Pan Jing Wen, Sidarta Ananda, Wu Tsung-Lin, Kwong Wai Hang Patrick, Ong Poo Lee, Tay Matthew Rong Jie, Phua Min Wee, Chong Wei Binh, Ang Wei Tech, Chua Karen Sui Geok
Rehabilitation Research Institute of Singapore, Nanyang Technological University, Singapore, Singapore.
Department of Sports Science and Physical Education, Chinese University of Hong Kong, Hong Kong, Hong Kong SAR, China.
Front Neurosci. 2024 Jul 22;18:1425183. doi: 10.3389/fnins.2024.1425183. eCollection 2024.
This study aimed to identify and quantify the kinematic and kinetic gait deviations in post-stroke hemiplegic patients with matched healthy controls using Statistical Parametric Mapping (SPM).
Fifteen chronic stroke patients [4 females, 11 males; age 53.7 (standard deviation 12.2) years; body mass 65.4 (10.4) kg; standing height 168.5 (9.6) cm] and 15 matched healthy controls [4 females, 11 males; age 52.9 (11.7) years; body weight 66.5 (10.7) years; standing height 168.3 (8.8) cm] were recruited. In a 10-m walking task, joint angles, ground reaction forces (GRF), and joint moments were collected, analyzed, and compared using SPM for an entire gait cycle.
Generally, when comparing the stroke patients' affected (hemiplegic) and less-affected (contralateral) limbs with the control group, SPM identified significant differences in the late stance phase and early swing phase in the joint angles and moments in bilateral limbs (all < 0.005). In addition, the vertical and anteroposterior components of GRF were significantly different in various periods of the stance phase (all < 0.005), while the mediolateral component showed no differences between the two groups.
SPM was able to detect abnormal gait patterns in both the affected and less-affected limbs of stroke patients with significant differences when compared with matched controls. The findings draw attention to significant quantifiable gait deviations in the less-affected post-stroke limb with the potential impact to inform gait retraining strategies for clinicians and physiotherapists.
本研究旨在使用统计参数映射（SPM）识别并量化中风后偏瘫患者与匹配的健康对照者之间的运动学和动力学步态偏差。
招募了15名慢性中风患者[4名女性，11名男性；年龄53.7（标准差12.2）岁；体重65.4（10.4）千克；身高168.5（9.6）厘米]和15名匹配的健康对照者[4名女性，11名男性；年龄52.9（11.7）岁；体重66.5（10.7）千克；身高168.3（8.8）厘米]。在10米步行任务中，收集、分析并使用SPM比较整个步态周期的关节角度、地面反作用力（GRF）和关节力矩。
总体而言，将中风患者受影响（偏瘫）和受影响较小（对侧）的肢体与对照组进行比较时，SPM发现双侧肢体在站立后期和摆动前期的关节角度和力矩存在显著差异（均<0.005）。此外，GRF的垂直和前后分量在站立期的不同阶段存在显著差异（均<0.005），而两组之间的内外侧分量无差异。
与匹配的对照组相比，SPM能够检测到中风患者受影响和受影响较小的肢体中的异常步态模式，且存在显著差异。这些发现提醒人们注意中风后受影响较小肢体中存在的可量化步态偏差，这可能会为临床医生和物理治疗师的步态再训练策略提供参考。
