Wearable Healthcare Monitoring System Research Articles

LoRaWAN-based hybrid internet of wearable things system implementation for smart healthcare

This study introduces the design and development of an Internet of Wearable Things-based Hybrid Healthcare Monitoring System (IoWT-HHMS) for smart medical applications. The system incorporates smart wearable sensing units for real-time, remote monitoring of vital health parameters such as Blood Pressure (BP), Heart Rate (HR), and Body Temperature (BT). A key innovation is the development of a hybrid wireless network communication mechanism within the IoWT-HHMS, utilising the FiPy microcontroller. This mechanism supports both short- and long-range connectivity and integrates an algorithm for efficient data acquisition and updating to the IoT platform. The IoWT-HHMS has undergone extensive testing and validation across various scenarios, including sensor functionality, performance of Wi-Fi and LoRaWAN networks, hybrid network connectivity, and accuracy assessment using the Datacake dashboard. The tests evaluated crucial aspects such as communication reliability, power consumption, and latency. The results demonstrate the system's high stability and accuracy in reading health parameters. Comparisons with reference devices reveal impressive accuracy levels for Systolic BP (SBP), Diastolic BP (DBP), HR, and BT, recording 96.37 %, 95.17 %, 97 %, and 98.57 % accuracy, respectively. Both Wi-Fi and LoRaWAN networks proved reliable in indoor and outdoor settings, maintaining data transmission over distances up to 1.5 km without data loss. In conclusion, the developed IoWT-HHMS shows great promise for efficient and effective real-time remote monitoring of patients' health conditions using an innovative hybrid wireless network communication mechanism.

A cost-effective and facile technique for realizing fabric based microfluidic channels using beeswax and PVC stencils.

Microfluidic channels fabricated over fabrics or papers have the potential to find substantial application in the next generation of wearable healthcare monitoring systems. The present work focuses on the fabrication procedures that can be used to obtain practically realizable fabric-based microfluidic channels (μFADs) utilizing patterning masks and wax, unlike conventional printing techniques. In this study, comparative analysis was used to differentiate channels obtained using different masking tools for channel patterning as well as different wax materials as hydrophobic barriers. Drawbacks of the conventional tape and candle wax technique were noted and a novel approach was used to create microfluidic channels through a facile and simple masking technique using PVC clear sheets as channel stencils and beeswax as the channel barriers. The resulting fabric based microfluidic channels with varying widths as well as complex microchannel, microwell, and micromixer designs were investigated and a minimum channel width resolution of 500 μm was successfully obtained over cotton based fabrics. Thereafter, the PVC clear sheet-beeswax based microwells were successfully tested to confine various organic and inorganic samples indicating vivid applicability of the technique. Finally, the microwells were used to make a simple and facile colorimetric assay for glucose detection and demonstrated effective detection of glucose levels from 10 mM to 50 mM with significant color variation using potassium iodide as the coloring agent. The above findings clearly suggest the potential of this alternative technique for making low-cost and practically realizable fabric based diagnostic devices (μFADs) in contrast to the other approaches that are currently in use.

Electrospun PVDF/aromatic HBP of 4th gen based flexible and self-powered TENG for wearable energy harvesting and health monitoring

In recent times, high-performance wearable electronic devices that can transform mechanical force into electrical energy for biomedical monitoring applications are receiving an increasing amount of attention. In the present study, we focused on a flexible, self-powered and wearable triboelectric nanogenerator (TENG) based on electrospun polyvinylidene fluoride (PVDF)/aromatic hyperbranched polyester of 4th generation (Ar.HBP-G4, 0–40 wt.-% w.r.t. PVDF content) blend nanoweb as tribo-negative layer and melt-blown thermoplastic polyurethane (TPU) as tribo-positive layer for energy harvesting and human health monitoring applications. Among the varying Ar.HBP-G4 content used, incorporation of Ar.HBP-G4 (10 wt.-%) in PVDF (P-Ar.HBP-G4-10) showed higher increase in the triboelectric output voltage when compared to pristine PVDF and other Ar.HBP-G4 weight ratios. The optimized P-Ar.HBP-G4-10/TPU based TENG exhibited a peak-to-peak voltage (Vp-p) of 124.4 V under an applied load of 9.8 N and frequency 1 Hz which is superior to many other TENGs reported elsewhere. Higher triboelectric performance of P-Ar.HBP-G4 blend based TENG compared to that of neat PVDF is attributed to the effect of Ar.HBP-G4-10 in enhancing the degree of crystallinity and polar β-crystalline phase content (98.3%) in PVDF. The ability of the TENG to power up portable electronic devices is demonstrated when it is powered for 750 s while connected through a capacitor and a rectifier, and the TENG was able to operate 45 light-emitting diodes directly. Evaluation of the triboelectric output of the TENG device attached to different parts of the human body reveal significantly better output voltage and sensitivity for human health monitoring. The results of this work pave a new way to develop TENG based on P-Ar.HBP-G4 nanowebs for sustainable energy generation and wearable healthcare monitoring systems.

