Wearable Wireless Research Articles

A Wireless Wearable Sensor System Based on a Silver Nanowire‐Decorated Silicon Nanomembrane for Precise and Continuous Hazardous Gas Monitoring

AbstractWearable wireless gas sensors have attracted enormous interest due to precise, real‐time healthcare and environmental monitoring without temporal and spatial limitations. Among various toxic gases, detecting ammonia is crucial because of its highly hazardous nature and applicability as a noninvasive biomarker for diagnosing health conditions. In this study, silver nanowires‐decorated silicon nanomembrane (AgNW‐SiNM) chemiresistive gas sensor with high selectivity to ammonia is fully integrated with an ultrathin flexible Joule heater and wireless communication system to fabricate wearable wireless real‐time toxic gas monitoring system. The sensor exhibits improved performance to ammonia gas, attributed to heating‐induced changes in adsorption/desorption rates, along with electronic and chemical sensitization facilitated by AgNW decoration. The gas sensing system exhibits stable and high responses of ≈1.83, 1.47, and 1.19 on the ammonia exposure at concentrations of 10, 5, and 1 ppm even under mechanical deformations. The real‐time dynamic response of the sensor is wirelessly transmitted to portable electronics and displayed on the screen. Moreover, the system alerts the users in advance through the integrated haptic interface when exposed to dangerous gas environments for early evacuation. The system paves the way for timely warnings from hazardous gas and more accurate noninvasive medical diagnosis related to respiratory disorders.

MXene and Conducting Polymer Composites for Wearable Mask Sensors

Significant efforts have been dedicated to advancing wearable electronics, ranging from life-supporting gear for soldiers to trendy accessories like smartwatches. Miniature gas sensors integrated into wearable devices offer real-time atmospheric information, safeguarding individuals from potential health condition monitoring and early disease detection. For example, recent studies have focused on detecting COVID-19 through breath analysis, utilizing over 500 compounds in exhaled breath as biomarkers for disease and metabolic assessment. Of particular interest is CO2, a key greenhouse gas crucial for monitoring indoor air quality and respiratory health. Excessive indoor CO2 levels, primarily from human exhalation, elevate the risk of COVID-19 transmission via aerosols. Another example of a considerable gas species in exhaled breath can be ethanol, which could cause adverse effects such as nausea, vomiting, skin allergies, low blood pressure, low blood sugar, and Parkinson's disease, seriously threatening human health and safety driving. Various techniques, including optical spectroscopy and gas chromatography, have been employed for gas detection, but they often suffer from drawbacks like bulkiness and high cost. Therefore, there is a strong need for developing detection devices that are affordable, portable, and wearable. Conducting polymers (CPs) show promise in constructing flexible gas sensors, but their limited response to diverse gases necessitates exploring hybridization with other nanomaterials to enhance sensing capabilities.In this study, two kinds of conducting polymers, including polyaniline (PANI) and polypyrrole (Ppy) were synthesized in a composite form with Ti3C2Tx MXene and deposited into polypropylene fiber-based disposable masks. The PANI-MXene composite gas sensor displayed a wide detection range, reliable reproducibility, long-term stability, and excellent flexibility and selectivity, a remarkable response (15.2%) towards 500 ppm CO2 gas, which is 6.5 times higher than pristine Ti3C2Tx and 2.4 times higher than pristine PANI. When Ppy is hybridized with Ti3C2Tx, the as-fabricated composites exhibited a rapid response/recovery speed, a good sensing response of 76.3 % toward 400 ppm ethanol, and an admirable theoretical limit of detection of 2.21 ppm. The outstanding sensing characteristics of the composite sensor are attributed to the abundant functional groups (e.g., amino groups in conducting polymers, terminal groups in Ti3C2Tx) and the formation of the Schottky junction between Ti3C2Tx and conducting polymers. Furthermore, a wearable wireless Bluetooth sensing device was developed for human breath monitoring, showcasing the potential of these MXene-CP composite sensors for respiratory disease diagnosis [1, 2]. The proposed gas sensing mechanism of the CP-based composites is also discussed in detail.

