TY - JOUR AU - Wang, Xiaoyi AU - Fu, Yan AU - Ye, Bing AU - Babineau, Jessica AU - Ding, Yong AU - Mihailidis, Alex PY - 2022 DA - 2022/6/13 TI -基于技术的中风患者上肢活动补偿评估与检测:JO - J Med Internet Res SP - e34307 VL - 24 IS - 6kw -卒中KW -上肢康复KW - UE康复KW -补偿KW -评估KW -技术KW -传感器KW -人工智能KW - AI AB -背景:上肢(UE)损伤影响高达80%的中风幸存者，占出院后康复的大部分。补偿是脑卒中幸存者在UE康复过程中常用的方法，用于适应运动功能的丧失，可能会阻碍康复过程的长期进行，并导致新的骨科问题。在康复过程中，对代偿运动的密切监测对于改善功能预后至关重要。目的:本文综述了基于技术的方法在脑卒中UE康复过程中如何应用于评估和检测补偿。方法:我们进行了广泛的数据库搜索。所有研究都由两名审稿人(XW和YF)独立筛选，第三名审稿人(by)参与解决差异。最终纳入的研究根据其与临床量表相关性的临床证据水平进行评级(具有相同的任务或相同的评价标准)。一位审稿人(XW)提取了关于出版物、人口统计信息、薪酬类型、用于薪酬评估的传感器、薪酬测量和统计或人工智能方法的数据。准确性由另一位审稿人(YF)检查。 Four research questions were presented. For each question, the data were synthesized and tabulated, and a descriptive summary of the findings was provided. The data were synthesized and tabulated based on each research question. Results: A total of 72 studies were included in this review. In all, 2 types of compensation were identified: disuse of the affected upper limb and awkward use of the affected upper limb to adjust for limited strength, mobility, and motor control. Various models and quantitative measurements have been proposed to characterize compensation. Body-worn technology (25/72, 35% studies) was the most used sensor technology to assess compensation, followed by marker-based motion capture system (24/72, 33% studies) and marker-free vision sensor technology (16/72, 22% studies). Most studies (56/72, 78% studies) used statistical methods for compensation assessment, whereas heterogeneous machine learning algorithms (15/72, 21% studies) were also applied for automatic detection of compensatory movements and postures. Conclusions: This systematic review provides insights for future research on technology-based compensation assessment and detection in stroke UE rehabilitation. Technology-based compensation assessment and detection have the capacity to augment rehabilitation independent of the constant care of therapists. The drawbacks of each sensor in compensation assessment and detection are discussed, and future research could focus on methods to overcome these disadvantages. It is advised that open data together with multilabel classification algorithms or deep learning algorithms could benefit from automatic real time compensation detection. It is also recommended that technology-based compensation predictions be explored. SN - 1438-8871 UR - //www.mybigtv.com/2022/6/e34307 UR - https://doi.org/10.2196/34307 UR - http://www.ncbi.nlm.nih.gov/pubmed/35699982 DO - 10.2196/34307 ID - info:doi/10.2196/34307 ER -