Strain‐Driven Negative Resistance Switching of Conductive Fibers with Adjustable Sensitivity for Wearable Healthcare Monitoring Systems with Near‐Zero Standby Power (Adv. Mater. 36/2023)

Strain‐Driven Negative Resistance Switching of Conductive Fibers with Adjustable Sensitivity for Wearable Healthcare Monitoring Systems with Near‐Zero Standby Power (Adv. Mater. 36/2023)

Strain-Driven Negative Resistance Switching of Conductive Fibers with Adjustable Sensitivity for Wearable Healthcare Monitoring Systems with Near-Zero Standby Power.

Recently, one of the primary concerns in e-textile-based healthcare monitoring systems for chronic illness patients has been reducing wasted power consumption, as the system should be always-on to capture diverse biochemical and physiological characteristics. However, the general conductive fibers, a major component of the existing wearable monitoring systems, have a positive gauge-factor (GF) that increases electrical resistance when stretched, so that the systems have no choice but to consume power continuously. Herein, a twisted conductive-fiber-based negatively responsive switch-type (NRS) strain-sensor with an extremely high negative GF (resistance change ratio ≈ 3.9× 108 ) that can significantly increase its conductivity from insulating to conducting properties is developed. To this end, a precision cracking technology is devised, which could induce a difference in the Young's modulus of the encapsulated layer on the fiber through selective ultraviolet-irradiation treatment. Owing to this technology, the NRS strain-sensors can allow for effective regulation of the mutual contact resistance under tensile strain while maintaining superior durability for over 5000 stretching cycles. For further practical demonstrations, three healthcare monitoring systems (E-fitness pants, smart-masks, and posture correction T-shirts) with near-zero standby power are also developed, which opens up advancements in electronic textiles by expanding the utilization range of fiber strain-sensors.

Wearable triboelectric nanogenerator with micro-topping structures via material jet printing method

With the development of human-machine interactions, human healthcare monitoring and Internet of Things, it is of vital importance to explore revolutionary fabrication methods to provide sustainable and flexible energy harvesters for massive personnel information. In this work, we developed the micro-topping structures enhanced triboelectric nanogenerator (MT-TENG) via unique jet printing method with the advantages of high precision, high efficiency and excellent uniformity. Regular micro-topping structure array could be tuned conveniently and rapidly through adjusting the ink properties, printing parameters and substrate characteristics in jet printing process. The results show that with micro-topping structures, TENG has high specific surface for contact electrification. MT-TENG can be applied in the real-time monitoring and self-powered sensing of body physiological signal and human joint movement. This work provides a previously unexplored strategy for shortening individual design cycle and promoting the practicality of TENG in mass manufacturing, and also possess a potential application of wearable electronics and healthcare monitoring system.

Motion Artifact Reduction in Electrocardiogram Signals Through a Redundant Denoising Independent Component Analysis Method for Wearable Health Care Monitoring Systems: Algorithm Development and Validation.

