{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T18:16:59Z","timestamp":1775067419196,"version":"3.50.1"},"reference-count":44,"publisher":"MDPI AG","issue":"16","license":[{"start":{"date-parts":[[2023,8,17]],"date-time":"2023-08-17T00:00:00Z","timestamp":1692230400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Natural Science Foundation of China","award":["62271349"],"award-info":[{"award-number":["62271349"]}]},{"name":"Natural Science Foundation of China","award":["520601220009"],"award-info":[{"award-number":["520601220009"]}]},{"name":"Natural Science Foundation of China","award":["2021-JCJQ-JJ-0617"],"award-info":[{"award-number":["2021-JCJQ-JJ-0617"]}]},{"name":"State Grid Shandong electric power company science and technology project","award":["62271349"],"award-info":[{"award-number":["62271349"]}]},{"name":"State Grid Shandong electric power company science and technology project","award":["520601220009"],"award-info":[{"award-number":["520601220009"]}]},{"name":"State Grid Shandong electric power company science and technology project","award":["2021-JCJQ-JJ-0617"],"award-info":[{"award-number":["2021-JCJQ-JJ-0617"]}]},{"name":"54th Research Institute of China Electronics Technology Group Corporation","award":["62271349"],"award-info":[{"award-number":["62271349"]}]},{"name":"54th Research Institute of China Electronics Technology Group Corporation","award":["520601220009"],"award-info":[{"award-number":["520601220009"]}]},{"name":"54th Research Institute of China Electronics Technology Group Corporation","award":["2021-JCJQ-JJ-0617"],"award-info":[{"award-number":["2021-JCJQ-JJ-0617"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Sensor-based human action recognition (HAR) is considered to have broad practical prospects. It applies to wearable devices to collect plantar pressure or acceleration information at human joints during human actions, thereby identifying human motion patterns. Existing related works have mainly focused on improving recognition accuracy, and have rarely considered energy-efficient management of portable HAR systems. Considering the high sensitivity and energy harvesting ability of triboelectric nanogenerators (TENGs), in this research a TENG which achieved output performance of 9.98 mW\/cm2 was fabricated using polydimethylsiloxane and carbon nanotube film for sensor-based HAR as a wearable sensor. Considering real-time identification, data are acquired using a sliding window approach. However, the classification accuracy is challenged by quasi-periodic characteristics of the intercepted sequence. To solve this problem, compensatory dynamic time warping (C-DTW) is proposed, which adjusts the DTW result based on the proportion of points separated by small distances under DTW alignment. Our simulation results show that the classification accuracy of C-DTW is higher than that of DTW and its improved versions (e.g., WDTW, DDTW and softDTW), with almost the same complexity. Moreover, C-DTW is much faster than shapeDTW under the same classification accuracy. Without loss of generality, the performance of the existing DTW versions can be enhanced using the compensatory mechanism of C-DTW.<\/jats:p>","DOI":"10.3390\/s23167230","type":"journal-article","created":{"date-parts":[[2023,8,17]],"date-time":"2023-08-17T10:47:02Z","timestamp":1692269222000},"page":"7230","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["C-DTW for Human Action Recognition Based on Nanogenerator"],"prefix":"10.3390","volume":"23","author":[{"given":"Haifeng","family":"Xu","sequence":"first","affiliation":[{"name":"School of Electrical and Information Engineering, Tianjin University, Tianjin 300072, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Renhai","family":"Feng","sequence":"additional","affiliation":[{"name":"School of Electrical and Information Engineering, Tianjin University, Tianjin 300072, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Weikang","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Electrical and Information Engineering, Tianjin University, Tianjin 300072, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2023,8,17]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"164","DOI":"10.1016\/j.patrec.2021.04.008","article-title":"Capturing causality and bias in human action recognition","volume":"147","author":"Lai","year":"2021","journal-title":"Pattern Recognit. 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