Pauk Jolanta, Minta-Bielecka Katarzyna
Białystok University of Technology, Białystok, Poland.
Glenrose Rehabilitation Hospital, Edmonton, Canada.
Acta Bioeng Biomech. 2016;18(4):33-40.
Hemiplegia is a paralysis on one side of the body resulting from disease or injury to the motor centers of the brain that may lead to difficulty in walking and problems in balance. A new methodology for hemiplegia gait patterns classification based on bicluster analysis, which aims to identify a group of patients with similar gait patterns, and verify if spatial-temporal gait parameters are correlated with the Barthel Index, has been proposed.
Eighteen hemiplegia patients were recruited. Measurements included spatialtemporal gait parameters and joint moments. Gait data were measured using a motion tracking system and two force platforms. Bicluster analysis was used to classify the subjects' gait patterns. The relation between Barthel Index and spatial-temporal gait parameters was determined based on the Spearman correlation.
A high correlation between spatial-temporal gait parameters and Barthel Index (r>0.5, p <0.05) was observed. Well-separated biclusters presenting similarity among the lower limb joints during the gait cycles were obtained from the data.
Bicluster analysis can be useful for identifying patients with similar gait patterns. The relation between the gait patterns and the underlying impairments would allow clinicians to target rehabilitation strategies at the patient's individual needs.
偏瘫是由脑部运动中枢的疾病或损伤导致的身体一侧瘫痪，可能会导致行走困难和平衡问题。本文提出了一种基于双聚类分析的偏瘫步态模式分类新方法，旨在识别一组具有相似步态模式的患者，并验证时空步态参数是否与巴氏指数相关。
招募了18名偏瘫患者。测量包括时空步态参数和关节力矩。使用运动跟踪系统和两个测力平台测量步态数据。采用双聚类分析对受试者的步态模式进行分类。基于斯皮尔曼相关性确定巴氏指数与时空步态参数之间的关系。
观察到时空步态参数与巴氏指数之间存在高度相关性（r>0.5，p<0.05）。从数据中获得了在步态周期中下肢关节之间呈现相似性的明显分离的双聚类。
双聚类分析有助于识别具有相似步态模式的患者。步态模式与潜在损伤之间的关系将使临床医生能够根据患者的个体需求制定康复策略。
