目的 上肢康复机器人是辅助上肢受伤患者开展康复训练的关键产品,秉持用户需求导向原则,综合患者、医护人员、设备运维人员三类上肢康复机器人产品核心用户群体需求,旨在精准设计出提升用户体验的产品。方法 以用户体验设计的层次理论为视角,借助问卷调研等手段,系统梳理上肢康复机器人用户的需求状况,进而构建与之相适配的指标体系。同时借助KANO模型对用户群体进行属性归类,完成用户需求的优先级排序。结果 在此基础上,引入质量功能展开(QFD)方法,将抽象的用户需求转化为具体的设计要素,以实现对上肢康复医疗机器人的精细化设计优化。结论 研究确立了科学严谨的上肢康复医疗机器人需求分析框架,建构了“工业工程-交互情感-智能算法”的QFD指标体系,针对产品系统的“鲁棒性”设计了检验方法,为上肢康复医疗机器人实现从机械化辅助到智能化陪伴的跨越夯实基础,也为同类型产品的后续开发提供了新思路。
Abstract
Upper limb rehabilitation robots are pivotal devices for assisting patients with upper limb injuries in performing rehabilitation training. Guided by the principle of user demand orientation, the work aims to integrate the demands of three core user groups, including patients, medical staff, and equipment operation and maintenance personnel, to achieve a precisely designed product that enhances the target users' experience. From the perspective of the hierarchical theory of user experience design, the user demands for upper limb rehabilitation robots were systematically sorted out through methods such as questionnaire surveys and subsequently a corresponding evaluation indicator system was constructed. Furthermore, the KANO model was employed to categorize user demands and prioritize them based on their attributes. On this basis, the Quality Function Deployment (QFD) method was introduced to translate abstract user demands into concrete design elements, enabling refined design and optimization of upper limb rehabilitation robots. In this study, a scientific and rigorous framework is established for demand analysis in upper limb rehabilitation robotics and a QFD-based technical indicator system encompassing industrial engineering, interactive emotional design, and intelligent algorithms is constructed. In addition, a robustness verification method is proposed for the product system. These contributions lay a solid foundation for transforming user demands into functional innovations and advancing upper limb rehabilitation robots from mechanical aids to intelligent partners. Additionally, the findings provide new insights and methodological references for the development of similar products.
关键词
上肢康复医疗机器人 /
用户需求设计 /
KANO 模型 /
质量功能展开(QFD)
Key words
medical robots for upper limb rehabilitation /
user demands /
KANO model /
Quality Function Deployment (QFD)
{{custom_sec.title}}
{{custom_sec.title}}
{{custom_sec.content}}
参考文献
[1] 张通. 中国脑卒中康复治疗指南(2011完全版)[J]. 中国康复理论与实践, 2012, 18(4): 301-318.
ZHANG T.Guidelines for Rehabilitation Treatment of Stroke in China (2011 Full Edition)[J]. Chinese Journal of Rehabilitation Theory and Practice, 2012, 18(4): 301-318.
[2] 顾竞春, 李勤, 顾怡勤. Kano模型在区域脑卒中人群服务模式建立中的探索与实践[J]. 中国全科医学, 2018, 21(18): 2201-2208.
GU J C, LI Q, GU Y Q.Development and Regional Performance Examination of a Kano Model-Based Service Pattern for the Stroke Population: An Exploratory Study[J]. Chinese General Practice, 2018, 21(18): 2201-2208.
[3] 温红博, 刘先伟, 姜有祥. K-means聚类方法在中考标准设定中的信度分析[J]. 中国考试, 2024(8): 69-78.
WEN H B, LIU X W, JIANG Y X.Reliability Analysis of the K-Means Clustering Method in Standard Setting for Junior High School Academic Proficiency Examinations[J]. Journal of China Examinations, 2024(8): 69-78.
[4] 史静琤, 莫显昆, 孙振球. 量表编制中内容效度指数的应用[J]. 中南大学学报(医学版), 2012, 37(2): 49-52.
SHI J C, MO X K, SUN Z Q.Content Validity Index in Scale Development[J]. Journal of Central South University (Medical Science), 2012, 37(2): 49-52.
