| Autor: |
Jiang Chen, Shuying Zhao, Huaning Meng, Xu Cheng, Wenjun Tan |
| Jazyk: |
angličtina |
| Rok vydání: |
2022 |
| Předmět: |
|
| Zdroj: |
Frontiers in Physiology, Vol 13 (2022) |
| Druh dokumentu: |
article |
| ISSN: |
1664-042X |
| DOI: |
10.3389/fphys.2022.1028907 |
| Popis: |
Currently, cardiovascular and cerebrovascular diseases have become serious global health problems related to their high incidence and fatality rate. Some patients with cardiovascular cerebro-cardiovascular diseases even may face motor or cognitive dysfunction after surgery. In recent years, human–computer interactive systems with artificial intelligence have become an important part of human well-being because they enable novel forms of rehabilitation therapies. We propose an interactive game utilizing real-time skeleton-based hand gesture recognition, which aims to assist rehabilitation exercises by improving the hand-eye coordination of the patients during a game-like experience. For this purpose, we propose a lightweight residual graph convolutional architecture for hand gesture recognition. Furthermore, we designed the whole system using the proposed gesture recognition module and some third-party modules. Finally, some participants were invited to test our system and most of them showed an improvement in their passing rate of the game during the test process. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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