Wireless Wearable Device Research Articles

Ultra-low cost and high-performance paper-based flexible pressure sensor for artificial intelligent E-skin

E-skin driven by artificial intelligence algorithms enables the innovation of future technologies such as IoT, intelligent manufacturing, health monitoring and human–machine interfaces for VR/AR. Although many flexible pressure sensors have been reported, the development of sensors that combine low-cost and high performance remains a huge challenge. Herein, we propose an all-paper-based pressure sensor with water-soluble graphite functional layer and carbon interdigital electrodes obtained by friction coating and screen printing, respectively. The sensor boasts a rectangular design measuring 1 cm × 2.15 cm, with a remarkably thin profile of only 71 μm and an ultra-light weight of 6 mg, and the cost of a single sensor is extremely low. Specifically, the sensor achieved a lower detection limit of 0.98 Pa and an upper detection limit of 2000 kPa, which represents a new benchmark among paper-based pressure sensors. It demonstrated high sensitivity across various pressure ranges: 319.94 kPa−1 (0–1 kPa), 97.63 kPa−1 (1–40 kPa), 18.75 kPa−1 (40–200 kPa), and 2.72 kPa−1 (200–2000 kPa). The sensor also exhibited a rapid response and recovery time of 8 ms and 9 ms, respectively, along with excellent durability (>20,000 fatigue tests, 10,000 cycles at 2 kPa and 10,000 cycles at 100 kPa) and high pressure stability. Furthermore, the eco-friendly sensor can identify eight surface textures with a recognition accuracy of 98.33% after training with a 2D convolutional neural network (2D CNN). Finally, a portable wireless wearable device with dimensions of 38 mm × 26 mm × 14 mm and a weight of only 11.265 g has been developed for pressure recognition, breathing, pulse, and heartbeat detection.

Three Years of Continuous Vital Signs Monitoring on the General Surgical Ward: Is It Sustainable? A Qualitative Study.

Continuous monitoring of vital signs using a wireless wearable device was implemented in 2018 at a surgical care unit of an academic hospital. This study aimed at gaining insight into nurses' and patients' perspectives regarding the use and innovation of a continuous vital signs monitoring system, three years after its introduction. This qualitative study was performed in a surgical, non-intensive care unit of an academic hospital in 2021. Key-user nurses (nurses with additional training and expertise with the device) and patients were selected for semi-structured interviews, and nurses from the ward were selected for a focus group interview using a topic list. Transcripts of the audio tapes were deductively analysed using four dimensions for adoptions of information and communication technologies (ICT) devices in healthcare. The device provided feelings of safety for nurses and patients. Nurses and patients had a few issues with the device, including the size and the battery life. Nurses gained knowledge and skills in using the system for measurement and interpretations. They perceived the system as a tool to improve the recognition of clinical decline. The use of the system could be further developed regarding the technical device's characteristics, nurses' interpretation of the data and the of type of alarms, the information needs of patients, and clarification of the definition and standardization of continuous monitoring. Three years after the introduction, wireless continuous vital signs monitoring is the new standard of care according to the end-users at the general surgical ward.

Satellite-Linked Remote Physiologic Monitoring During Simulated Rural Ground Ambulance and Rotor Wing Transports

