摘要
人机智能技术是指通过协同感知、协同认知和协同决策,实现人类与机器的交互与协同,在高动态环境中完成复杂任务,充分发挥人类与机器的优势互补。近年来,在康复医学领域,借助数字感知、人机交互、状态可视化和智能决策等关键技术,突破了传统人工康复和机器康复范式中对经验依赖与时空限制的局限,推动康复模式从被动干预向主动参与转变,实现了康复的个性化与周期化,显著提升了患者功能恢复效率与生活质量。该文围绕人机智能康复技术的国内外研究现状,从关键技术和典型应用两方面进行综述。重点探讨感知、交互、可视化和决策等核心技术,分析人工康复、机器康复和人机康复三种范式的特点,并按康复亚专科分类综述典型应用,最后对人机智能康复技术的应用挑战与未来发展进行展望。
Human-machine intelligent technology enables interaction and collaboration between humans and machines through collaborative perception,cognition,and decision-making,facilitating the execution of complex tasks in dynamic environments while leveraging the complementary strengths of both.In recent years,advancements in digital sensing,human-machine interaction,state visualization,and intelligent decision-making have overcome the limitations of traditional manual and machine-based rehabilitation paradigms,such as reliance on empirical knowledge and spatial-temporal constraints.This has driven a transformation in rehabilitation approaches,shifting from passive intervention to active patient engagement,enabling personalized and cyclic rehabilitation,and significantly improving functional recovery efficiency and quality of life.This review analyzes global research progress in human-machine intelligent rehabilitation technology,focusing on core technologies(perception,interaction,visualization,and decision-making)and three rehabilitation paradigms(manual,machine-based,and human-machine collaborative).Typical applications are categorized by rehabilitation subspecialties.Finally,challenges and future directions for the implementation of human-machine intelligent rehabilitation technology are discussed.
作者
程洪
黄宗海
张静婷
邹朝彬
宋广奎
穆逢君
Cheng Hong;Huang Zonghai;Zhang Jingting;Zou Chaobin;Song Guangkui;Mu Fengjun(School of Automation Engineering,University of Electronic Science and Technology of China,Chengdu 611731,China)
出处
《数字医学与健康》
2025年第4期280-292,共13页
DIGITAL MEDICINE AND HEALTH
基金
国家自然科学基金(62403104,62303092)。
关键词
人工智能
人机交互
康复机器人
数字孪生
康复评估可视化
智能决策
Artificial intelligenece
Human-machine interaction
Rehabilitation robotics
Digital twin
Real-time state visualization in rehabilitation assessment
Intelligent decision systems
作者简介
通信作者:程洪,Email:hcheng@uestc.edu.cn。