The quest for improved diagnosis and treatment in home health care models has led to the development of wearable medical devices for remote vital signs monitoring. An accurate signal and a high diagnostic yield are critical for the cost-effectiveness of wearable health care monitoring systems and their widespread application in resource-constrained environments. Despite technological advances, the information acquired by these devices can be contaminated by motion artifacts (MA) leading to misdiagnosis or repeated procedures with increases in associated costs. This makes it necessary to develop methods to improve the quality of the signal acquired by these devices. We aimed to present a novel method for electrocardiogram (ECG) signal denoising to reduce MA. We aimed to analyze the method's performance and to compare its performance to that of existing approaches. We present the novel Redundant denoising Independent Component Analysis method for ECG signal denoising based on the redundant and simultaneous acquisition of ECG signals and movement information, multichannel processing, and performance assessment considering the information contained in the signal waveform. The method is based on data including ECG signals from the patient's chest and back, the acquisition of triaxial movement signals from inertial measurement units, a reference signal synthesized from an autoregressive model, and the separation of interest and noise sources through multichannel independent component analysis. The proposed method significantly reduced MA, showing better performance and introducing a smaller distortion in the interest signal compared with other methods. Finally, the performance of the proposed method was compared to that of wavelet shrinkage and wavelet independent component analysis through the assessment of signal-to-noise ratio, dynamic time warping, and a proposed index based on the signal waveform evaluation with an ensemble average ECG. Our novel ECG denoising method is a contribution to converting wearable devices into medical monitoring tools that can be used to support the remote diagnosis and monitoring of cardiovascular diseases. A more accurate signal substantially improves the diagnostic yield of wearable devices. A better yield improves the devices' cost-effectiveness and contributes to their widespread application.

Facile fabrication of silver-nanowire-based chips using dry-film photoresist for wearable optical detection

With technological advances in wearable health care monitoring system, there increasing demands for the patterning technology for reliable sensors. Dry-film photoresists (DFRs) have several advantages for the patterning of silver nanowires (AgNWs), including cost-effectiveness, low toxicity of the process, and ease of mass production through a roll-to-roll process. In this study, using DFRs, we achieved the facile fabrication of AgNW-based chips for optical detection of myoglobin (Mb) via surface-enhanced Raman spectroscopy (SERS). Mb is found in accessible biological fluids such as urine and serum, which is a representative protein biomarker for human health monitoring. AgNWs were successfully patterned on polyethylene terephthalate films using DFR to form multiple spots, with a diameter of ~500 µm, that are available for detection. SERS spectra showed that the AgNW chips can efficiently detect myoglobin proteins down to levels of clinical significance. Our results will provide insights for the cost-effective production method of futuristic health care monitoring system.

Wearable Sensing Systems for Monitoring Mental Health.

Wearable systems for monitoring biological signals have opened the door to personalized healthcare and have advanced a great deal over the past decade with the development of flexible electronics, efficient energy storage, wireless data transmission, and information processing technologies. As there are cumulative understanding of mechanisms underlying the mental processes and increasing desire for lifetime mental wellbeing, various wearable sensors have been devised to monitor the mental status from physiological activities, physical movements, and biochemical profiles in body fluids. This review summarizes the recent progress in wearable healthcare monitoring systems that can be utilized in mental healthcare, especially focusing on the biochemical sensors (i.e., biomarkers associated with mental status, sensing modalities, and device materials) and discussing their promises and challenges.

A Comprehensive Review on Wearable Health Monitoring Systems

This paper presents a comprehensive review of the wearable healthcare monitoring systems proposed by the researchers to date. One of the earliest wearable recorders, named “a silicon locket for ECG monitoring”, was developed at the Indian Institute of Technology, Bombay, in 2003. Thus, the wearable health monitoring systems, started with the acquisition of a single signal/ parameter to the present generation smart and affordable multi-parameter recording/monitoring systems, have evolved manifolds in these two decades. Wearable systems have dramatically changed in terms of size, cost, functionality, and accuracy. The early-day wearable recorders were with limited functionalities against today’s systems, e.g., Apple’s iWatch which comprises abundant health monitoring features like heart rate monitoring, breathing app, accelerometers, smart walking/ activity monitoring, and alerts. Most of the present-day smartphones are not only capable of recording various health features like body temperature, heart rate, photoplethysmograph (PPG) signal, calory consumption, smart activity monitoring, stress measurement, etc. through different apps, but they also help the user to get monitored by a family physician via GSM or even internet of things (IoT). One of the latest, state-of-the-art real-time personal health monitoring systems, Wearable IoT-cloud-based health monitoring system (WISE), is a beautiful amalgamation of body area sensor network (BASN) and IoT framework for ubiquitous health monitoring. The future of wearable health monitoring systems will be far beyond the IoT and BASN.