Telemedicine and remote monitoring are rapidly gaining momentum in health care, including in-home and postdischarge monitoring. However, remote monitoring for telemedicine teams and receiving medical centers is yet to reach emergency medical services. When transporting a critically ill patient, continuous vital sign monitoring may be helpful to enhance receiving center collaboration and change care delivery before arrival when necessary. Our primary objective was to demonstrate successful transmission and reception of real-time physiologic summary data to a hospital base station during ambulance transport using a low-energy Bluetooth wireless wearable device linked to iridium satellite communications. We completed our proof-of-concept study on 2 simulated ground ambulance transports and 1 helicopter flight in rural areas surrounding Rochester, Minnesota. Each simulated transport used Mayo Clinic–developed wearable devices paired one-to-one with a physiologic communication kit. Electrocardiographic and photoplethysmographic waveforms were processed on the wearables every 5 minutes, with vital sign data generated and transmitted to an iridium satellite and relayed to a base station network–protected computer and mobile application with real-time display of summary and location. Data and geolocation were tracked in real time with a mobile application during the simulated transport, and summary data packets were saved on Mayo Clinic servers. During the 3 simulated rural transports, all (n=7; 100%) wearables successfully captured, recorded, and transmitted raw waveform physiologic signals. All devices transmitted successfully via the iridium satellite to the base station network–protected computer and mobile application. In all, 106 (69%) of 154 transmissions were successfully processed. Our project demonstrated successful remote monitoring of physiologic vital signs during transport in rural, low–cellular signal areas. The use of live remote monitoring should be explored to understand its utility in practice and outcomes.

Effects of hydromorphone-based intravenous patient-controlled analgesia with and without a low basal infusion on postoperative hypoxaemia: study protocol for a randomised controlled clinical trial

IntroductionWhen patients receive patient-controlled intravenous analgesia (PCIA), no basal infusion is always recommended, as the addition of a basal infusion increases the occurrence of postoperative opioid-induced respiratory depression. However, few...

Advantage of Vital Sign Monitoring Using a Wireless Wearable Device for Predicting Septic Shock in Febrile Patients in the Emergency Department: A Machine Learning-Based Analysis.

Intermittent manual measurement of vital signs may not rapidly predict sepsis development in febrile patients admitted to the emergency department (ED). We aimed to evaluate the predictive performance of a wireless monitoring device that continuously measures heart rate (HR) and respiratory rate (RR) and a machine learning analysis in febrile but stable patients in the ED. We analysed 468 patients (age, ≥18 years; training set, n = 277; validation set, n = 93; test set, n = 98) having fever (temperature >38 °C) and admitted to the isolation care unit of the ED. The AUROC of the fragmented model with device data was 0.858 (95% confidence interval [CI], 0.809–0.908), and that with manual data was 0.841 (95% CI, 0.789–0.893). The AUROC of the accumulated model with device data was 0.861 (95% CI, 0.811–0.910), and that with manual data was 0.853 (95% CI, 0.803–0.903). Fragmented and accumulated models with device data detected clinical deterioration in febrile patients at risk of septic shock 9 h and 5 h 30 min earlier, respectively, than those with manual data. Continuous vital sign monitoring using a wearable device could accurately predict clinical deterioration and reduce the time to recognise potential clinical deterioration in stable ED patients with fever.

Driver vigilance detection for high-speed rail using fusion of multiple physiological signals and deep learning

With the popularity of high-speed rail in China and with faster operation speeds, the safety of railways has also received more attention. This paper proposes a vigilance detection method for high-speed rail drivers based on wireless wearable multi-physiological signals fusion and deep learning. The intended method consists of three components: wireless wearable signal acquisition equipment, physiological signal preprocessing and driver vigilance detection. In the initial stage, a wireless wearable device based on open source brain–computer interfaces was used to collect electroencephalogram, electrocardiogram and electromyogram signals in the high-speed rail simulation environment. Secondly, linear filtering, fast independent component analysis and wavelet filtering are performed on the three kinds of signals, and reasonable slicing is performed to make a dataset. Finally, a convolutional recurrent neural network with channel attention mechanism and memory ability is proposed. Multiple physiological signals from wireless wearable devices are used to train the network. This network improves the ability to recognize the vigilance of drivers and verifies the effectiveness of the combination of squeeze-and-excitation block and long short-term memory with convolutional neural network. Furthermore, the vigilance detection effectiveness was evaluated under different signal combinations; the testing set verified the accuracy of the network as 98.11%. Results prove the feasibility of the high-speed rail driver vigilance detection method based on multiple physiological signals and deep learning, which can help to avoid high-speed rail accidents.