High-Performance, flexible moist-electric generator for self-powered wearable wireless sensing

A moist-electric generator (MEG) extracts energy from the moisture in the environment and converts it into clean, usable electrical power, making it an ideal energy source for wearable electronic devices. However, the intricate manufacturing process, low power density, and inefficient energy output significantly impede its practical applications. Therefore, this study developed a flexible moist-electric generator (FMEG) with a simple structure and high output power for self-powered wearable wireless sensor systems. The FMEG adopts a sandwich structure consisting of Cu and Al as metal electrodes, with an ionic hydrogel film composed of polystyrene sulfonic acid (PSS)/ polyvinyl alcohol (PVA)/LiCl serving as the electrolyte layer. By designing a doubly asymmetric structure and introducing a metal-air reaction, a single FMEG can generate a long-term continuous voltage of 0.7 V and an output current density of 56.39 μA/cm2 at 90 % RH. The simple manufacturing process and sandwich structure design facilitate the low-cost scale integration of FMEG by series and parallel connection, thus increasing the overall power output and providing sufficient power for small wearable electronics. A self-powered wearable wireless sensing system based on FMEG was designed and developed for long-term wearable health monitoring by using integrated FMEGs as an energy device to harvest moisture energy from the environment and skin. The wearable wireless sensing device realizes the monitoring of the environment, heart rate, and human movement by integrating multifunctional sensors, and sends the data to the smart device by wireless transmission, which demonstrates the broad application prospect of FMEG in self-powered devices and wearable electronics fields.

Recent Advances in the Fabrication and Application of Electrochemical Paper-Based Analytical Devices.

In response to growing environmental concerns, the scientific community is increasingly incorporating green chemistry principles into modern analytical techniques. Electrochemical paper-based analytical devices (ePADs) have emerged as a sustainable and efficient alternative to conventional analytical devices, offering robust applications in point-of-care testing, personalized healthcare, environmental monitoring, and food safety. ePADs align with green chemistry by minimizing reagent use, reducing energy consumption, and being disposable, making them ideal for eco-friendly and cost-effective analyses. Their user-friendly interface, alongside sensitive and selective detection capabilities, has driven their popularity in recent years. This review traces the evolution of ePADs from simple designs to complex multilayered structures that optimize analyte flow and improve detection. It also delves into innovative electrode fabrication methods, assessing key advantages, limitations, and modification strategies for enhanced sensitivity. Application-focused sections explore recent advancements in using ePADs for detecting diseases, monitoring environmental hazards like heavy metals and bacterial contamination, and screening contaminants in food. The integration of cutting-edge technologies, such as wearable wireless devices and the Internet of Things (IoT), further positions ePADs at the forefront of point-of-care testing (POCT). Finally, the review identifies key research gaps and proposes future directions for the field.

The utility of wearable electroencephalography combined with behavioral measures to establish a practical multi-domain model for facilitating the diagnosis of young children with attention-deficit/hyperactivity disorder

BackgroundA multi-method, multi-informant approach is crucial for evaluating attention-deficit/hyperactivity disorders (ADHD) in preschool children due to the diagnostic complexities and challenges at this developmental stage. However, most artificial intelligence (AI) studies on the automated detection of ADHD have relied on using a single datatype. This study aims to develop a reliable multimodal AI-detection system to facilitate the diagnosis of ADHD in young children.Methods78 young children were recruited, including 43 diagnosed with ADHD (mean age: 68.07 ± 6.19 months) and 35 with typical development (mean age: 67.40 ± 5.44 months). Machine learning and deep learning methods were adopted to develop three individual predictive models using electroencephalography (EEG) data recorded with a wearable wireless device, scores from the computerized attention assessment via Conners’ Kiddie Continuous Performance Test Second Edition (K-CPT-2), and ratings from ADHD-related symptom scales. Finally, these models were combined to form a single ensemble model.ResultsThe ensemble model achieved an accuracy of 0.974. While individual modality provided the optimal classification with an accuracy rate of 0.909, 0.922, and 0.950 using the ADHD-related symptom rating scale, the K-CPT-2 score, and the EEG measure, respectively. Moreover, the findings suggest that teacher ratings, K-CPT-2 reaction time, and occipital high-frequency EEG band power values are significant features in identifying young children with ADHD.ConclusionsThis study addresses three common issues in ADHD-related AI research: the utility of wearable technologies, integrating databases from diverse ADHD diagnostic instruments, and appropriately interpreting the models. This established multimodal system is potentially reliable and practical for distinguishing ADHD from TD, thus further facilitating the clinical diagnosis of ADHD in preschool young children.

