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Wireless battery-free body sensor networks using near-field-enabled clothing

Health and Fitness

Wireless battery-free body sensor networks using near-field-enabled clothing

R. Lin, H. Kim, et al.

Discover how innovative near-field-enabled clothing can revolutionize the way we monitor human physiological signals. Conducted by a team of experts including Rongzhou Lin, Han-Joon Kim, and others from the National University of Singapore, this research showcases a unique system for real-time, battery-free sensor networks that can help enhance clinical diagnostics and athletic performance.

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Playback language: English
Abstract
Networks of sensors placed on the skin can provide continuous measurement of human physiological signals for applications in clinical diagnostics, athletics and human-machine interfaces. Wireless and battery-free sensors are particularly desirable for reliable long-term monitoring, but current approaches for achieving this mode of operation rely on near-field technologies that require close proximity (at most a few centimetres) between each sensor and a wireless readout device. Here, we report near-field-enabled clothing capable of establishing wireless power and data connectivity between multiple distant points around the body to create a network of battery-free sensors interconnected by proximity to functional textile patterns. Using computer-controlled embroidery of conductive threads, we integrate clothing with near-field-responsive patterns that are completely fabric-based and free of fragile silicon components. We demonstrate the utility of the networked system for real-time, multi-node measurement of spinal posture as well as continuous sensing of temperature and gait during exercise.
Publisher
Nature Communications
Published On
Jan 23, 2020
Authors
Rongzhou Lin, Han-Joon Kim, Sippanat Achavananthadith, Selman A. Kurt, Shawn C.C. Tan, Haicheng Yao, Benjamin C.K. Tee, Jason K.W. Lee, John S. Ho
Tags
near-field technology
wireless sensors
functional textiles
physiological monitoring
real-time data
spinal posture
exercise
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