Smart Wearable Sensors Based on Triboelectric Nanogenerator for Personal Healthcare Monitoring.
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ABSTRACT:
SUBMITTER: Li R
PROVIDER: S-EPMC8064435 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Gait and waist motions always contain massive personnel information and it is feasible to extract these data via wearable electronics for identification and healthcare based on the Internet of Things (IoT). There also remains a demand to develop a cost-effective human-machine interface to enhance the immersion during the long-term rehabilitation. Meanwhile, triboelectric nanogenerator (TENG) revealing its merits in both wearable electronics and IoT tends to be a possible solution. Herein, the authors present wearable TENG-based devices for gait analysis and waist motion capture to enhance the intelligence and performance of the lower-limb and waist rehabilitation. Four triboelectric sensors are equidistantly sewed onto a fabric belt to recognize the waist motion, enabling the real-time robotic manipulation and virtual game for immersion-enhanced waist training. The insole equipped with two TENG sensors is designed for walking status detection and a 98.4% identification accuracy for five different humans aiming at rehabilitation plan selection is achieved by leveraging machine learning technology to further analyze the signals. Through a lower-limb rehabilitation robot, the authors demonstrate that the sensory system performs well in user recognition, motion monitoring, as well as robot and gaming-aided training, showing its potential in IoT-based smart healthcare applications.
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Project description:Wearable sensors are important components, converting mechanical vibration energy into electrical signals or other forms of output, which are widely used in healthcare, disaster warning, and transportation. However, the reliance on batteries limits the portability of wearable sensors and hinders their application in the field of Internet of Things. To solve this problem, we designed a miniaturized high-performance hybrid nanogenerator (MHP-HNG), which combined the functions of triboelectric sensing and electromagnetic power generation as well as the advantages of miniaturization. By optimizing the design of TENG and EMG, the wearable sensor achieved a voltage output of 14.14 V and a power output of 49 mW. Based on the wireless optical communication and wireless communication technologies, the wearable sensor achieved the integration of sensing, communication, and self-powered function, which is expected to realize health monitoring, emergency warning, and rehabilitation assistance, and further extend the potential application value in the medical field.
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Project description:The fast-spreading of novel coronavirus disease (COVID-19) has been sweeping arount the globe and brought heavy casualties and economic losses, which creats dire needs for technological solutions into medical preventive actions. In this work, triboelectric nanogenerator for respiratory sensing (RS-TENG) has been designed and integrated with facemask, which endows the latter with respiratory monitoring function. The output of RS-TENG for respiratory flow can reach up to about 8 V and 0.8 μA respectively although it varies with different respiratory status, which proves the high sensitivity of RS-TENG for respiratory monitoring. An apnea alarm system can be constructed by combining the smart facemask with circuit modules so that timely alarm can be transmitted after people stop breathing. Furthermore, RS-TENG can be used to control household appliances, which brings convenience to the life of the disabled people. Considering its incomparable advantages such as small volume, easy fabrication, simple installation and economical applicability, such design is helpful for developing multifunctional health monitoring gadgets during the COVID-19 pandemic.
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Project description:Wearable and implantable electronics (WIEs) are more and more important and attractive to the public, and they have had positive influences on all aspects of our lives. As a bridge between wearable electronics and their surrounding environment and users, sensors are core components of WIEs and determine the implementation of their many functions. Although the existing sensor technology has evolved to a very advanced level with the rapid progress of advanced materials and nanotechnology, most of them still need external power supply, like batteries, which could cause problems that are difficult to track, recycle, and miniaturize, as well as possible environmental pollution and health hazards. In the past decades, based upon piezoelectric, pyroelectric, and triboelectric effect, various kinds of nanogenerators (NGs) were proposed which are capable of responding to a variety of mechanical movements, such as breeze, body drive, muscle stretch, sound/ultrasound, noise, mechanical vibration, and blood flow, and they had been widely used as self-powered sensors and micro-nanoenergy and blue energy harvesters. This review focuses on the applications of self-powered generators as implantable and wearable sensors in health monitoring, biosensor, human-computer interaction, and other fields. The existing problems and future prospects are also discussed.
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Project description:With aging, disability of the body can easily occur because the function of the body is degraded. Especially, swallowing disorder is regarded as a crucial issue because patients cannot obtain the nutrients from food by swallowing it. Hence, the rehabilitation of swallowing disorder is urgently required. However, the conventional device for swallowing rehabilitation has shown some limitations due to its external power source and internal circuit. Herein, a self-powered triboelectric nanogenerator for swallowing rehabilitation (TSR) is proposed. To increase the electrical output and pressure sensitivity of the TSR, the tilted reactive ion etching is conducted and the electrical output and pressure sensitivity are increased by 206% and 370%, respectively. The effect of the tilted reactive ion etching into the electrical output generated from the TSR is systematically analyzed. When the tongue is pressing, licking, and holding the TSR, each motion is successfully detected through the proposed TSR. Based on these results, the smart swallowing rehabilitation monitoring system (SSRMS) is implemented as the application and the SSRMS could successfully detect the pressing by the tongue. Considering these results, the SSRMS can be expected to be utilized as a promising smart swallowing rehabilitation monitoring system in near future.
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