Copper Paste Printed Paper‐Based Dual‐Band Antenna for Wearable Wireless Electronics

AbstractWearable wireless electronics is becoming a significant research area because of the unique features of this technology. Within this field printed antennas are the key electrical component accomplishing the signal transmission and energy harvesting tasks and at the same these antennas need to be lightweight, environmentally friendly, safe to wear, and easy to conform. Currently, the majority of available paper‐based antennas are designed for RFID, sensing, UWB, WLAN, and medical applications, with just a few being utilized in wearable applications, particularly for wireless body area network (WBAN). Furthermore, few studies have been conducted on the usage of printable copper conductive materials and low‐temperature plasma technique for the fabrication of such antennas. This study demonstrates the realization of a dual‐band paper‐based wearable antenna by screen‐printing of a plasma‐sintered conductive copper paste. The copper paste, composed of 51 wt% solid particles, can easily produce desired conductive patterns on photo paper after printing and a subsequent plasma sintering, with a good adhesion. The antenna designed on photopaper operates in the frequency bands of 1.73–2.55 GHz and 7.66–8.89 GHz. Free‐space simulation and measurement results reveal that the antenna exhibits stable radiation performance in the targeted WBAN (2.4–2.4835 GHz) and X uplink (7.9–8.4 GHz) frequency bands, together with low profile, excellent conformality and acceptable SAR values on the body and no electronic waste formed after disposal, making it a competitive candidate for usage in wearable wireless electronics.

Self-powered flexible wearable wireless sensing for outdoor work heatstroke prevention and health monitoring

Outdoor workers are susceptible to heatstroke in hot weather. Currently, there are no wearable devices on the market to assess the risk of heatstroke. This paper proposes a self-powered flexible wearable wireless sensing system for outdoor work heatstroke prevention and health monitoring (SWSM). SWSM consists of two parts, one part is a wearable heatstroke prevention patch based on flexible wireless sensing (WPFS) to monitor the wearer’s physiological indicators continuously. The other part is a self-powered device based on solar energy (SPDS), which can generate milliamp level current for powering the WPFS. With these indicators, the wearer’s activity category is confirmed by the multi-layer perceptron (MLP) model. WPFS contains a PVDF-HFD nanofibre cooling film (PNCF), flexible triboelectric nanogenerator (TENG)-based button (B-TENG), and functional sensing components. Temperatures under PNCF coverage can be up to 12% lower than environmental temperatures. B-TENG is used to adjust the mode. Based on the wearer’s physiological indicators a heatstroke risk assessment equation can be created to assess the potential risk of heatstroke. Finally, the data is displayed on the Internet of Things (IoT) platform. The system is wireless, self-powered, flexible wearable, and can be used for real-time prevention of heatstroke risk and health monitoring of outdoor workers.

Implementation of Wearable Wireless Chest Patch Monitoring Terminal

A wearable wireless chest patch monitoring terminal is designed to realize the acquisition, processing, and wireless transmission of ECG, respiration, and body temperature signals. The analog front-end ADS1292R, which integrates respiratory impedance and ECG front-end, is utilized to collect human ECG and respiratory signals. The body temperature is collected using a low-power, high-precision digital temperature sensor MAX30208. A filter algorithm for signal processing and wireless transmission is designed through a low-power nRF52840 Bluetooth SoC with an Arm Cortex-M4F kernel. The experimental results show that the designed monitoring terminal can monitor the ECG, respiration, and body temperature parameters of the human body in real-time and send the monitoring results via Bluetooth, with a continuous working time of more than 13 hours. The wearable wireless chest patch monitoring terminal features good portability, long standby time, and high measurement accuracy, and it has promising application prospects in the fields of family health monitoring, mobile medical treatment, and smart healthcare.