[5] 黄品高, 黄剑平, 黄博俊, 等. 实现下肢假肢智能仿生控制的神经功能重建及行走意图识别方法[J]. 中国科学基金, 2021, 35(S1): 227-235.
HUANG P G, HUANG J P, HUANG B J, et al.Neural Function Reconstruction and Walking Intention Recognition Method for Realizing Intelligent Bionic Control of Lower Limb Prosthesis[J]. Bulletin of National Natural Science Foundation of China, 2021, 35(S1): 227-235.
[6] 龚兴若, 孔亚敏, 马丙祥. 上肢外骨骼机器人在儿童脑性瘫痪中的研究和应用进展[J]. 中国康复医学杂志, 2024, 39(3): 436-442.
GONG X R, KONG Y M, MA B X.Research and Application Progress of Upper Limb Exoskeleton Robot in Children with Cerebral Palsy[J]. Chinese Journal of Rehabilitation Medicine, 2024, 39(3): 436-442.
[7] 张洪峰, 焦永亮, 李博, 等. 人工智能在康复辅助技术中的应用研究进展与趋势[J]. 科学技术与工程, 2022, 22(27): 11751-11760.
ZHANG H F, JIAO Y L, LI B, et al.Research Progress and Trend of Artificial Intelligence in Rehabilitation Assistive Technology[J]. Science Technology and Engineering, 2022, 22(27): 11751-11760.
[8] 蔡礼彬, 陈正. 基于KANO和QFD的青岛世界园艺博览会服务品质研究[J]. 经济管理, 2015, 37(1): 129-138.
CAI L B, CHEN Z.Research on Service Quality of 2014 Qingdao International Horticultural Exposition Based on KANO and QFD[J]. Economic Management Journal, 2015, 37(1): 129-138.
[9] 秦岩丁, 范迦得, 张浩琦, 等. 气动人工肌肉驱动的上肢康复外骨骼机器人设计与控制[J]. 机械工程学报, 2025, 61(3): 225-236.
QIN Y D, FAN J D, ZHANG H Q, et al.Design and Control of a Pneumatic Artificial Muscle Actuated Exoskeleton Robot for Upper Limb Rehabilitation[J]. Journal of Mechanical Engineering, 2025, 61(3): 225-236.
[10] RAN H.Induced Charge Signal of a Glass RPC Detector[J]. Chinese Physics C, 2014, 38(4): 046002.
[11] 蒋红斌, 李青霞. 新型抗菌不锈钢材料在乡村养蜂产品设计中的应用研究[J]. 装饰, 2021(6): 86-89.
JIANG H B, LI Q X.Research on the Application of New Antibacterial Stainless Steel in the Design of Rural Beekeeping Products[J]. Zhuangshi, 2021(6): 86-89.
[12] 陆继翔, 张琪培, 杨志宏, 等. 基于CNN-LSTM混合神经网络模型的短期负荷预测方法[J]. 电力系统自动化, 2019, 43(8): 131-137.
LU J X, ZHANG Q P, YANG Z H, et al.Short-Term Load Forecasting Method Based on CNN-LSTM Hybrid Neural Network Model[J]. Automation of Electric Power Systems, 2019, 43(8): 131-137.
[13] 谭荣斌, 鲁守银, 徐伟杰, 等. 基于人机交互的上肢外骨骼训练康复机器人路径规划[J]. 制造业自动化, 2022, 44(11): 58-63.
TAN R B, LU S Y, XU W J, et al.Path Planning of Upper Limb Exoskeleton Training Rehabilitation Robot Based on Human-Computer Interaction[J]. Manufacturing Automation, 2022, 44(11): 58-63.
[14] 刘四维, 关敏, 高强. 任务导向性训练在脑卒中后偏瘫康复中的应用进展[J]. 中国康复医学杂志, 2020, 35(3): 374-378.
LIU S W, GUAN M, GAO Q.Application Progress of Task-oriented Training in Hemiplegia Rehabilitation after Stroke[J]. Chinese Journal of Rehabilitation Medicine, 2020, 35(3): 374-378.
