Wearable Smart System Research Articles

Recent Progress in Wearable Near-Sensor and In-Sensor Intelligent Perception Systems.

As the Internet of Things (IoT) becomes more widespread, wearable smart systems will begin to be used in a variety of applications in people's daily lives, not only requiring the devices to have excellent flexibility and biocompatibility, but also taking into account redundant data and communication delays due to the use of a large number of sensors. Fortunately, the emerging paradigms of near-sensor and in-sensor computing, together with the proposal of flexible neuromorphic devices, provides a viable solution for the application of intelligent low-power wearable devices. Therefore, wearable smart systems based on new computing paradigms are of great research value. This review discusses the research status of a flexible five-sense sensing system based on near-sensor and in-sensor architectures, considering material design, structural design and circuit design. Furthermore, we summarize challenging problems that need to be solved and provide an outlook on the potential applications of intelligent wearable devices.

Functional fibers/textiles for smart sensing devices and applications in personal healthcare systems.

Personalized medical diagnostics and monitoring have become increasingly important due to inefficient and delayed medical services of traditional centralized healthcare systems. To enhance the comfort and portability, flexible health monitoring systems have been developed in recent years. In particular, smart fiber/textile-based sensing devices show superiority for continuously monitoring personal health and vital physiological parameters owing to their light weight, good flexibility and inherent miniaturization. This review focuses on the recent advances in smart fiber/textile-based sensing devices for wearable electronic applications. First, fabrication strategies of smart sensing fibers/textiles are introduced in detail. In addition, sensing performances, working principles and applications of smart sensing fibers/textiles such as pressure sensing fibers/textiles, stretchable strain sensing fibers/textiles, temperature sensing fibers/textiles, and biofluid, gas and humidity sensing fibers/textiles in health monitoring are also reviewed systematically. Finally, we propose current challenges and future prospects in the area of fiber/textile-based sensors for wearable healthcare monitoring and diagnosis systems. In general, this review aims to give an overall perspective of the promising field by reviewing various fiber/textile-based sensing devices and highlighting the importance for researchers to keep up with the sequential exploration of soft sensing fibers/textiles for applications in wearable smart systems.

Deep‐learning enabled smart insole system aiming for multifunctional foot‐healthcare applications

AbstractReal‐time foot pressure monitoring using wearable smart systems, with comprehensive foot health monitoring and analysis, can enhance quality of life and prevent foot‐related diseases. However, traditional smart insole solutions that rely on basic data analysis methods of manual feature extraction are limited to real‐time plantar pressure mapping and gait analysis, failing to meet the diverse needs of users for comprehensive foot healthcare. To address this, we propose a deep learning‐enabled smart insole system comprising a plantar pressure sensing insole, portable circuit board, deep learning and data analysis blocks, and software interface. The capacitive sensing insole can map both static and dynamic plantar pressure with a wide range over 500 kPa and excellent sensitivity. Statistical tools are used to analyze long‐term foot pressure usage data, providing indicators for early prevention of foot diseases and key data labels for deep learning algorithms to uncover insights into the relationship between plantar pressure patterns and foot issues. Additionally, a segmentation method assisted deep learning model is implemented for exercise‐fatigue recognition as a proof of concept, achieving a high classification accuracy of 95%. The system also demonstrates various foot healthcare applications, including daily activity statistics, exercise injury avoidance, and diabetic foot ulcer prevention.

A nanonewton-scale biomimetic mechanosensor

Biomimetic mechanosensors have profound implications for various areas, including health care, prosthetics, human‒machine interfaces, and robotics. As one of the most important parameters, the sensitivity of mechanosensors is intrinsically determined by the detection resolution to mechanical force. In this manuscript, we expand the force detection resolution of current biomimetic mechanosensors from the micronewton to nanonewton scale. We develop a nanocrack-based electronic whisker-type mechanosensor that has a detection resolution of 72.2 nN. We achieve the perception of subtle mechanical stimuli, such as tiny objects and airflow, and the recognition of surface morphology down to a 30 nm height, which is the finest resolution ever reported in biomimetic mechanosensors. More importantly, we explore the use of this mechanosensor in wearable devices for sensing gravity field orientation with respect to the body, which has not been previously achieved by these types of sensors. We develop a wearable smart system for sensing the body’s posture and movements, which can be used for remote monitoring of falls in elderly people. In summary, the proposed device offers great advantages for not only improving sensing ability but also expanding functions and thus can be used in many fields not currently served by mechanosensors.