Self-powered and multi-mode flexible sensing film with patterned conductive network for wireless monitoring in healthcare

The flexible and multi-functional strain sensors have attracted extensive research attention due to their promising applications in various wearable electronics. However, it remains a huge challenge to design and fabricate the self-powered flexible sensing micro-system based on a single multifunctional material to relieve the dependence on external rigid and heavy battery. Herein, a self-powered and multi-mode flexible sensing system integrated with triboelectric nanogenerator (TENG), flexible solid-state supercapacitors (FSSC) and strain sensor is developed based on thermoplastic polyurethane film with asymmetric and cross conductive networks through a facile screen printing process. The unique conductive network endows the prepared strain sensor with an independent anisotropic response to the strain applied in different directions. The TENG in single-electrode mode is presented to generate electricity from ubiquitously bio-mechanical energy and stored it in the FSSC immediately, realizing continuous green power supply for the sensor. As proof-of-concept, an all-in-one smart device consisting of energy supply and sensing module is constructed, demonstrating the great convenience and feasibility for practical application in sustainable wearable electronics. Benefiting from the excellent comprehensive sensing performance, the wireless wearable device assembled by the prepared sensor exhibits excellent detection and recognition for various human motion, expressions, phonation, and physiological signal, revealing the broad potential applications in rehabilitation training, human-machine interaction and medical diagnosis. This work proposes an innovative and scalable approach to manufacture multifunctional micro-systems, which will bring new vitality and more possibilities to a new generation of wearable electronics.

Low-cost Internet of Things (IoT)-enabled a wireless wearable device for detecting potassium ions at the point of care

We present a wearable device for wireless monitoring of potassium in sweat. The device consists of an all-solid-state ion-selective electrode (ISE) and a miniaturized printed circuit board (PCB) for potentiometric readout and processing. Stencil-printed carbon electrodes (SPCE) were fabricated on PET substrates using various types of graphite for comparison of sensor performance and were modified with carbon black to enhance sensor performance. The PCB readout module includes a low-power Wi-Fi interface for transmitting data real-time to a smartphone application, which can calculate potassium concentrations using a software algorithm and display the results on an OLED screen. The potassium selective ISE showed a response (< 11 s) to K+ with good sensitivity (56.1 ± 0.7 mV decade-1) and a linear range of 10-4-10-1 M with an LOD of 1 × 10-5 M. As a proof-of-concept, we demonstrate the applicability of the SPCE-ISE coupled to the wireless potentiometer operated from a smartphone for point-of-care testing (POC) of potassium in artificial sweat. The wearable Internet of Things (IoT) device uses an Arduino supported, Wi-Fi embedded microcontroller to transfer data. We reduced the cost of analysis compared to commercially available read-out devices using our potentiometer (< $25). This work represents a significant step forward as it is one of the first systems that integrates both sensing and data display in real-time on a device compatible with wearable applications by untrained users, making POC testing easier to fit into daily life.

A Passive Smart Face Mask for Wireless Cough Monitoring: A Harmonic Detection Scheme With Clutter Rejection.

Cough detection has aroused great interest because the assessment of cough frequency may improve diagnosis accuracy for dealing with several diseases, such as chronic obstructive pulmonary disease (COPD) and the recent COVID-19 global pandemic crisis. Here, we propose and experimentally demonstrate a wireless smart face mask based on a passive harmonic tag for real-time cough monitoring and alert. Our results show that the cough events can be successfully monitored through non-contact track of the received signal strength indicator (RSSI) at the harmonic frequency. Owing to the frequency orthogonality between the launched and backscattered radio-frequency (RF) signals, the harmonic tag-based smart mask can well suppress the electromagnetic interferences, such as clutters and crosstalks in noisy environments. We envision that this zero-power and lightweight wireless wearable device may be beneficial for cough monitoring and the public health condition in terms of tracking potential contagious person and virus-transmissive events.