Review on the wearable health-care monitoring system with robust motion artifacts reduction techniques

PurposeWearables are gaining prominence in the health-care industry and their use is growing. The elderly and other patients can use these wearables to monitor their vitals at home and have them sent to their doctors for feedback. Many studies are being conducted to improve wearable health-care monitoring systems to obtain clinically relevant diagnoses. The accuracy of this system is limited by several challenges, such as motion artifacts (MA), power line interference, false detection and acquiring vitals using dry electrodes. This paper aims to focus on wearable health-care monitoring systems in the literature and provides the effect of MA on the wearable system. Also presents the problems faced while tracking the vitals of users.Design/methodology/approachMA is a major concern and certainly needs to be suppressed. An analysis of the causes and effects of MA on wearable monitoring systems is conducted. Also, a study from the literature on motion artifact detection and reduction is carried out and presented here. The benefits of a machine learning algorithm in a wearable monitoring system are also presented. Finally, distinct applications of the wearable monitoring system have been explored.FindingsAccording to the study reduction of MA and multiple sensor data fusion increases the accuracy of wearable monitoring systems.Originality/valueThis study also presents the outlines of design modification of dry/non-contact electrodes to minimize the MA. Also, discussed few approaches to design an efficient wearable health-care monitoring system.

An Insight into Tunable Innate Piezoelectricity of Silk for Green Bioelectronics.

Commercially available bioelectronics account for significant percentage of e-waste, especially battery waste, that demand immediate intervention due to rising environmental concerns. Consumers are becoming increasingly aware and cautious of their contribution to carbon footprint on a regular basis. It has become imperative to adopt sustainability in every aspect of production of bioelectronics taking into consideration the growing market for wearable healthcare monitoring system. Green electronics is a relatively new concept gaining tremendous attention within the scientific and industrial community with the ultimate goal of employing organic, biodegradable, and self-sustainable system to replace the conventional inorganic battery-powered electronics. Silk is a green material that has been extensively explored for its use in functional electronics due to its tunable biodegradability and flexibility. Nevertheless, an intriguing property of Silk is its innate piezoelectricity. This review highlights the importance of crystal orientation and structure of Silk Fibroin to display piezoelectric response and documents possible strategies for its enhancement. It also provides insight into the possibility of using piezoelectric Silk as a piezoelectric sensor, actuator, and energy harvester to form self-powered hybrid systems for autonomous bioelectronics.

Memory Devices: Solution‐Processed Stretchable Ag2S Semiconductor Thin Films for Wearable Self‐Powered Nonvolatile Memory (Adv. Mater. 23/2021)

In article number 2100066, Ju-Young Kim Moon Kee Choi, Jae Sung Son, and co-workers develop a solution-processed synthesis of intrinsically stretchable Ag2S thin films for the fabrication of self-powered stretchable resistive random-access memory devices. The device exhibits excellent switching characteristics, mechanical stretchability, and extremely high chemical and thermal durability. A self-powered memory combined with motion sensors is demonstrated for use as a wearable healthcare-monitoring system.

Solution-Processed Stretchable Ag2 S Semiconductor Thin Films for Wearable Self-Powered Nonvolatile Memory.

Compared with the large plastic deformation observed in ductile metals and organic materials, inorganic semiconductors have limited plasticity (<0.2%) due to their intrinsic bonding characters, restricting their widespread applications in stretchable electronics. Herein, the solution-processed synthesis of ductile α-Ag2 S thin films and fabrication of all-inorganic, self-powered, and stretchable memory devices, is reported. Molecular Ag2 S complex solution is synthesized by chemical reduction of Ag2 S powder, fabricating wafer-scale highly crystalline Ag2 S thin films. The thin films show stretchability due to the intrinsic ductility, sustaining the structural integrity at a tensile strain of 14.9%. Moreover, the fabricated Ag2 S-based resistive random access memory presents outstanding bipolar switching characteristics (Ion /Ioff ratio of ≈105 , operational endurance of 100 cycles, and retention time >106 s) as well as excellent mechanical stretchability (no degradation of properties up to stretchability of 52%). Meanwhile, the device is highly durable under diverse chemical environments and temperatures from -196 to 300 °C, especially maintaining the properties for 168 h in 85% relative humidity and 85 °C. A self-powered memory combined with motion sensors for use as a wearable healthcare monitoring system is demonstrated, offering the potential for designing high-performance wearable electronics that are usable in daily life in a real-world setting.

