Knitted self-powered sensing textiles for machine learning-assisted sitting posture monitoring and correction

Abstract

With increasing work pressure in modern society, prolonged sedentary positions with poor sitting postures can cause physical and psychological problems, including obesity, muscular disorders, and myopia. In this paper, we present a self-powered sitting position monitoring vest (SPMV) based on triboelectric nanogenerators (TENGs) to achieve accurate real-time posture recognition through an integrated machine learning algorithm. The SPMV achieves high sensitivity (0.16 mV/Pa), favorable stretchability (10%), good stability (12,000 cycles), and machine washability (10 h) by employing knitted double threads interlaced with conductive fiber and nylon yarn. Utilizing a knitted structure and sensor arrays that are stitched into different parts of the clothing, the SPMV offers a non-invasive method of recognizing different sitting postures, providing feedback, and warning users while enhancing long-term wearing comfortability. It achieves a posture recognition accuracy of 96.6% using the random forest classifier, which is higher than the logistic regression (95.5%) and decision tree (94.3%) classifiers. The TENG-based SPMV offers a reliable solution in the healthcare system for non-invasive and long-term monitoring, promoting the development of triboelectric-based wearable electronics.

Ultrastretchable High-Conductivity MXene-Based Organohydrogels for Human Health Monitoring and Machine-Learning-Assisted Recognition

“…Recently, a sedentary lifestyle has been adopted by individuals due to substantial pressure from work or education. Numerous physical and psychological problems, such as spine disease, obesity, muscular disorders, and myopia follow poor long-term sitting posture . A convenient and wearable sensor with an intervention function is required to remind users to maintain the right sitting posture, which will alleviate problems arising from a poor sitting posture.…”

“…Moreover, in order to satisfy an accurate detection of both large-scale deformations induced by bodily movements and subtle stimuli deformations such as breathing and artery pulse, wearable electronics with high strain/pressure sensitivity, wide detection range, and low detection threshold are of great importance. Recently, various wearable electronics have been proposed mostly based on elastomer matrices − (e.g., polydimethylsiloxane (PDMS), VHB, Ecoflex), hydrogel matrices, , and nanofibers. , Although elastomer-based and nanofiber-based wearable electronics have manifested excellent conductivity and high sensitivity, their intrinsic properties, such as limited stretchability, uncomfortableness, mechanical mismatches, nonbiodegradability, and complex fabrication processes, have severely impeded their practical applications. However, by virtue of their inherently high stretchability, flexibility, and biocompatibility, conductive hydrogels stand out from these existing materials .…”

Wearable Optical Sensing in the Medical Internet of Things (MIoT) for Pervasive Medicine: Opportunities and Challenges

“…Some reports about battery powered WOSs and skin-like battery-free devices can be found in ref 222. Technologies such as sweat energy harvesting, 223 wireless power transmission, 224 self-powered sensing textiles, 225 and triboelectric sensors 226 can provide remarkable solutions for the continuous power supply of wearable devices.…”

Elastic Fibers/Fabrics for Wearables and Bioelectronics

“…• Limitation of raw material in mechanical and electrical stability • Precise fabrication of contact junctions for different devices Sensor [ 178,179] SC [ 180,181] TENG [111,182] TEG [175,183]…”