吉林大学学报(工学版) ›› 2025, Vol. 55 ›› Issue (10): 3274-3282.doi: 10.13229/j.cnki.jdxbgxb.20240066

• 计算机科学与技术 • 上一篇    

基于虚拟现实技术的肢体运动康复训练评估装置

赵剑1,2,3(),杨晨1,2,李贵海1,史丽娟3,4,匡哲君1,3()   

  1. 1.长春大学 计算机科学技术学院,长春 130022
    2.长春大学 网络空间安全学院,长春 130022
    3.人体健康状态辨识与机能增强吉林省重点实验室,长春 130022
    4.长春大学 电子信息工程学院,长春 130022
  • 收稿日期:2024-01-18 出版日期:2025-10-01 发布日期:2026-02-03
  • 通讯作者: 匡哲君 E-mail:zhaojian@ccu.edu.cn;kuangzhejun@ccu.edu.cn
  • 作者简介:赵剑(1980-),男,教授,博士.研究方向:虚拟现实、智能康复. E-mail: zhaojian@ccu.edu.cn
  • 基金资助:
    吉林省科技发展计划项目(YDZJ202303CGZH010);吉林省科技发展计划项目(YDZJ202301ZYTS496);吉林省教育厅科学技术研究规划项目(JJKH20230673KJ)

Limb movement rehabilitation training evaluation device based on virtual reality technology

Jian ZHAO1,2,3(),Chen YANG1,2,Gui-hai LI1,Li-juan SHI3,4,Zhe-jun KUANG1,3()   

  1. 1.College of Computer Science and Technology,Changchun University,Changchun 130022,China
    2.College of Cyberspace Security,Changchun University,Changchun 130012,China
    3.Jilin Provincial Key Laboratory of Human Health Status Identification Function & Enhancement,Changchun 130022,China
    4.College of Electronic Information Engineering,Changchun University,Changchun 130012,China
  • Received:2024-01-18 Online:2025-10-01 Published:2026-02-03
  • Contact: Zhe-jun KUANG E-mail:zhaojian@ccu.edu.cn;kuangzhejun@ccu.edu.cn

摘要:

针对传统肢体康复训练方法存在重复性高、个性化不足、训练数据不可视等问题,提出了一种基于虚拟现实技术的肢体康复训练评估系统。该系统以提高患者参与度、实现个性化康复方案、实时反馈和监控、保障安全性和数据分析为设计原则。本文对10名患者进行了实验,通过虚拟仿真环境,患者可以参与更具吸引力和交互性的康复训练,同时系统可根据患者的状况动态调整康复方案。此外,系统还能收集大量康复数据,为医护人员提供详细的信息,以支持治疗过程的优化和个性化调整。

关键词: 虚拟现实, 肢体康复, 体态识别, 骨骼坐标, 系统评估

Abstract:

For patients, the traditional means of physical rehabilitation training have some problems such as high repeatability, lack of individuation and invisible training data. This paper provides the design, implementation and effect evaluation of a physical rehabilitation training evaluation system based on virtual reality technology. The system is designed on the principles of improved patient engagement, personalized rehabilitation, real-time feedback and monitoring, safety and data analysis. This paper conducted experiments on 10 patients. Through virtual simulation environment, patients can participate in more attractive and interactive rehabilitation training, and the system can dynamically adjust rehabilitation programs according to patients' conditions. In addition, the system can also collect a large amount of rehabilitation data, providing detailed information for medical staff to support the optimization and personalized adjustment of the treatment process.

Key words: virtual reality, limb rehabilitation, body recognition, bone coordinates, system evaluation

图1

系统框架结构图"

图2

肢体康复训练评估仪"

图3

Kinect 2.0技术路线图"

图4

采集数据和虚拟场景之间的交互"

图5

9种专项训练"

图6

躯干-屈曲训练"

图7

人体各关节点"

图8

康复训练可视化数据汇总"

图9

与上次对比准确度"

图10

服务器后台患者数据"

表1

参与者信息"

参与者ID性别年龄/岁其他病史烧伤程度能否自主训练
125中度可以
240中度可以
334中度可以
438中度可以
529中度可以
631中度可以
740中度可以
842中度可以
926中度可以
1030中度可以

图11

对照组和实验组进行康复训练前的动作标准度"

图12

对照组和实验组进行康复训练后的动作标准度"

图13

每天无聊感总分"

图14

每天注意力不集中总分"

图15

每天能跟上节奏的总分"

