ORIGINAL RESEARCH article
Front. Bioeng. Biotechnol.
Sec. Biomechanics
This article is part of the Research TopicRevolutionizing sports science: Biomechanical models, wearable tech, and AIView all 19 articles
Fully textile passive wireless sensing for human movement monitoring with multiple sensors
Provisionally accepted
- ETH Zürich, Zurich, Switzerland
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Movement monitoring with wearable technologies is becoming increasingly popular in different fields of applications (clinical, sports, entertainment). Particularly, textile-based wearables for movement monitoring are attractive as they follow the body movement, are comfortable to use, and can provide continuous tracking capabilities. Ideally, these wearable devices should be flexible (as opposed to current technologies with rigid electronics on the garments) and transmit data wirelessly to avoid hindering the natural movement with connections. Although fully textile wireless and passive wearable systems - whereby the textile sensing part does not have any rigid components and the data is wirelessly transmitted to an external reader - have been developed, the capability of these technologies is currently limited to a single sensor. In this work, we present a system based on a resonating inductor-capacitor (LC) circuits that can measure multiple sensors to broaden the range of use by tracking more than a single joint. Importantly, the presented system employs multiple capacitive strain sensors but retains the use of a single inductor for data transmission, limiting the complexity of realization and the number of connections. After characterization on the bench for careful design of the circuit components, we demonstrated the capability of the system to be used for human movement monitoring and activity classification by integrating two sensors in sport leggings and performing different static and dynamic activities. The tests with sensorized leggings were performed by a single participant. Among a set of chosen classification algorithms, the best performance (F1-score) was 0.98 for the static activities and 0.96 for dynamic activities. When including three independent sessions (donning and doffing the sensorised leggings) accuracy and F1-score dropped to 0.86 and 0.87 respectively. Overall, the presented system has the potential to be adopted as unobtrusive and comfortable smart clothing for real time movement monitoring.
Keywords: activityclassification, e-textiles, Movement monitoring, multiplexing, Wearable strain sensors, wireless system
Received: 13 Oct 2025; Accepted: 31 Jan 2026.
Copyright: © 2026 Galli, Ahmadizadeh and Menon. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Carlo Menon
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