A review of biomarkers in the context of type 1 diabetes: Biological sensing for enhanced glucose control.

As wearable healthcare monitoring systems advance, there is immense potential for biological sensing to enhance the management of type 1 diabetes (T1D). The aim of this work is to describe the ongoing development of biomarker analytes in the context of T1D. Technological advances in transdermal biosensing offer remarkable opportunities to move from research laboratories to clinical point‐of‐care applications. In this review, a range of analytes, including glucose, insulin, glucagon, cortisol, lactate, epinephrine, and alcohol, as well as ketones such as beta‐hydroxybutyrate, will be evaluated to determine the current status and research direction of those analytes specifically relevant to T1D management, using both in‐vitro and on‐body detection. Understanding state‐of‐the‐art developments in biosensing technologies will aid in bridging the gap from bench‐to‐clinic T1D analyte measurement advancement.

Cloud Centric Authentication for Wearable Healthcare Monitoring System

Security and privacy are the major concerns in cloud computing as users have limited access on the stored data at the remote locations managed by different service providers. These become more challenging especially for the data generated from the wearable devices as it is highly sensitive and heterogeneous in nature. Most of the existing techniques reported in the literature are having high computation and communication costs and are vulnerable to various known attacks, which reduce their importance for applicability in real-world environment. Hence, in this paper, we propose a new cloud based user authentication scheme for secure authentication of medical data. After successful mutual authentication between a user and wearable sensor node, both establish a secret session key that is used for future secure communications. The extensively-used Real-Or-Random (ROR) model based formal security analysis and the broadly-accepted Automated Validation of Internet Security Protocols and Applications (AVISPA) tool based formal security verification show that the proposed scheme provides the session-key security and protects active attacks. The proposed scheme is also informally analyzed to show its resilience against other known attacks. Moreover, we have done a detailed comparative analysis for the communication and computation costs along with security and functionality features which proves its efficiency in comparison to the other existing schemes of its category.

Cloud‐assisted elliptic curve password authenticated key exchange protocol for wearable healthcare monitoring system

SummaryWearable devices (WDs) adopting advanced microsensors and IoT technology are facing severe security risks in the process of building wearable healthcare monitoring system. In particular, new requirements are proposed for the security of the identity authentication and key agreement protocol as well as the consumption of computing resources for WDs, such as replay attack, modification attack, server‐spoofing attack, privileged‐insider attack, and denial‐of‐service attack. To satisfy such requirements, cloud‐assisted EC password authenticated key exchange (CEPAK), an identity dynamic authentication and key agreement protocol, is proposed, and it uses a cloud‐assisted authentication service and elliptic curve algorithm. The capability of CEPAK protocol is analyzed to deal with network attack and consumption of computing resources and communication resources. It is shown that on the basis of satisfying the security requirements of the system, the cloud‐assisted authentication server can greatly share the consumption of computing resources of intelligent terminals, effectively save the computing resources of intelligent terminals, and improve the system's ability to deal with attacks caused by consumption of computing resources.

A magnetized microneedle-array based flexible triboelectric-electromagnetic hybrid generator for human motion monitoring

Most triboelectric-electromagnetic hybrid generators (TEHGs) are not suitable for monitoring human motions as wearable self-powered sensors owing to the rigid, complicated and bulky structures. In this work, we developed a novel magnetized microneedle-array (MA) based flexible TEHG for monitoring human motions. The magnetic-field-induced spray self-assembly method with electro-magnetizing technique was firstly proposed to cost-effectively fabricate magnetized microneedles for TEHG. The magnetized microneedles in TEHG simultaneously serve as the frictional layer of triboelectric generator (TEG) and bendable magnetic poles of electromagnetic generator (EMG). TEG utilized the closed bending-friction-restoring behavior of microneedles to generate triboelectricity while EMG used the rotation of magnetized microneedles to produce the induced electromotive force. TEG could output the open-circuit voltage (VOC) of 10 V and the EMG could generate the short-circuit current (ISC) of 80 μA under the 30 N and 1 Hz compressing-releasing operations. We demonstrated that the MA-based TEHG, integrated in insole and attached on elbow as the self-powered sensors, could exactly detect triggering frequency of human motions. Considering the unique advantages, including flexibility, small dimension, light weight, and easy scale up, further applications of TEHG in wearable electronics, self-powered sensors, and healthcare monitoring system are promising.