Intelligent Bio-Impedance System for Personalized Continuous Blood Pressure Measurement.

Continuous blood pressure (BP) measurement is crucial for long-term cardiovascular monitoring, especially for prompt hypertension detection. However, most of the continuous BP measurements rely on the pulse transit time (PTT) from multiple-channel physiological acquisition systems that impede wearable applications. Recently, wearable and smart health electronics have become significant for next-generation personalized healthcare progress. This study proposes an intelligent single-channel bio-impedance system for personalized BP monitoring. Compared to the PTT-based methods, the proposed sensing configuration greatly reduces the hardware complexity, which is beneficial for wearable applications. Most of all, the proposed system can extract the significant BP features hidden from the measured bio-impedance signals by an ultra-lightweight AI algorithm, implemented to further establish a tailored BP model for personalized healthcare. In the human trial, the proposed system demonstrates the BP accuracy in terms of the mean error (ME) and the mean absolute error (MAE) within 1.7 ± 3.4 mmHg and 2.7 ± 2.6 mmHg, respectively, which agrees with the criteria of the Association for the Advancement of Medical Instrumentation (AAMI). In conclusion, this work presents a proof-of-concept for an AI-based single-channel bio-impedance BP system. The new wearable smart system is expected to accelerate the artificial intelligence of things (AIoT) technology for personalized BP healthcare in the future.

IBGS: A Wearable Smart System to Assist Visually Challenged

Traditional blind guide devices are large and high cost. In this paper, a kind of intelligent blind guide system (IBGS) is introduced. GD32 is used as the main control chip, it cooperates with various functional modules to realize traffic light recognition, obstacle avoidance, payment, and navigation functions on the basis of speech recognition. At the same time, IBGS uses WIFI instead of Bluetooth to get rid of the dependence on smart phones. In addition, a cloud database is built, and the Internet of Things technology is used to realize the information interconnection between the IBGS, the database, and the guardian’s mobile terminal. In order to better realize the function of speech recognition, this paper proposes a Conv-Transformer Transducer (ConvT-T) speech recognition framework based on Weak-Attention Suppression (WAS), which improves the efficiency of multi-head attention through WAS. The proposed method achieves word error rate (WER) of 3.2% in test-clean and 7.9% in test-other on the LibriSpeech ASR corpus with only 73M parameters, which reduces the WER by 0.3% and 0.4% compared to ConvT-T respectively, indicating that WAS can effectively play the role of suppressing non-critical attention on the ConvT-T framework. At the same time, the IBGS has been tested in a comprehensive application scenario. In outdoor traffic light recognition, speech recognition, and obstacle avoidance tests, the accuracy rates of 92.33%, 90.33%, and 96.67% were achieved respectively. The results show that the IBGS can effectively deal with various challenges encountered by the blind in their daily outdoor walking.

“Sweat-chargeable” on-skin supercapacitors for practical wearable energy applications

Supercapacitors (SCs) have received worldwide attention as energy devices for wearable smart systems. Biocompatibility and self-charging property of SCs require serious consideration, but the related studies are just in their infancy. Here, a “sweat-chargeable” on-skin SC using biocompatible NaCl electrolyte and freestanding polyaniline/carbon nanotube (PANI/CNT) electrodes is presented. Although the capacitance of the biocompatible SC is about half of that using conventional skin-irritated H2SO4 electrolyte, the potential window extends from 0.8 V to 1.4 V. Thus, a higher energy density can be obtained. The self-charging property is achieved by simply adding a piece of Zn foil on one electrode with silver paste, which provides energy source and maintains a super compact two-electrode configuration of SC. The sweat absorbed from human body could trigger the redox reaction between the added Zn foil and oxygen in air, resulting in the self-charging of the device to 0.652 V in 6 min. To demonstrate its wearability in real applications, a “sweat-chargeable” band is prepared that can spontaneously power a timer or a pedometer when the user is exercising. This work has made a further step in the development of biocompatible and practical wearable energy devices.