Self-powered wearable remote control system based on self-adhesive, self-healing, and tough hydrogels

The advent of the fifth-generation mobile communication network era induces a great potential for the design and development of self-powered wearable electronic devices. Hydrogels, as a typical material for flexible electrodes, have been widely employed in self-powered wearable electronic devices. However, the hydrogel-based triboelectric nanogenerator (H-TENG) is usually compromised by the challenges in data collection, operational stability, and manufacturability due to the unstable combination between the friction layer and the electrode layer, the occurrence of hydrogel damage during prolonged operation, and also the difficulty of machining sticky hydrogel electrodes. In the present study, a composite hydrogel composed of acrylamide, crotonyl alcohol, and 4-carboxyphenylboronic acid was synthesized via ultraviolet crosslinking, which was specially developed for H-TENG and wearable wireless remote control interface, featuring with excellent stretchability and mechanical strength as well as self-healing and self-adhesive properties. The open-circuit voltage of the H-TENG prepared with the hydrogel reached up to 165 V, and the output voltage remained almost unchanged following 10,000 cycles of compression test. Additionally, a wearable wireless remote control system was designed that could accurately control the multiple appliances and adjust different working modes using the H-TENG. Consequently, the development of the H-TENG and wearable wireless remote control system has the potential to provide a new methodology for the application of next-generation wearable devices in various areas, such as smart homes, as a representative example.

An Enhancement for Wireless Body Area Network Using Adaptive Algorithms

Wireless Body Area Networks (WBANs) are one of the most critical technologies for maintaining constant monitoring of patient’s health and diagnosing diseases. They consist of small, wearable wireless sensors transmitting signals. Within this vision, WBANs are not without unique difficulties, for instance, high energy consumption, heat from the sensor, and impaired data accuracy. This paper introduces adaptive algorithms combining Convolutional Neural Networks (CNNs) and dynamic threshold mechanisms to enhance the performance and energy efficiency of Wireless Body Area Networks. The study utilizes the MIB-BIH Arrhythmias dataset to improve the detection of arrhythmias. The results show a 10.53% improvement in battery life and a 5.62-fold enhancement in temperature management when sleep mode technology is applied. As a result, the model reached the average accuracy of ECG classification of 98% and a high level of selectivity and sensitivity to a normal type of heartbeat and quite satisfactory results in the classification of arrhythmia type of heartbeat.

Astrosense – a Printed Wearalbe Electrochemical Sensor for Monitoring Cortisol in Sweat during Human Spaceflight

The In Space Manufacturing of sensors and electronics can directly addresses the logistic challenge for long-duration human spaceflight missions by reducing mission logistics mass, increase reliability, mitigate risk, while also offering a high degree of customization and tailorability. This manufacturing approach relies on additive manufacturing technologies, due to its versatility, low power consumption, automation, fast manufacturing time with low waste generation, and ability to print a variety of materials. To ensure the health and safety of crew members, developing human health portable diagnostic tools that can be manufactured during long duration missions is necessary to ensure that the crew members are monitored in real time so that countermeasures can be deployed as soon as possible. Here we report the development of Astrosense (Figure 1), a wearable wireless and fully printed platform that integrates several sensors, including, electrochemical sensor for the detection of cortisol in sweat, temperature, CO2 and humidity sensors, as well as, the required hardware required to control each individual sensor.Astrosense consists of two sections, a reusable, and a disposable section. The reusable section contains the CO2,temperature, humidity sensor, the potentiostat that controls the cortisol sensor and the printed antennas for data transmission. The cortisol sensor, sweat harvest component and printed batteries will be located on the disposable section of Astrosense, so that they can be easily replaced once the sensor is either saturated, degraded or when the batteries need to be replaced. The disposable section will interfase with the reusable section of Astrosense through several medical grade adhesives and pogo pins. This allows for the easy replacement of the cortisol sensor as well as mounting and dismounting of the device on the human skin. Figure 1

Curvature-Adaptive Compact Triple-Band Metamaterial Uniplanar Compact Electromagnetic Bandgap-Based Printed Antenna for Wearable Wireless and Medical Body Area Network Applications