Low-Cost Internet of Things (Iot)-Enabled a Wireless Wearable Device for Detecting Potassium Ions at the Point of Care

Low-Cost Internet of Things (Iot)-Enabled a Wireless Wearable Device for Detecting Potassium Ions at the Point of Care

Flexible and Anisotropic Strain Sensors with the Asymmetrical Cross-Conducting Network for Versatile Bio-Mechanical Signal Recognition.

Flexible strain sensors with high performance are actively and widely investigated for wearable electronic devices. However, the conventional sensors often suffer from a lack of detection of complex multidimensional strain, which severely limits their wide applications. To overcome this critical challenge, we propose a pattern design by screen printing to construct an asymmetrical cross-conductive network in the piezoresistive strain sensor, which can enhance the response to external stimuli in different directions. The unique network endows the prepared sensors with the excellent ability of instantaneous detection and accurate identification of multidimensional strains. Moreover, the sensor also demonstrates high sensitivity, fast response, an ultra-wide sensing range, and excellent stability and durability. Benefiting from the outstanding comprehensive performance of the prepared sensor, a full range of human actions (wink, smile, swallowing, and joint bending) and subtle bio-signals (pulse and breathing) are easily and accurately monitored. A wireless wearable device assembled by the sensor shows great potential applications in practical real-time physiological monitoring and intelligent mobile diagnosis for humans. This work provides an innovative and effective strategy for manufacturing flexible and multifunctional strain sensors to fully satisfy versatile applications of new-generation wearable electronic devices.

Wearable Patch Heart Rate Variability Is an Early Marker of Systemic Inflammation During Experimental Human Endotoxemia.

Early diagnosis and treatment can reduce the risk of organ failure and mortality in systemic inflammatory conditions. Heart rate variability (HRV) has potential for early identification of the onset of systemic inflammation, as it may detect changes in sympathetic nervous system activity resulting from the developing inflammatory response before clinical signs appear. With the use of new methodologies, we investigated the onset and kinetics of HRV changes as well as several inflammatory parameters and symptoms during experimental human endotoxemia, a model of systemic inflammation in humans in vivo. Healthy volunteers were intravenously administered LPS (n = 15) or placebo (n = 15). HRV was determined using a wireless wearable device, and parameters low to high frequency (LF:HF) ratio, root mean square of the successive differences (RMSSD), and standard deviation of normal-to-normal R-R intervals (SDNN)were calculated through 1-min-rolling 6-min windows. Plasma cytokine levels and flu-like symptoms and vital signs were serially assessed. The increase in LF:HF ratio, reflecting sympathetic predominance, was more pronounced in the LPS group compared to the placebo group, with the difference becoming statistically significant 65 min following LPS administration (1.63 [1.42-1.83] vs. 1.28 [1.11-1.44], P = 0.005). Significant between-group differences in RMSSD and SDNN were observed from 127 to 140 min post-LPS administration onwards, respectively. Plasma cytokine levels showed significant between-group differences staring 60 min post-LPS. For symptom score, heart rate, temperature, and diastolic blood pressure, significant differences compared with the placebo group were observed at 90, 118, 120, and 124 min post-LPS, respectively. In a controlled human model of systemic inflammation, elevations in the LF:HF ratio followed very shortly after elevations in plasma cytokine levels and preceded onset of flu-like symptoms and alterations in vital signs. HRV may represent a promising non-invasive tool for early detection of a developing systemic inflammatory response.