A Novel Wearable Foot and Ankle Monitoring System for the Assessment of Gait Biomechanics

Walking is the most basic form of human activity for achieving mobility. As an essential function of the human body, the examination of walking is directed towards the assessment of body mechanics in posture and during movement. This work proposes a wearable smart system for the monitoring and objective evaluation of foot biomechanics during gait. The proposed solution assumes the cross-correlation of the plantar pressure with lower-limb muscular activity, throughout the stance phase of walking. Plantar pressure is acquired with an array of resistive pressure sensors deployed onto a shoe insole along the center of gravity progression line. Lower-limb muscular activity is determined from the electromyogram of the tibialis anterior and gastrocnemius lower limb muscles respectively. Under this scenario, physiological gait assumes the interdependency of plantar pressure on the heel area with activation of the tibialis anterior, as well as plantar pressure on the metatarsal arch/toe area with activation of the gastrocnemius. As such, assessment of gait physiology is performed by comparison of a gait map, formulated based on the footprint–lower-limb muscle cross-correlation results, to a reference gait template. A laboratory proof of concept validates the proposed solution in a test scenario which assumes a normal walking and two pathological walking patterns.

High‐Performance Flexible Magnetic Tunnel Junctions for Smart Miniaturized Instruments

Flexible electronics is an emerging field in many applications ranging from in vivo biomedical devices to wearable smart systems. The capability of conforming to curved surfaces opens the door to add electronic components to miniaturized instruments, where size and weight are critical parameters. Given their prevalence on the sensors market, flexible magnetic sensors play a major role in this progress. For many high‐performance applications, magnetic tunnel junctions (MTJs) have become the first choice, due to their high sensitivity, low power consumption etc. MTJs are also promising candidates for non‐volatile next‐generation data storage media and, hence, could become central components of wearable electronic devices. In this work, a generic low‐cost regenerative batch fabrication process is utilized to transform rigid MTJs on a 500 µm silicon wafer substrate into 5 µm thin, mechanically flexible silicon devices, and ensuring optimal utilization of the whole substrate. This method maintains the outstanding magnetic properties, which are only obtained by deposition of the MTJ on smooth high‐quality silicon wafers. The flexible MTJs are highly reliable and resistive to mechanical stress. Bending of the MTJ stacks with a diameter as small as 500 µm is possible without compromising their performance and an endurance of over 1000 cycles without fatigue has been demonstrated. The flexible MTJs are mounted onto the tip of a cardiac catheter with 2 mm in diameter without compromising their performance. This enables the detection of magnetic fields and the angle which they are applied at with a high sensitivity of 4.93%/Oe and a low power consumption of 0.15 μW, while adding only 8 and 5 μm to the weight and diameter of the catheter, respectively.

(Invited) Carbon Nanomaterials for Flexible and Stretchable Devices

The development of flexible electronics and equipment attracts significant interests in recent years. It is of great importance to develop flexible and wearable energy storage devices for wearable and portable devices. Carbon nanomaterials have large surface area, good conductivity and excellent mechanical and chemical stability, enabling their applications in high performance energy conversion and energy storage devices. In this talk, I will present fiber-shaped ultra-stretchable and flexible supercapacitor made of carbon nanotube fibers, film-shaped stretchable supercapacitors and flexible Zn-air batteries using stretchable graphitized natural fabrics as electrodes. The ultra-stretchable wire-shaped supercapacitor was made by winding two carbon nanotube@graphene@MnO2 fibers around a superelastic core fiber. The supercapacitor can sustain tensile strain up to 850%, which is hitherto the highest value, while keeping stable electrochemical performance. We further demonstrated that there devices can be assembled with carbon-based flexible sensors into wearable smart systems. These strategy paves new ways for the fabrication of high performance wearable energy storage devices and flexible electronics.

