been shown off. A comparative examination of various system architectures, baseband signal processing methods, system-level integration strategies, and possible applications are included in this article. Going forward, researchers will continue to focus on integrating radar chips to achieve compact form factors and employ advanced signal processing methods to further enhance detection accuracy.

Flexible Arc-Shaped Micro-Fiber Bragg Grating Array Three-Dimensional Tactile Sensor for Fingertip Signals Detection and Human Pulse Monitoring.

A flexible arc-shaped micro-Fiber Bragg Grating (mFBG) array three-dimensional tactile sensor for fingertip signal detection and human pulse monitoring is presented. It is based on a three mFBGs array which is embedded in an arc-shaped poly (dimethylsiloxane) (PDMS) elastomer, which can effectively discriminate the normal force, left force, and right force by monitoring the reflected intensity variation of the three mFBGs. Different from the traditional FBG sensors, this sensor measures force by detecting changes in light intensity, effectively avoiding the wavelength cross-sensitivity impact of temperature variations on the sensor performance. This design strategy simplifies the sensor structure, reduces the system complexity and signal interrogation cost, and enhances reliability and practicality. Through systematic experiments, we successfully validated the sensor's superior performance, achieving a minimum detection force of 0.01 N and providing robust data support for practical applications. In addition, the sensor has been used to monitor human pulse accurately. The successful fabrication and experimental validation of this sensor lay a foundation for its widespread application in fields such as robot perception and human vital signal detection.

Human Vital Signs Signal Monitoring and Repairment with an Optical Fiber Sensor Based on Deep Learning

Optical fiber sensors have been widely applied for their advantages such as small size, lightweight, and strong electronic interference robustness. Compared with current electronic sensors, optical fiber sensors perform better in measuring parameters in harsh environments, which makes them suitable for more and more applications, such as target tracing and detection and monitoring of health signs in medical services. However, due to fiber optic sensor failure, improper transmission and storage, or other reasons, missing data occur from time to time. Therefore, effective missing value processing methods are desirable as they can be used to facilitate data processing or analysis. In the present study, gated recurrent unit (GRU) interpolation is performed by using the generative adversarial network (GAN) model to process the irregular delay relationship between the data before and after the collection of incomplete vital signs data. Furthermore, a data interpolation model based on VS-E2E-GAN is proposed to reconstruct vital signs signals. The ROC curve (AUC), metrics including mean squared error (MSE), and accuracy (ACC) of experiments reach 0.901, 0.777, and 0.908, respectively, which indicates that the proposed VS-E2E-GAN model performs well in terms of vital signs data imputation and repairment, has strong robustness when compared with other works, and has potential clinical application in health monitoring, smart home, and so on.

Development of Highly Flexible Piezoelectric PVDF-TRFE/Reduced Graphene Oxide Doped Electrospun Nano-Fibers for Self-Powered Pressure Sensor.

The demand for self-powered, flexible, and wearable electronic devices has been increasing in recent years for physiological and biomedical applications in real-time detection due to their higher flexibility and stretchability. This work fabricated a highly sensitive, self-powered wearable microdevice with Poly-Vinylidene Fluoride-Tetra Fluoroethylene (PVDF-TrFE) nano-fibers using an electrospinning technique. The dielectric response of the polymer was improved by incorporating the reduced-graphene-oxide (rGO) multi-walled carbon nano-tubes (MWCNTs) through doping. The dielectric behavior and piezoelectric effect were improved through the stretching and orientation of polymeric chains. The outermost layer was attained by chemical vapor deposition (CVD) of conductive polymer poly (3,4-ethylenedioxythiophene) to enhance the electrical conductivity and sensitivity. The hetero-structured nano-composite comprises PVDF-TrFE doped with rGO-MWCNTs over poly (3,4-ethylenedioxythiophene) (PEDOT), forming continuous self-assembly. The piezoelectric pressure sensor is capable of detecting human physiological vital signs. The pressure sensor exhibits a high-pressure sensitivity of 19.09 kPa-1, over a sensing range of 1.0 Pa to 25 kPa, and excellent cycling stability of 10,000 cycles. The study reveals that the piezoelectric pressure sensor has superior sensing performance and is capable of monitoring human vital signs, including heartbeat and wrist pulse, masticatory movement, voice recognition, and eye blinking signals. The research work demonstrates that the device could potentially eliminate metallic sensors and be used for early disease diagnosis in biomedical and personal healthcare applications.

Vital Sign Monitoring in Dynamic Environment via mmWave Radar and Camera Fusion

Contact-free vital sign monitoring, which uses wireless signals for recognizing human vital signs (i.e, breath and heartbeat), is an attractive solution to health and security. However, the subject's body movement and the change in actual environments can result in inaccurate frequency estimation of heartbeat and respiratory. In this paper, we propose a robust mmWave radar and camera fusion system for monitoring vital signs, which can perform consistently well in dynamic scenarios, e.g., when some people move around the subject to be tracked, or a subject waves his/her arms and marches on the spot. Three major processing modules are developed in the system, to enable robust sensing. Firstly, we utilize a camera to assist a mmWave radar to accurately localize the subjects of interest. Secondly, we exploit the calculated subject position to form transmitting and receiving beamformers, which can improve the reflected power from the targets and weaken the impact of dynamic interference. Thirdly, we propose a weighted multi-channel Variational Mode Decomposition (WMC-VMD) algorithm to separate the weak vital sign signals from the dynamic ones due to subject's body movement. Experimental results show that, the 90 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">${^{th}}$</tex-math></inline-formula> percentile errors in respiration rate (RR) and heartbeat rate (HR) are less than 0.5 RPM (respirations per minute) and 6 BPM (beats per minute), respectively.