A Wearable Electrocardiography Sensor-System with Three-Dimensional Stretchable Interconnects

The recent COVID-19 pandemic has proven that low-cost wireless wearable medical device which offer reliable continuous health monitoring can be extremely valuable and game changing tools in early diagnosis, control and management of contiguous disease. Current commercial wearables are not reliable and accurate enough for medical diagnosis, further they are rigid, bulky, and expensive.Here we present a skin-mounted, low-cost, soft and stretchable wearable electrocardiography (ECG) sensor-system which enables continuous and wireless ECG recording. The ECG sensor-system consists of low-cost, disposable, soft and stretchable, carbon-based electrodes patch; and a reusable, front-end and wireless circuits patch. The sensor patches are made by our developed low-cost scalable manufacturing method of spray-printing, on breathable, conformal, stretchable medical adhesives. The softness and thinness of electrodes patch ensure the conformability of electrodes to skin, maximizes the quality of sensing by decreasing the electrode-skin impedance and consequently improving the signal to noise ratio (SNR) and furthermore offer comfort to users. The reusable ECG circuit patch consists of three-dimensional stretchable/deformable interconnects (SDI) integrated with off-the-shelf integrated circuit components. SDI is made of microfluidic channels filled with liquid metal (LM). Unless other reported liquid metal based interconnects, SDI has been designed in 3D form to increase the stretchability and make it robust to deformations in all three x, y and z axis. The sensor-system is also waterproof and the developed disposable sensors are breathable and more comfortable than commercial wet gel electrodes. The recorded ECG signal can be sent to a personal device such as tablet and laptop wirelessly and be displayed in real-time. The developed sensor-system is a platform that can be applied for the construction of various types of sensor-systems with other sensing capabilities. Figure 1

Wearable and Battery-Free Health-Monitoring Devices With Optical Power Transfer

Wireless epidermal wearable devices attract interests and expectations as a tool for personalized, low-cost health monitoring technology. The concept of the wireless attachable personal health monitoring devices has been more widely considered by combining them with biosensors. To bring the most advantage out of the structure of the epidermal attachable device, a battery-free approach was introduced to reduce the volume and extend the lifetime of the device. In this work, an energy harvesting technology and noninvasive sensor were applied with the attachable battery-free devices as a wireless power system and painless measuring system. A glucose sensor was used as an example to develop the wireless wearable device for diabetes-monitoring. The device consists of two functional parts: an optical power transfer and an electrochemical sensing part. The operation starts when the optical power transfer part accumulates power from series-connected photovoltaic cells and intermittently supplies the power to the electrochemical sensing part. In the electrochemical sensing part, an amperometric method was used for controlling the oxidation voltage and measuring a faraday current from the noninvasive sensor and current as brightness and duration of light pulses from a light-emitting diode (LED). The experiment results show that the device works as expected for a variety of glucose concentrations.

Research on the Application of Wireless Wearable Sensing Devices in Interactive Music

Wireless wearable devices can greatly assist and promote the artistic presentation of interactive music and have attracted the attention of more and more composers, musicians, dancers, and visual artists. It can pick up data information in real time, integrate with performers, and provide immersive performance experience. It not only builds a bridge between subjective feeling and spiritual perception for performers and audience but also enables audience to directly observe art information better. This paper mainly introduces the development process of a wearable sensor system designed for monitoring interactive music movement. Firstly, an interactive music motion model is established according to the principle of human body kinematics, and the experimental scheme of measuring the swaying angle of interactive music with a single sensor device is standardized. A multisensor fusion algorithm is proposed to estimate the swing angle of interactive music. Based on the “cost‐incentive” emotional model, the wireless wearable device and interactive music model are regarded as continuous variables determined by the emotional effect value and the incentive value. Extract energy, rhythm, harmony, time domain, and spectrum features of interactive music of wireless wearable devices, and reduce the dimension of a music feature space through principal component analysis, spatial projection, and relief feature selection. Finally, the practicability of the system and the accuracy of the algorithm are verified by experiments. The recognition rate of wireless wearable devices and interactive music realized based on this algorithm was improved.

Assessment of Residual Radioactivity by a Comprehensive Wireless, Wearable Device in Thyroid Cancer Patients Undergoing Radionuclide Therapy and Comparison With the Results of a Home Device: A Feasibility Study.