Wearable Smart System for Visually Impaired People.

In this paper, we present a wearable smart system to help visually impaired persons (VIPs) walk by themselves through the streets, navigate in public places, and seek assistance. The main components of the system are a microcontroller board, various sensors, cellular communication and GPS modules, and a solar panel. The system employs a set of sensors to track the path and alert the user of obstacles in front of them. The user is alerted by a sound emitted through a buzzer and by vibrations on the wrist, which is helpful when the user has hearing loss or is in a noisy environment. In addition, the system alerts people in the surroundings when the user stumbles over or requires assistance, and the alert, along with the system location, is sent as a phone message to registered mobile phones of family members and caregivers. In addition, the registered phones can be used to retrieve the system location whenever required and activate real-time tracking of the VIP. We tested the system prototype and verified its functionality and effectiveness. The proposed system has more features than other similar systems. We expect it to be a useful tool to improve the quality of life of VIPs.

A hierarchical combinatorial testing method for smart phone software in wearable IoT systems

As the Internet of Things technology is finding more wide applications; wearable smart systems such as smart phones have gradually come into our lives. The smart wearable systems with numerous states usually lead to various unanticipated problems. A connective and semantic similarity clustering algorithm (CSSCA) and a hierarchical combinatorial test model based on finite state machine (FSM) are proposed to solve the problem. The FSM model of user manipulations is usually used to model the system design specification of a smart phone for black-box testing, and then it is converted into a regular expression, and some testing cases are generated according to the regular expression. Many experiments show that a large in scale and complicated in structure smart phone software can be tested using our innovative algorithms to discover more deep hidden logical errors efficiently and effectively.

A Study on a Healthcare System Using Smart Clothes

Being able to monitor the heart will allow the diagnosis of heart diseases for patients during daily activities, and the detection of burden on the heart during strenuous exercise. Furthermore, with the help of U-health technology, immediate medical action can be taken, in the case of abnormal symptoms of the heart in daily life. Therefore, it appears to be necessary to develop the corresponding technology to monitor the condition of the heart daily. In this study, a novel wearable smart system was proposed, to monitor the activity of the heart in daily life, and to further evaluate the rhythm of arrhythmia. The wearable system includes three modified bipolar conductive fiber electrodes in the chest part, which can resolve the reduction problem of the magnitude of the signal, by magnifying the signal and removing the noise, to obtain high affinity and validity for medical-type usage (<0.903%). The biological signal acquisition and data lines, and the signal processing engine and communication consist of a conductive ink, and the pic18 and ANT protocol nRF24AP2, respectively. The proposed algorithm was able to detect a strong ECG, signal and r-point passing over the noise. The confidence intervals were 96 %, which could satisfy the requirement to detect arrhythmia under the unconstrained conditions.

A Smart and Wearable Cardiac Healthcare System with Monitoring of Sudden Fall for Elderly and Post-Operative Patients

The dominance of chronic diseases, driven by an increasingly aging population with a new health paradigm that emphasizes early finding, early diagnosis and early treatment, is highly recommended. Especially, Cardiac disorders and sudden falls are the prominent reasons behind hospitalization of the elderly and post-operative patients. In the present work, we have designed and developed a GSM (Global System for Mobile) based wearable smart system with 3-axis accelerometer and three lead ECG recording system. The whole system is wearable for all and can be used as a real-time monitoring, self-diagnosis, and remote- diagnosis tool as it will detect whenever there is an abnormal heart condition and a sudden fall situation. The entire data flow program and evaluation for the system has been done under NI LabVIEW platform. After detecting the health abnormalities the system sends alert notifications to the care giver and health professionals to take compulsory actions. This paper also deals with estimation of ECG parameters as they have significant clinical values in order to detect cardiac disorders. With this developed system, elderly or ill individuals especially senior citizens who live alone or have a disability could stay independently at their home.

Application of Wearable Smart System To Support Physical Activity

Application of Wearable Smart System To Support Physical Activity