Measurement of finger joint angle using stretchable carbon nanotube strain sensor.

Strain sensors capable of monitoring complex human motions are highly desirable for the development of wearable electronic devices and healthcare monitoring systems. Excellent sensitivity and a wide working range of the sensor material are important requirements for distinguishing dynamic human motion. In this study, a highly stretchable strain sensor was fabricated via inkjet printing of single-walled carbon nanotube (SWCNT) thin films on a stretchable polydimethylsiloxane substrate. The sensor was attached to the metacarpophalangeal (MCP) joint of the hand in 12 healthy male subjects. The subjects placed their hands next to a conventional goniometer and flexed the MCP joint to predetermined angles. A linear relationship was found between the change in the length of the strain sensor and the intended angle of the MCP joint. The fabricated thin films showed high durability during repeated cycling (1,000 cycles) and good sensitivity with a gauge factor of 2.75. This study demonstrates that the newly developed stretchable CNT strain sensor can be used for effectively measuring MCP joint angles. This sensor may also be useful for the analysis of complex and dynamic hand motions that are difficult to measure using a conventional goniometer.

Functionalized Organic Thin Film Transistors for Biosensing.

The rise of organic bioelectronics efficiently bridges the gap between semiconductor devices and biological systems, leading to flexible, lightweight, and low-cost organic bioelectronic devices suitable for health or body signal monitoring. The introduction of organic semiconductors in the devices can soften the boundaries between microelectronic systems and dynamically active cells and tissues. Therefore, organic bioelectronics has attracted much attention recently due to the unique properties and promising applications. Organic thin film transistors (OTFTs), owing to their inherent capability of amplifying received signals, have emerged as one of the state-of-the-art biosensing platforms. The advantages of organic semiconductors in terms of synthetic freedom, low temperature solution processing, biocompatibility, and mechanical flexibility render OTFTs ideal transducers for wearable electronics, e-skin, and implantable devices. How to realize highly sensitive, selective, rapid, and efficient signal capture and extraction of biological recognition events is the major challenge in the design of biosensors. OTFTs are prone to converting the presence or change of target analytes into specific electrical signals even in complex biological systems. More importantly, OTFT sensors can be conveniently functionalized with chemical or biological modifications and exhibit substantially improved device sensitivity and selectivity as well as other analytical figure of merits, including calibration range, linearity, and accuracy. However, the stability and reproducibility of the organic devices need to be further improved. In this Account, we first introduce the unique features of OTFTs for bioelectronic applications. Two typical OTFT configurations, including organic electrochemical transistor (OECT) and electrolyte gated organic field effect transistor (EGOFET), are highlighted in their sensing applications mainly due to the operation of the devices in electrolytes and the combination of ionic and electronic charge transports in the devices. These devices are potentiometric transducers with low working voltages (<1 V) and high sensitivity, and are thus suitable for wearable applications with low power consumption. Second, the functionalization strategies on channel materials, electrolytes, and gate electrodes based on various modification methods and sensing mechanisms are discussed in sequence. In an OECT- or EGOFET-based biosensor, the device performance is particularly sensitive to the physical properties of the two interfaces, including channel/electrolyte and gate/electrolyte interfaces. Any change in the potential drop or capacitance of either interface can influence the channel current substantially. Therefore, the functionalization of the interfaces is critical to the sensing performance. In particular, when an electrochemically active material is modified on the interfaces, the reaction of the analyte catalyzed by the modified material can influence the interface potential and lead to a channel current response much stronger than that of a conventional electrochemical measurement. So the biosensors are much more sensitive than typical analytical methods due to the signal amplification of the transistors. Third, the processing techniques including screen printing and inkjet printing and the possibility for mass production are discussed. The applications of organic transistors in wearable electronics and healthcare monitoring systems, especially the fabric OECT-based biosensors for noninvasive detection, are presented. It is expected that the versatile organic transistors will enable various compact, flexible and disposable biosensors compatible with wearable electronics.