[1] Levac D, Colquhoun H, O'Brien K K. Scoping studies: advancing the methodology[J]. Implementation science, 2015, 5(1): No.69.
[2] Merians A S, Jack D, Boian R, et al. Virtual reality-augmented rehabilitation for patients following stroke[J]. Physical Therapy, 2002, 82(9): 898-915.
[3] Holden M. K. Virtual environments for motor rehabilitation: review[J]. Cyberpsychology & Behavior, 2005, 8(3): 187-211.
[4] Lohse K R, Lang C E, Boyd L A. Is more better? using metadata to explore dose-response relationships in stroke rehabilitation[J]. Stroke, 2014, 45(7): 2053-2058.
[5] Laver K E, Schoene D, Crotty M, et al. Telerehabilitation services for stroke[J]. The Cochrane Database of Systematic Reviews, 2020,1(1): No.CD010255.
[6] Barclay-Goddard R, Stevenson T. J. The impact of exercise in community-dwelling individuals with Alzheimer's disease: a meta-analysis[J]. Australasian Journal on Ageing, 2014, 33(2): 106-113.
[7] Laver K E, George S, Thomas S, et al. Virtual reality for stroke rehabilitation[J]. Cochrane Database of Systematic Reviews, 2025, 5(6): No.CD008349.
[8] Clark R A, Pua Y H, Bryant A L, et al. Validity of the Microsoft Kinect for providing lateral trunk lean feedback during gait retraining[J]. Gait & posture, 2013, 38(4): 1064-1066.
[9] Deutsch J E, Borbely M, Filler J, et al. Use of a low-cost, commercially available gaming console (wii) for rehabilitation of an adolescent with cerebral palsy[J]. Physical Therapy, 2008, 88(10): 1196-1207.
[10] Lange B, Koenig S, Chang C Y, et al. Designing informed game-based rehabilitation tasks leveraging advances in virtual reality[J]. Disability and Rehabilitation, 2012, 34(22): 1863-1870.
[11] Cameirão M S, Badia S B I, Oller E D, et al. Neurorehabilitation using the virtual reality-based rehabilitation gaming system: methodology[J]. Journal of Neuro-Engineering and Rehabilitation, 2012, 9(1): 1-9.
[12] Da Silva Cameirão M, Bermúdez I B S, Duarte E, et al. Virtual reality-based rehabilitation speeds up functional recovery of the upper extremities after stroke: a randomized controlled pilot study in the acute phase of stroke using the rehabilitation gaming system[J]. European Journal of Physical and Rehabilitation Medicine, 2011, 47(2): 223-232.
[13] Lloréns R, Noé E, Colomer C, et al. Balance recovery through virtual stepping exercises using Kinect skeleton tracking: a follow-up study with chronic stroke patients[J]. Studies in Health Technology and Informatics, 2015, 217: 919-925.
[14] Levac D E, Glegg S M, Sveistrup H, et al. Promoting therapists' use of motor learning strategies within virtual reality-based stroke rehabilitation[J]. PloS one, 2016, 11(12):No.e0168311.
[15] Sveistrup H. Motor rehabilitation using virtual reality[J]. Journal of NeuroEngineering and Rehabilitation, 2004, 1(1): 1-10.
[16] Oblak J, Cikajlo I, Matjačić Z. Universal haptic drive: a robot for arm and hand rehabilitation[J]. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2013, 21(3): 506-515.
[17] Prochnow D, Bermúdez I B S, Schmidt J, et al. A functional magnetic resonance imaging study of visuomotor processing in a virtual reality-based paradigm: Rehabilitation gaming system[J]. European Journal of Neuroscience, 2013, 37(9): 1441-1447.
[18] Borghese N A, Pirovano M, Lanzi P L, et al. Feasibility and preliminary efficacy of a telerehabilitation approach in stroke patients[J]. Games for Health Journal, 2013, 2(5): 318-324.
[19] Shin J H, Kim M Y, Lee J Y, et al. Effective game-based virtual reality using Xbox Kinect on balance, gait, and cognitive function in individuals with Parkinson's disease: a randomized controlled trial[J]. Journal of Neuroengineering and Rehabilitation, 2013, 10(1): 1-11.
[20] Webster D, Celik O, Popa D O. Exergame design for robotic stroke rehabilitation[C]∥Proceedings of the Conference on Interactive Entertainment, 2014: 1-8.
[21] Bonnechère B, Jansen B, Omelina L, et al. The use of commercial video games in rehabilitation: a systematic review[J]. International Journal on Disability and Human Development, 2014, 13(4): 395-405.
[22] Dutta A, Jacob A, Nair S. A game theoretic framework for analyzing Kinect based stroke rehabilitation system[C]∥IEEE 15th International Conference on e-Health Networking, Applications and Services (Healthcom), Visby, Sweden, 2013: 330-334.
[23] Weiss P L, Rand D. Virtual reality in neurorehabilitation[J]. Journal of Clinical & Diagnostic Research, 2024,18(Sup.): No.41
[24] Chen C, Jeng M C, Fung C P, et al. The effectiveness of an interactive virtual reality game system in patients with unilateral neglect following stroke[J]. The American Journal of Occupational Therapy, 2014, 68(6): 653-662.
[25] Int. J. Mol. Burns: classification, pathophysiology, and treatment: a review[J]. International Journal of Molecular Sciences, 2023, 24(4): No.3749.
[26] Lijuan S, Feng L, Yuan L, et al. Biofeedback respiratory rehabilitation training system based on virtual reality technology[J]. Sensors, 2023, 23(22): No. 9025.
[27] DeVellis R. F. Scale Development: Theory and Applications[M]. Thousand Oaks: Sage Publications,2017.
[28] Shotton J, Fitzgibbon A, Cook M, et al. Real-time human pose recognition in parts from single depth images[J]. Communications of the ACM, 2013, 56(1): 116-124.
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