DEMA: A Deep Learning-Enabled Model for Non-Invasive Human Vital Signs Monitoring Based on Optical Fiber Sensing.

Optical fiber sensors are extensively employed for their unique merits, such as small size, being lightweight, and having strong robustness to electronic interference. The above-mentioned sensors apply to more applications, especially the detection and monitoring of vital signs in medical or clinical. However, it is inconvenient for daily long-term human vital sign monitoring with conventional monitoring methods under the uncomfortable feelings generated since the skin and devices come into direct contact. This study introduces a non-invasive surveillance system that employs an optical fiber sensor and advanced deep-learning methodologies for precise vital sign readings. This system integrates a monitor based on the MZI (Mach-Zehnder interferometer) with LSTM networks, surpassing conventional approaches and providing potential uses in medical diagnostics. This could be potentially utilized in non-invasive health surveillance, evaluation, and intelligent health care.

Triboelectrically active hydrogel drives self-charging zinc-ion battery and human motion sensing

The fast advancement of flexible electronic technology hastens an ever-growing demand for power sources that are adaptable and flexible, and the arrival of innovative energy harvesting technologies such as triboelectric nanogenerator (TENG) further endow the potable electronics with versatility and sustainability. Herein, polyvinyl alcohol/ polyacrylamide/ zinc sulfate (PPZ) hydrogel was synthesized via an one-step UV-initiated polymerization. The hydrogel demonstrates exceptional tensile properties (with a large strain of 915 % and a corresponding tensile strength of 231 KPa), excellent electrical conductivity and light transmittance. A highly flexible and easily adaptable single-electrode TENG was thus fabricated on the base of the as-synthetized PPZ (PPZ-TENG), where the PPZ hydrogel functions as both the charging layer and current collector. While promoting a high electrical output performance of the PPZ-TENG (an open circuit voltage of 176 V and a power density of 328 mW/m2), the PPZ hydrogel also serves as an efficient ion-conductive electrolyte to construct highly flexible self-charging zinc ion batteries (ZIBs). Besides, highly sensitive strain response toward environmental stimuli was also demonstrated, which makes the integration strategy a promising solution for future development self-powered flexible wearable electronics toward the sustainable monitoring of human vital signs such as pulse and limb movement.

Statement of Retraction: Estimation of human vital signs and analysis of heart attack risk using EDENN

Statement of Retraction: Estimation of human vital signs and analysis of heart attack risk using EDENN

RETRACTED ARTICLE: Estimation of human vital signs and analysis of heart attack risk using EDENN

We, the Editors and Publisher of the International Journal of Healthcare Management, have retracted the following article: Priyanka Bibay Thakkar & R. H. Talwekar (30 Dec 2022): Estimation of human vital signs and analysis of heart attack risk using EDENN, International Journal of Healthcare Management, DOI: 10.1080/20479700.2022.2161150 Since publication, significant concerns have been raised about the integrity of the data and reported results in the article. When approached for an explanation, the authors did not provide their original data or any necessary supporting information. As verifying the validity of published work is core to the integrity of the scholarly record, we are therefore retracting the article. The corresponding author listed in this publication has been informed. We have been informed in our decision-making by our policy on publishing ethics and integrity and the COPE guidelines on retractions. The retracted article will remain online to maintain the scholarly record, but it will be digitally watermarked on each page as ‘Retracted’.

Time-Division Multiplexing MIMO Radar System With Self-Injection-Locking for Image Hotspot-Based Monitoring of Multiple Human Vital Signs

Time-Division Multiplexing MIMO Radar System With Self-Injection-Locking for Image Hotspot-Based Monitoring of Multiple Human Vital Signs

Contactless and short‐range vital signs detection with doppler radar millimetre‐wave (76–81 GHz) sensing firmware

AbstractVital signs such as heart rate (HR) and respiration rate (RR) are essential physiological parameters that are routinely used to monitor human health and bodily functions. They can be continuously monitored through contact or contactless measurements performed in the home or a hospital. In this study, a contactless Doppler radar W‐band sensing system was used for short‐range, contactless vital sign estimation. Frequency‐modulated continuous wave (FMCW) measurements were performed to reduce the influence of a patient's micromotion. Sensing software was developed that can process the received chirps to filter and extract heartbeat and breathing rhythm signals. The proposed contactless sensing system eliminates the need for the contact electrodes, electric patches, photoelectric sensors, and conductive wires used in typical physiological sensing methods. The system operates at 76–81 GHz in FMCW mode and can detect objects on the basis of changes in frequency and phase. The obtained signals are used to precisely monitor a patient's HR and RR with minimal noise interference. In a laboratory setting, the heartbeats and breathing rhythm signals of healthy young participants were measured, and their HR and RR were estimated through frequency‐ and time‐domain analyses. The experimental results confirmed the feasibility of the proposed W‐band mm‐wave radar for contactless and short‐range continuous detection of human vital signs.