Objective: To investigate the feasibility of using a wireless wearable device (WD) in differentiated thyroid cancer (DTC) patients undergoing radionuclide therapy with I-131 (RAI) and protected hospitalization, this study compared the measurements of residual radioactivity obtained with those registered by a permanent environmental home device (HD). Methods: Twenty consecutive patients undergoing RAI hospitalized in restricted, controlled areas were enrolled. The patients underwent comprehensive monitoring of vital/nonvital parameters. We obtained 45580± 13 measurements from the WD, detecting the residual radioactivity for each patient during approximately 56 hours of hospitalization, collecting data 53 times per hour. The samples, collected during daily activities, were averaged every two hours, and the results correlated with those from the HD. Bland-Altman analysis was also used to evaluate the agreement between the two techniques. Results: A significant relationship between the WD and HD was observed (r = 0.96, p < 0.0001). Bland-Altman analysis recognized the agreement between measurements by the WD and HD. The mean value at the end of the first day of hospitalization was 80.81 microSv/h and 60.77 microSv/h (p = ns for WD and HD), whereas those at the end of the second day were 47.08 and 24.96 (p = ns). In the generalized linear model (GLM), a similar trend in performance across time was found with the two techniques. Conclusion: This study demonstrates good agreement between the residual radioactivity measures estimated by the WD and HD modalities, rendering them interchangeable. This approach will allow both the optimization of medical staff exposure and safer patient discharge. Abbreviations: wireless device (WD); differentiated thyroid cancer (DTC); radionuclide therapy with I-131 (RAI); home device (HD); generalized linear model (GLM).

Evaluation of static ulcer on lower extremities using wireless wearable near-infrared spectroscopy device: Effect of deep venous thrombosis on TRiggered Angiography Non-Contrast-Enhanced sequence magnetic resonance imaging.

Venous leg ulcers, or static leg ulcers, are chronic wounds associated with ambulatory venous hypertension of the lower extremities as a consequence of venous valve reflux, reduce venous capacitance, poor calf venous pump, heart failure, or in conjunction with venous obstruction. A static ulcer with venous thrombosis in a pelvic or thigh vein responds favorably to anticoagulation agents. However, anticoagulation is less effective and even harmful when ambulatory venous hypertension has another cause such as venous reflux, poorly heart function, and poor calf venous pump. TRiggered Angiography Non-Contrast-Enhanced (TRANCE) magnetic resonance imaging (MRI) exploits differences in vascular signal intensity during the cardiac cycle for subsequent image subtraction, providing detailed radiation-free venograms without the use of contrast agents. The method is a new tool for evaluating the presence of thrombosis in the venous systems. TRANCE-MRI was employed to document the existence of venous thrombosis within the eight patients in this study. Subsequently, we used a wireless wearable near-infrared spectroscopy device to compare deep vein thrombosis-associated and non-deep vein thrombosis-associated static ulcers. The sampling depths were 5 and 10 mm, representing the dermis and subcutaneous tissue, respectively. There are four patients with venous leg ulcers proven with venous thrombosis by TRANCE-MRI and are classified as deep vein thrombosis group. Compared with the non-deep vein thrombosis group, the deep vein thrombosis group had less deoxyhemoglobin, less total hemoglobin, and a significantly lower H2O signal in the 5-mm sampling depth (dermis level). And eight health participants were included as control group. Wounded patients (including deep vein thrombosis and non-deep vein thrombosis patients) have higher H2O concentration on the 5-mm depth sampling than control group. In the 10-mm sampling depth (subcutaneous level), the deoxyhemoglobin and tissue oxygen saturation of the deep vein thrombosis group were lower than those of the non-deep vein thrombosis group, and the H2O concentration was higher than non-deep vein thrombosis group. Patients with static foot ulcers and deep vein thrombosis had similar oxyhemoglobin, deoxyhemoglobin, total hemoglobin, and tissue oxygen saturation than did those without deep vein thrombosis in 5-mm depth sampling (dermis level). Notably, the H2O signal of patients with non-deep vein thrombosis-associated static ulcers was higher for the 5-mm sampling depth. In patients with static ulcers and deep vein thrombosis, the H2O level may be higher in the 10-mm sampling depth, indicating that those patients had more subcutaneous water. In patients with non-deep vein thrombosis static foot ulcer, the near-infrared spectroscopy (NIRS) indicated worse fluid retention in the dermis level. The H2O value in the NIRS may be different owing to underline the cause of the venous leg ulcers.

