Guangjun Wang
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Guangjun Wang has a total of 12 co-authors. Here are the top co-authors by number of shared publications:
Benyue Su
The University Key Laboratory of Intelligent Perception and Computing of Anhui Province, Anqing Normal University, Anqing, China
2 shared publicationsHanyuan Zhang
Institute of Intelligent Machines, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, China
2 shared publicationsLiangliang Yao
The University Key Laboratory of Intelligent Perception and Computing of Anhui Province, Anqing Normal University, Anqing, China
2 shared publicationsYi Fan
The University Key Laboratory of Intelligent Perception and Computing of Anhui Province, Anqing Normal University, Anqing, China
2 shared publications- Zuchang Ma
Institute of Intelligent Machines, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, China
2 shared publications Bangguo Zhu
The University Key Laboratory of Intelligent Perception and Computing of Anhui Province, Anqing Normal University, Anqing, China
1 shared publication
Latest Publications
- 10 February 2024
- Published by Springer Nature in Multimedia Tools and Applications
- Vol. 83 (29) , 72197-72219
Design of an exergame system for knee osteoarthritis rehabilitation based on the exercise prescription
- 10 February 2024
- Published by Springer Nature in Multimedia Tools and Applications
- Vol. 83 (29) , 72197-72219
Design of an exergame system for knee osteoarthritis rehabilitation based on the exercise prescription
- 26 August 2022
- Published by Springer Nature in Health Information Science and Systems
- Vol. 10 (1) , 1-10
Design and evaluation of an exergame system to assist knee disorders patients' rehabilitation based on gesture interaction
We designed a knee rehabilitation exercise game (Exergame) for home-based rehabilitation of patients with knee disorders. The system includes three functional components: knee exercise plan formulation, exergame, and exercise feedback. The 3D Human Pose Estimation based on images is used as the gesture interaction to capture the patient's primary joint motion data. We recruited 20 knee osteoarthritis (KOA) to evaluate the system's feasibility and user experience. The physician's group formulated the patient's exercise plans. The average accuracy of motion recognition is 95.2%, indicating that the system can effectively guide rehabilitation training for KOA patients. The results of the UEQ-S questionnaire, namely the practical quality value (1.63 ± 0.85), hedonic quality value (1.75 ± 0.86), and the total value (1.69 ± 0.86) of 20 patients, indicate that the system provides an excellent user experience, which improves the willingness and compliance of the patients for the active exercise. The above evidence confirms that the proposed approach is suitable for Knee disorders rehabilitation exercise and has promising application prospects.
- 26 August 2022
- Published by Springer Nature in Health Information Science and Systems
- Vol. 10 (1) , 1-10
Design and evaluation of an exergame system to assist knee disorders patients' rehabilitation based on gesture interaction
We designed a knee rehabilitation exercise game (Exergame) for home-based rehabilitation of patients with knee disorders. The system includes three functional components: knee exercise plan formulation, exergame, and exercise feedback. The 3D Human Pose Estimation based on images is used as the gesture interaction to capture the patient's primary joint motion data. We recruited 20 knee osteoarthritis (KOA) to evaluate the system's feasibility and user experience. The physician's group formulated the patient's exercise plans. The average accuracy of motion recognition is 95.2%, indicating that the system can effectively guide rehabilitation training for KOA patients. The results of the UEQ-S questionnaire, namely the practical quality value (1.63 ± 0.85), hedonic quality value (1.75 ± 0.86), and the total value (1.69 ± 0.86) of 20 patients, indicate that the system provides an excellent user experience, which improves the willingness and compliance of the patients for the active exercise. The above evidence confirms that the proposed approach is suitable for Knee disorders rehabilitation exercise and has promising application prospects.