A novel, compact, monopole apple-shaped, triple-band metamaterial-printed wearable antenna backed by a uniplanar compact electromagnetic bandgap (UC-EBG) structure is introduced in this paper for wearable wireless and medical body area network (WBAN/MBAN) applications. A tri-band UC-EBG structure has been utilized as a ground plane to minimize the impact of antenna radiation on the human body and improve antenna performance for the proposed wearable antenna. Metamaterial triangular complementary split ring resonators (TCSRRs) are incorporated into the antenna and UC-EBG structure, resulting in a compact UC-EBG-backed antenna with an overall size of 39 × 39 × 2.84 mm3 (0.41 λg × 0.41 λg × 0.029 λg). The printed textile antenna operates at 2.45 GHz for the wireless local area network (WLAN), 3.5 GHz for 5G new radio (NR), and 5.8 GHz for the industrial, scientific, and medical (ISM) bands with improved gain and high-efficiency values. Furthermore, the performance of the antenna is analyzed on the human body, where three models of curved body parts are considered: a child’s arm (worst case) with a 40 mm radius, an adult’s arm with a 60 mm radius, and an adult’s leg with a 70 mm radius. The results demonstrate that the proposed antenna is an attractive candidate for wearable healthcare and fitness monitoring devices and other WBAN/MBAN applications due to its compact size, high performance, and low SAR values.

Outdoor Sports Data Monitoring Scheme Based on Wearable Devices and Wireless Sensor Networks (WSNs)

Outdoor Sports Data Monitoring Scheme Based on Wearable Devices and Wireless Sensor Networks (WSNs)

Machine Learning-Based Fatigue Level Prediction for Exoskeleton-Assisted Trunk Flexion Tasks Using Wearable Sensors

Monitoring physical demands during task execution with exoskeletons can be instrumental in understanding their suitability for industrial tasks. This study aimed at developing a fatigue level prediction model for Back-Support Industrial Exoskeletons (BSIEs) using wearable sensors. Fourteen participants performed a set of intermittent trunk-flexion task cycles consisting of static, sustained, and dynamic activities, until they reached medium-high fatigue levels, while wearing BSIEs. Three classification algorithms, Support Vector Machine (SVM), Random Forest (RF), and XGBoost (XGB), were implemented to predict perceived fatigue level in the back and leg regions using features from four wearable wireless Electromyography (EMG) sensors with integrated Inertial Measurement Units (IMUs). We examined the best grouping and sensor combinations by comparing prediction performance. The findings showed best performance in binary classification of leg and back fatigue with 95% (2 EMG + IMU sensors) and 82% (single IMU sensor) accuracy, respectively. Tertiary classification for back and leg fatigue level prediction required four sensor setups with both EMG and IMU measures to perform at 79% and 67% accuracy, respectively. The efforts presented in our article demonstrate the feasibility of an accessible fatigue level detection system, which can be beneficial for objective fatigue assessment, design selection, and implementation of BSIEs in real-world scenarios.

D23. A Wearable Wireless Device Monitors Sacral Pressure during Operative Cases

D23. A Wearable Wireless Device Monitors Sacral Pressure during Operative Cases

IOT Based Remote Patient Monitoring System

Abstract: A remote monitoring technique that can accurately track human physiological indicators has applications in virtual reality, sports science, medicine, rehabilitation, and surveillance. The majority of systems now in use for tracking bodily parameters in humans need wiring that limits natural movement. In order to get over this restriction, a wearable wireless sensor network that monitors physiological human body characteristics has been built using an accelerometer, a pulse oximeter, a heart-rate sensor, a temperature sensor, and a galvanic skin response sensor. The individual is being tracked wirelessly using his own location. It would be simple to modify this system to watch athletes and young children. Unlike a tethered monitoring equipment, the wireless feature allows the human body to move freely, making the system genuinely portable, quick, and dependable. The portable and the designed sensor node's small size makes it simple to attach to the body.

An examination of wearable technology in the field biomedical engineering: A review

A wearable device is a piece of technology that can be worn on the body, designed to be portable, lightweight and equipped with various sensors or features for specific functions. As a game-changer in the field of biomedical engineering, wearable technology provides innovative approaches to illness management, individualized healthcare and health monitoring. This review looks at wearable technology as it stands in the field of biomedical engineering, emphasizing its uses, difficulties and potential. The research examines a wide variety of wearable wireless biosensors, sensor patches, wristwatches, wearable face masks and multi-sensor smart clothing, emphasizing their potential to measure physiological parameters, including blood pressure, heart rate and sleep patterns. This study demonstrates the need for intelligent wearable devices for high-quality signal capture, processing and continuous monitoring of critical parameters. The creation of smart wearables that meet the specified design standards enables the creator of a wearable with reduced power consumption that can be used to monitor the health of patients. This study offers a thorough analysis of wearable technology's present state, obstacles and potential applications in the field of biomedical engineering. It will be of great use to investigators, medical professionals and developers of technology.