[15] 陈琦, 沈祥胜. 基于脑机接口技术的信息可视化研究——以植物人患者康复辅助系统设计为例[J]. 装饰, 2020(2): 116-119.
CHEN Q, SHEN X S.Research on Information Visualization Based on Brain Computer Interface Technology: Taking the Design of Rehabilitation Assistant System for Vegetative Patients as an Example[J]. Zhuangshi, 2020(2): 116-119.
[16] 孙超, 苑明海, 周灼, 等. 外骨骼上肢康复机器人的结构设计与仿真研究[J]. 机电工程, 2019, 36(4): 383-386.
SUN C, YUAN M H, ZHOU Z, et al.Structural Design and Simulation Analysis of Exoskeleton Upper Limb Rehabilitation Robot[J]. Journal of Mechanical & Electrical Engineering, 2019, 36(4): 383-386.
[17] 颜海, 王昀. 智能康复产品的设计系统工程[J]. 包装工程, 2024, 45(S1): 579-587.
YAN H, WANG Y.Design System Engineering of Intelligent Rehabilitation Products[J]. Packaging Engineering, 2024, 45(S1): 579-587.
[18] 张永涛, 李炜, 程养民. Stewart六维力传感器与多节点无线通信数据采集[J]. 传感技术学报, 2025, 38(5): 780-787.
ZHANG Y T, LI W, CHENG Y M.Stewart Six-Dimensional Force Sensor and Multi-Node Wireless Communication Data Acquisition[J]. Chinese Journal of Sensors and Actuators, 2025, 38(5): 780-787.
[19] 杨青, 王晨蔚. 基于深度学习LSTM神经网络的全球股票指数预测研究[J]. 统计研究, 2019, 36(3): 65-77.
YANG Q, WANG C W.A Study on Forecast of Global Stock Indices Based on Deep LSTM Neural Network[J]. Statistical Research, 2019, 36(3): 65-77.
[20] 陈童, 王妍, 赵琦. 基于Leap Motion的中国古琴声画结合交互设计研究[J]. 文艺评论, 2014(9): 77-81.
CHEN T, WANG Y, ZHAO Q.Research on Interactive Design of Chinese Guqin Based on Leap Motion[J]. Literature and Art Criticism, 2014(9): 77-81.
[21] ZINTCHOUK D, GREGERSEN M, LAURITZEN T, et al.Geriatrician-Performed Comprehensive Geriatric Care in Older Adults Referred to a Community Rehabilitation Unit: A Randomized Controlled Trial[J]. European Journal of Internal Medicine, 2018, 51: 18-24.
[22] 刘志辉, 孙奕, 唐智, 等. 一种7自由度外骨骼上肢康复机器人设计与控制研究[J]. 东华大学学报(自然科学版), 2017, 43(4): 535-540.
LIU Z H, SUN Y, TANG Z, et al.Study on Designing and Control of 7-DoF Exoskeleton Upper-Limb Rehabilitation Robot[J]. Journal of Donghua University (Natural Science), 2017, 43(4): 535-540.
[23] 刘笑宇, 唐敏, 董英, 等. 虚拟康复的新进展: 基于力触觉反馈的上肢运动功能评估[J]. 中国科学基金, 2022, 36(2): 214-224.
LIU X Y, TANG M, DONG Y, et al.A New Progress in Virtual Rehabilitation: Assessment of Upper Limb Motor Functions Based on Haptic Feedback Technology[J]. Bulletin of National Natural Science Foundation of China, 2022, 36(2): 214-224.
[24] 袁润萍, 汤从智, 江勇, 等. 上肢康复机器人促进卒中后上肢功能恢复的作用和机制研究进展[J]. 中国脑血管病杂志, 2022, 19(7): 509-513.
YUAN R P, TANG C Z, JIANG Y, et al.Research Progress on the Effect and Mechanism of Upper Limb Rehabilitation Robot in Promoting the Functional Recovery after Stroke[J]. Chinese Journal of Cerebrovascular Diseases, 2022, 19(7): 509-513.