{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,10]],"date-time":"2026-01-10T18:59:39Z","timestamp":1768071579149,"version":"3.49.0"},"reference-count":31,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2021,3,25]],"date-time":"2021-03-25T00:00:00Z","timestamp":1616630400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100002585","name":"Korea Aerospace University","doi-asserted-by":"publisher","award":["2020-01-003"],"award-info":[{"award-number":["2020-01-003"]}],"id":[{"id":"10.13039\/501100002585","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>In this paper, we propose a method of identifying human motions, such as standing, walking, running, and crawling, using a millimeter wave radar sensor. In our method, two signal processing is performed in parallel to identify the human motions. First, the moment at which a person\u2019s motion changes is determined based on the statistical characteristics of the radar signal. Second, a deep learning-based classification algorithm is applied to determine what actions a person is taking. In each of the two signal processing, radar spectrograms containing the characteristics of the distance change over time are used as input. Finally, we evaluate the performance of the proposed method with radar sensor data acquired in an indoor environment. The proposed method can find the moment when the motion changes with an error rate of 3%, and also can classify the action that a person is taking with more than 95% accuracy.<\/jats:p>","DOI":"10.3390\/s21072305","type":"journal-article","created":{"date-parts":[[2021,3,25]],"date-time":"2021-03-25T21:09:45Z","timestamp":1616706585000},"page":"2305","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":22,"title":["Identification of Human Motion Using Radar Sensor in an Indoor Environment"],"prefix":"10.3390","volume":"21","author":[{"given":"Sung-wook","family":"Kang","sequence":"first","affiliation":[{"name":"School of Electronics and Information Engineering, College of Engineering, Korea Aerospace University, Goyang-si 10540, Gyeonggi-do, Korea"}]},{"given":"Min-ho","family":"Jang","sequence":"additional","affiliation":[{"name":"School of Electronics and Information Engineering, College of Engineering, Korea Aerospace University, Goyang-si 10540, Gyeonggi-do, Korea"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9115-4897","authenticated-orcid":false,"given":"Seongwook","family":"Lee","sequence":"additional","affiliation":[{"name":"School of Electronics and Information Engineering, College of Engineering, Korea Aerospace University, Goyang-si 10540, Gyeonggi-do, Korea"}]}],"member":"1968","published-online":{"date-parts":[[2021,3,25]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1109\/MSP.2016.2628914","article-title":"Automotive radars: A review of signal processing techniques","volume":"34","author":"Patole","year":"2017","journal-title":"IEEE Signal Process. 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