Continual Monitoring of Respiratory Disorders to Enhance Therapy via Real-Time Lung Sound Imaging in Telemedicine

This work presents a configurable Internet of Things architecture for acoustical sensing and analysis for frequent remote respiratory assessments. The proposed system creates a foundation for enabling real-time therapy and patient feedback adjustment in a telemedicine setting. By allowing continuous remote respiratory monitoring, the system has the potential to give clinicians access to assessments from which they could make decisions about modifying therapy in real-time and communicate changes directly to patients. The system comprises a wearable wireless microphone array interfaced with a programmable microcontroller with embedded signal conditioning. Experiments on the phantom model were conducted to demonstrate the feasibility of reconstructing acoustic lung images for detecting obstructions in the airway and provided controlled validation of noise resilience and imaging capabilities. An optimized denoising technique and design innovations provided 7 dB more SNR and 7% more imaging accuracy for the proposed system, benchmarked against digital stethoscopes. While further clinical studies are warranted, initial results suggest potential benefits over single-point digital stethoscopes for internet-enabled remote lung monitoring needing noise immunity and regional specificity. The flexible architecture aims to bridge critical technical gaps in frequent and connected respiratory function at home or in busy clinical settings challenged by ambient noise interference.

Developing a Novel Prosthetic Hand with Wireless Wearable Sensor Technology Based on User Perspectives: A Pilot Study.

Myoelectric hands are beneficial tools in the daily activities of people with upper-limb deficiencies. Because traditional myoelectric hands rely on detecting muscle activity in residual limbs, they are not suitable for individuals with short stumps or paralyzed limbs. Therefore, we developed a novel electric prosthetic hand that functions without myoelectricity, utilizing wearable wireless sensor technology for control. As a preliminary evaluation, our prototype hand with wireless button sensors was compared with a conventional myoelectric hand (Ottobock). Ten healthy therapists were enrolled in this study. The hands were fixed to their forearms, myoelectric hand muscle activity sensors were attached to the wrist extensor and flexor muscles, and wireless button sensors for the prostheses were attached to each user's trunk. Clinical evaluations were performed using the Simple Test for Evaluating Hand Function and the Action Research Arm Test. The fatigue degree was evaluated using the modified Borg scale before and after the tests. While no statistically significant differences were observed between the two hands across the tests, the change in the Borg scale was notably smaller for our prosthetic hand (p = 0.045). Compared with the Ottobock hand, the proposed hand prosthesis has potential for widespread applications in people with upper-limb deficiencies.

Wearable wireless continuous vital signs monitoring on the general ward.

Wearable wireless sensors for continuous vital signs monitoring (CVSM) offer the potential for early identification of patient deterioration, especially in low-intensity care settings like general wards. This study aims to review advances in wearable CVSM - with a focus on the general ward - highlighting the technological characteristics of CVSM systems, user perspectives and impact on patient outcomes by exploring recent evidence. The accuracy of wearable sensors measuring vital signs exhibits variability, especially notable in ambulatory patients within hospital settings, and standard validation protocols are lacking. Usability of CMVS systems is critical for nurses and patients, highlighting the need for easy-to-use wearable sensors, and expansion of the number of measured vital signs. Current software systems lack integration with hospital IT infrastructures and workflow automation. Imperative enhancements involve nurse-friendly, less intrusive alarm strategies, and advanced decision support systems. Despite observed reductions in ICU admissions and Rapid Response Team calls, the impact on patient outcomes lacks robust statistical significance. Widespread implementation of CVSM systems on the general ward and potentially outside the hospital seems inevitable. Despite the theoretical benefits of CVSM systems in improving clinical outcomes, and supporting nursing care by optimizing clinical workflow efficiency, the demonstrated effects in clinical practice are mixed. This review highlights the existing challenges related to data quality, usability, implementation, integration, interpretation, and user perspectives, as well as the need for robust evidence to support their impact on patient outcomes, workflow and cost-effectiveness.