{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,21]],"date-time":"2026-10-21T12:46:19Z","timestamp":1792586779003,"version":"4.5.0"},"reference-count":47,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2021,12,22]],"date-time":"2021-12-22T00:00:00Z","timestamp":1640131200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100003621","name":"Ministry of Science ICT and Future Planning","doi-asserted-by":"publisher","award":["NTIS 1711138169, KMDF KMDF_PR_20200901_0100"],"award-info":[{"award-number":["NTIS 1711138169, KMDF KMDF_PR_20200901_0100"]}],"id":[{"id":"10.13039\/501100003621","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100008783","name":"National Research Council of Science and Technology","doi-asserted-by":"publisher","award":["CAP-18014-000"],"award-info":[{"award-number":["CAP-18014-000"]}],"id":[{"id":"10.13039\/501100008783","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003693","name":"Korea Institute of Science and Technology","doi-asserted-by":"publisher","award":["2E31153"],"award-info":[{"award-number":["2E31153"]}],"id":[{"id":"10.13039\/501100003693","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The joint angle during gait is an important indicator, such as injury risk index, rehabilitation status evaluation, etc. To analyze gait, inertial measurement unit (IMU) sensors have been used in studies and continuously developed; however, they are difficult to utilize in daily life because of the inconvenience of having to attach multiple sensors together and the difficulty of long-term use due to the battery consumption required for high data sampling rates. To overcome these problems, this study propose a multi-joint angle estimation method based on a long short-term memory (LSTM) recurrent neural network with a single low-frequency (23 Hz) IMU sensor. IMU sensor data attached to the lateral shank were measured during overground walking at a self-selected speed for 30 healthy young persons. The results show a comparatively good accuracy level, similar to previous studies using high-frequency IMU sensors. Compared to the reference results obtained from the motion capture system, the estimated angle coefficient of determination (R2) is greater than 0.74, and the root mean square error and normalized root mean square error (NRMSE) are less than 7\u00b0 and 9.87%, respectively. The knee joint showed the best estimation performance in terms of the NRMSE and R2 among the hip, knee, and ankle joints.<\/jats:p>","DOI":"10.3390\/s22010053","type":"journal-article","created":{"date-parts":[[2021,12,23]],"date-time":"2021-12-23T02:02:57Z","timestamp":1640224977000},"page":"53","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":66,"title":["Prediction of Lower Extremity Multi-Joint Angles during Overground Walking by Using a Single IMU with a Low Frequency Based on an LSTM Recurrent Neural Network"],"prefix":"10.3390","volume":"22","author":[{"given":"Joohwan","family":"Sung","sequence":"first","affiliation":[{"name":"Center for Bionics, Biomedical Research Division, Korea Institute of Science and Technology, Seoul 02792, Korea"},{"name":"Department of Biomedical Science, College of Medicine, Korea University, Seoul 02841, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2762-668X","authenticated-orcid":false,"given":"Sungmin","family":"Han","sequence":"additional","affiliation":[{"name":"Center for Bionics, Biomedical Research Division, Korea Institute of Science and Technology, Seoul 02792, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6858-539X","authenticated-orcid":false,"given":"Heesu","family":"Park","sequence":"additional","affiliation":[{"name":"Center for Bionics, Biomedical Research Division, Korea Institute of Science and Technology, Seoul 02792, Korea"},{"name":"Department of Biomedical Science, College of Medicine, Korea University, Seoul 02841, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hyun-Myung","family":"Cho","sequence":"additional","affiliation":[{"name":"Center for Bionics, Biomedical Research Division, Korea Institute of Science and Technology, Seoul 02792, Korea"},{"name":"Department of Artificial Intelligence, Korea University, Seoul 02841, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Soree","family":"Hwang","sequence":"additional","affiliation":[{"name":"Center for Bionics, Biomedical Research Division, Korea Institute of Science and Technology, Seoul 02792, Korea"},{"name":"School of Biomedical Engineering, Korea University, Seoul 02841, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2751-2519","authenticated-orcid":false,"given":"Jong Woong","family":"Park","sequence":"additional","affiliation":[{"name":"Department of Biomedical Science, College of Medicine, Korea University, Seoul 02841, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Inchan","family":"Youn","sequence":"additional","affiliation":[{"name":"Center for Bionics, Biomedical Research Division, Korea Institute of Science and Technology, Seoul 02792, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2021,12,22]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Baldwin, R., Bobovych, S., Robucci, R., Patel, C., and Banerjee, N. 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