App. Res. of Comp. Accepted Paper
Vol. 41, 2024 No. 8

Action assessment method of rehabilitation training based on human skeleton key points for cardiovascular patients

Zhang Ruize1a
Guo Wei2
Yang Guanci1a,1b
Luo Kexin1c
Li Yang1a
He Ling1a
1. a. Key Laboratory of Advanced Manufacturing Technology of Ministry of Education, b. State Key Laboratory of Public Big Data, c. School of Mechanical Engineering, Guizhou University, Guiyang 550025, China
2. Guizhou Provincial Staff & Workers Hospital, Guiyang 550025, China
DOI: 10.19734/j.issn.1001-3695.2023.11.0606

Abstract

To assess and correct the movements during cardiovascular patients' independent rehabilitation training at home, this paper proposed an action assessment method for cardiovascular patients' rehabilitation training based on key points of the human skeleton (ASRT-PHS) . Firstly, this paper constructed a dataset for rehabilitation training actions using a camera and data augmentation in accordance with the specified rehabilitation training specification for cardiovascular patients. Secondly, this paper employed a deep learning-based detector and pose estimator to capture human body positions and extract key points of the human skeleton, respectively. And then input the results into a convolutional neural network for action recognition. Thirdly, by calculating joint angle thresholds, joint distance ratio and assessing standard motions, this paper constructed a motion segmentation model based on joint distance ratios and an action assessment model based on action joint angle thresholds. This paper investigated the optimal combination of ASRT-PHS by assessing its performance with various joint angle thresholds and action recognition approaches. The results show that ASRT-PHS achieves an average action recognition, segmentation and assessment accuracy of 92.78%, 77.6% and 87%, respectively. Finally, case tests about the true cardiovascular patients show that the average accuracy of the prototype system is 71.3%, which provides a feasible intelligent auxiliary system for patients' autonomous rehabilitation training at home.

Foundation Support

国家自然科学基金项目(62373116,62163007)
贵州省科技计划(黔科合平台人才[2020]6007-2,黔科合支撑[2021]一般439,黔科合支撑[2023]一般117)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2023.11.0606
Publish at: Application Research of Computers Accepted Paper, Vol. 41, 2024 No. 8

Publish History

[2024-03-07] Accepted Paper

Cite This Article

张睿泽, 郭威, 杨观赐, 等. 基于人体骨骼关键点的心血管患者康复训练动作评估方法 [J]. 计算机应用研究, 2024, 41 (8). (2024-04-10). https://doi.org/10.19734/j.issn.1001-3695.2023.11.0606. (Zhang Ruize, Guo Wei, Yang Guanci, et al. Action assessment method of rehabilitation training based on human skeleton key points for cardiovascular patients [J]. Application Research of Computers, 2024, 41 (8). (2024-04-10). https://doi.org/10.19734/j.issn.1001-3695.2023.11.0606. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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