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一款基于实时手势识别的康复互动游戏。

An interactive game for rehabilitation based on real-time hand gesture recognition.

作者信息

Chen Jiang, Zhao Shuying, Meng Huaning, Cheng Xu, Tan Wenjun

机构信息

College of Information Science and Engineering, Northeastern University, Shenyang, China.

College of Economics and Management, Shenyang Agricultural University, Shenyang, China.

出版信息

Front Physiol. 2022 Oct 26;13:1028907. doi: 10.3389/fphys.2022.1028907. eCollection 2022.

Abstract

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.

摘要

目前,心血管疾病已成为严重的全球性健康问题,因其发病率和死亡率高。一些患有心血管疾病的患者术后甚至可能面临运动或认知功能障碍。近年来,具有人工智能的人机交互系统已成为人类福祉的重要组成部分,因为它们能够实现新型康复治疗形式。我们提出了一种利用基于实时骨架的手势识别的交互式游戏,旨在通过在类似游戏的体验中改善患者的手眼协调能力来辅助康复锻炼。为此,我们提出了一种用于手势识别的轻量级残差图卷积架构。此外,我们使用所提出的手势识别模块和一些第三方模块设计了整个系统。最后,邀请了一些参与者测试我们的系统,他们中的大多数人在测试过程中游戏通过率有所提高。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/863b/9643738/5dc04c267eb8/fphys-13-1028907-g001.jpg

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