9dfcce80-9760-4555-ba74-b8274d84c70220220121064523514naun:naunmdt@crossref.orgMDT DepositInternational Journal of Circuits, Systems and Signal Processing1998-446410.46300/9106http://www.naun.org/cms.action?id=30291720221720221610.46300/9106.2022.16https://npublications.com/journals/circuitssystemssignal/2022.phpYanliDouDepartment of Physical Education, Lvliang University, lvliang, ChinaMost nursing workers have a positive cognitive attitude towards physical exercise, but their exercise behavior lags behind. There are significant differences in the frequency, time, experience and load of physical exercise among nurses of different ages. Care workers’ union organizations should try their best to provide health assistance to medical staff to meet their needs for physical exercise, so as to ensure their physical and mental health. Aiming at the problem of target tracking in motion video, this paper proposes a method of tracking motion video of nursing staff based on deep neural network (DNN). The effectiveness and adaptability of this method are verified by an example. This method can not only track and estimate the position of the target effectively, but also describe the shape of the target well, thus solving the problem that the shape of the target is complex and difficult to track in motion video.1132022113202246146956https://npublications.com/journals/circuitssystemssignal/2022/b142005-056(2022).pdf10.46300/9106.2022.16.56https://npublications.com/journals/circuitssystemssignal/2022/b142005-056(2022).pdfOuyang Gu, Zhong Bineng, Bai Bing, et al. Application and latest research progress of DNN in target tracking algorithm. Small Microcomputer System, 2018, 39(02):315-323. Hou Zhiqiang, Dai Bo, Hu Dan, et al. Visual tracking based on perceptual DNN. 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