Wearable Trip-Risk Monitoring System based on Plantar Information

This study develops a novel sensing system to monitor two trip-risk-related factors when walking on any surface and under any condition. One factor is the visualized plantar aspect during walking. We extended our previous system to a new wireless wearable device that also provides more stable image as well as improves the walking comfort. During walking, a plantar image is produced on a reflecting surface and captured by a camera embedded in a clog. The other factor is the minimum toe clearance (MTC). MTC is defined as the minimum distance between the ground and toe at the swing phase. Acceleration and time-of-flight sensors are attached to the plantar surface of a clog to accurately observe the MTC. The efficacy of both sensing systems embedded in the clog is demonstrated using the data obtained by experiments.

A Resource-Optimized VLSI Implementation of a Patient-Specific Seizure Detection Algorithm on a Custom-Made 2.2cm 2 Wireless Device for Ambulatory Epilepsy Diagnostics.

A patient-specific epilepsy diagnostic solution in the form of a wireless wearable ambulatory device is presented. First, the design, VLSI implementation, and experimental validation of a resource-optimized machine learning algorithm for epilepsy seizure detection are described. Next, the development of a mini-PCB that integrates a low-power wireless data transceiver and a programmable processor for hosting the seizure detection algorithm is discussed. The algorithm uses only EEG signals from the frontal lobe electrodes while yielding a seizure detection sensitivity and specificity competitive to the standard full EEG systems. The experimental validation of the algorithm VLSI implementation proves the possibility of conducting accurate seizure detection using quickly-mountable dry-electrode headsets without the need for uncomfortable/painful through-hair electrodes or adhesive gels. Details of design and optimization of the algorithm, the VLSI implementation, and the mini-PCB development are presented and resource optimization techniques are discussed. The optimized implementation is uploaded on a low-power Microsemi Igloo FPGA, requires 1237 logic elements, consumes 110 μW dynamic power, and yields a minimum detection latency of 10.2 μs. The measurement results from the FPGA implementation on data from 23 patients (198 seizures in total) shows a seizure detection sensitivity and specificity of 92.5% and 80.1%, respectively. Comparison to the state of the art is presented from system integration, the VLSI implementation, and the wireless communication perspectives.

Highly Sensitive and Wearable Liquid Metal-Based Pressure Sensor for Health Monitoring Applications: Integration of a 3D-Printed Microbump Array with the Microchannel.

Wearable pressure sensors capable of sensitive, precise, and continuous measurement of physiological and physical signals have great potential for the monitoring of health status and the early diagnosis of diseases. This work introduces a 3D-printed rigid microbump-integrated liquid metal-based soft pressure sensor (3D-BLiPS) for wearable and health-monitoring applications. Using a 3D-printed master mold based on multimaterial fused deposition modeling, the fabrication of a liquid metal microchannel and the integration of a rigid microbump array above the microchannel are achieved in a one-step, direct process. The microbump array enhances the sensitivity of the pressure sensor (0.158 kPa-1 ) by locally concentrating the deformation of the microchannel with negligible hysteresis and a stable signal response under cyclic loading. The 3D-BLiPS also demonstrates excellent robustness to 10 000 cycles of multidirectional stretching/bending, changes in temperature, and immersion in water. Finally, these characteristics are suitable for a wide range of applications in health monitoring systems, including a wristband for the continuous monitoring of the epidermal pulse rate for cuffless blood pressure estimation and a wireless wearable device for the monitoring of body pressure using a multiple pressure sensor array for the prevention of pressure ulcers.