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1.
Nat Commun ; 13(1): 5311, 2022 09 09.
Article in English | MEDLINE | ID: mdl-36085341

ABSTRACT

Wearable strain sensors that detect joint/muscle strain changes become prevalent at human-machine interfaces for full-body motion monitoring. However, most wearable devices cannot offer customizable opportunities to match the sensor characteristics with specific deformation ranges of joints/muscles, resulting in suboptimal performance. Adequate wearable strain sensor design is highly required to achieve user-designated working windows without sacrificing high sensitivity, accompanied with real-time data processing. Herein, wearable Ti3C2Tx MXene sensor modules are fabricated with in-sensor machine learning (ML) models, either functioning via wireless streaming or edge computing, for full-body motion classifications and avatar reconstruction. Through topographic design on piezoresistive nanolayers, the wearable strain sensor modules exhibited ultrahigh sensitivities within the working windows that meet all joint deformation ranges. By integrating the wearable sensors with a ML chip, an edge sensor module is fabricated, enabling in-sensor reconstruction of high-precision avatar animations that mimic continuous full-body motions with an average avatar determination error of 3.5 cm, without additional computing devices.


Subject(s)
Accelerometry , Machine Learning , Range of Motion, Articular , Wearable Electronic Devices , Accelerometry/instrumentation , Humans , Motion
2.
ACS Nano ; 14(9): 11860-11875, 2020 09 22.
Article in English | MEDLINE | ID: mdl-32790337

ABSTRACT

Emerging soft exoskeletons pose urgent needs for high-performance strain sensors with tunable linear working windows to achieve a high-precision control loop. Still, the state-of-the-art strain sensors require further advances to simultaneously satisfy multiple sensing parameters, including high sensitivity, reliable linearity, and tunable strain ranges. Besides, a wireless sensing system is highly desired to enable facile monitoring of soft exoskeleton in real time, but is rarely investigated. Herein, wireless Ti3C2Tx MXene strain sensing systems were fabricated by developing hierarchical morphologies on piezoresistive layers and incorporating regulatory resistors into circuit designs as well as integrating the sensing circuit with near-field communication (NFC) technology. The wireless MXene sensor system can simultaneously achieve an ultrahigh sensitivity (gauge factor ≥ 14,000) and reliable linearity (R2 ≈ 0.99) within multiple user-designated high-strain working windows (130% to ≥900%). Additionally, the wireless sensing system can collectively monitor the multisegment exoskeleton actuations through a single database channel, largely reducing the data processing loading. We finally integrate the wireless, battery-free MXene e-skin with various soft exoskeletons to monitor the complex actuations that assist hand/leg rehabilitation.


Subject(s)
Exoskeleton Device , Titanium , Electric Power Supplies , Monitoring, Physiologic
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