{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,5]],"date-time":"2026-09-05T15:57:16Z","timestamp":1788623836883,"version":"build-2803163510"},"reference-count":34,"publisher":"SAGE Publications","issue":"3","license":[{"start":{"date-parts":[[2022,11,29]],"date-time":"2022-11-29T00:00:00Z","timestamp":1669680000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Soft Robotics"],"published-print":{"date-parts":[[2023,6,1]]},"abstract":"<jats:p>\n                    Skeletal muscles are critical to human-limb motion dynamics and energetics, where their mechanical states are seldom explored\n                    <jats:italic toggle=\"yes\">in vitro<\/jats:italic>\n                    due to practical limitations of sensing technologies. This article aims to capture mechanical deformations of muscle contraction using wearable flexible sensors, which is justified with model calibration and experimental validation. The capacitive sensor is designed with the composite of conductive fabric electrodes and the porous dielectric layer to increase the pressure sensitivity and prevent lateral expansions. In this way, the compressive displacement of muscle deformation is captured in the muscle-sensor coupling model in terms of sensor deformation and parameters of pretension, material, and shape properties. The sensing model is calibrated in a linear form using ultrasound medical imaging. The sensor is capable of measuring muscle strain of 70% with an error of &lt;3.6% and temperature disturbance of &lt;5.6%. After 10K cycles of compression, the drift is only 3.3%. Immediate application of the proposed method is illustrated by gait pattern identification, where the K-nearest neighbor prediction accuracy of squats, level walking, stair ascent\/descent, and ramp ascent is over 97% with a standard deviation below 2.6% compared to that of 94.61\u2009\u00b1\u20094.24% for ramp descent, and the response time is 14.37\u2009\u00b1\u20090.52\u2009ms. The wearable sensing method is valid for muscle deformation monitoring and gait pattern identification, and it provides an alternative approach to capture mechanical motions of muscles, which is anticipated to contribute to understand locomotion biomechanics in terms of muscle forces and metabolic landscapes.\n                  <\/jats:p>","DOI":"10.1089\/soro.2022.0065","type":"journal-article","created":{"date-parts":[[2022,12,1]],"date-time":"2022-12-01T11:44:01Z","timestamp":1669895041000},"page":"601-611","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":21,"title":["Flexible Capacitive Sensing and Ultrasound Calibration for Skeletal Muscle Deformations"],"prefix":"10.1177","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7740-6792","authenticated-orcid":false,"given":"Jiajie","family":"Guo","sequence":"first","affiliation":[{"name":"State Key Laboratory of Digital Manufacturing Equipment and Technology, School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan, China."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chuxuan","family":"Guo","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Digital Manufacturing Equipment and Technology, School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan, China."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jialei","family":"Zhou","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Digital Manufacturing Equipment and Technology, School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan, China."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kui","family":"Duan","sequence":"additional","affiliation":[{"name":"Huazhong University of Science and Technology, School Hospital, Wuhan, China."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qining","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Advanced Manufacturing and Robotics, College of Engineering, Peking University, Beijing, China."}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2022,11,29]]},"reference":[{"key":"e_1_3_4_2_2","doi-asserted-by":"crossref","unstructured":"Winter DA. 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