摘要
目的研究基于数字视频和数字图像处理的步态分析在卒中患者康复训练中的作用。方法选择一侧肢体偏瘫的卒中患告20例,应用基于数字视频和数字图像处理的步态分析方法,评价康复训练前及训练后3个月双侧肢体的时空参数(跨步周期、跨步长、步频、步速、站立相时间)和髋、膝、踝关节角度参数的变化。结果①20例患者训练前跨步长、步速为(0.51±0.12)m、(0.26±0.17)m/s;训练后为(0.66±0.23)m、(0.33±0.21)m/s,均P<0.05。跨步周期、步频及站立相时间训练前后差异无统计学意义。②与康复训练前比较,康复训练后患侧肢体踝关节首次着地屈曲角度明显减小;踝、髋关节站立相最大伸展角度增大;足尖离地时膝关节屈曲角度增大,踝关节伸展角度增加;迈步相膝、髋关节最大屈曲角度均增加;矢状面髋关节角度变化范围增大,踝关节角度变化范围减少。健侧肢体康复训练前后,除膝关节迈步相最大屈曲角度增加外(P<0.05),其他关节角度参数变化不明显。结论基于数字视频和数字图像处理的步态分析,有助于定量评价卒中患者的步态特征和康复治疗效果。
Objective To study the effect of gait analysis based on digital video and digital image processing in rehabilitation training in patients with stroke. Methods Twenty patients with unilateral hemiplegia after stroke were selected. Gait analysis by digital video and digital image processing were used to evaluate the parameter changes of the temporal-spatial parameters of bilateral limbs （stride circles, stride length, stride frequency, stride speed, stand phase time） and the joint （hip, knee, ankle joints） angles before and after （3 months） the rehabilitation training. Results （1）Tbe stride length and speed in 20 patients were 0.51±0. 12 m and 0.26± 0. 17 m/s before the rehabilitation training; they were 0.66 ± 0. 23 m and 0. 33 ±0. 21 m/s after the training （ P 〈0. 05 all）. There were no significant differences among the stride circles, stride frequency, and stand phase time before and after the training. （2）The flexion angle of the affected ankle joint reduced significantly when first touched ground after the rehabilitation training as compared to that before the training; the maximum extension angle of the standing phase of ankle and hip joints was increased; the flexion angle of knee joint increased at toe-off, so did the extension angle of ankle joint; the maximum flexion angles of knee and hip joints at stride phase was increased; the range of hip joint angle change in sagittal plan was increased, and that of the ankle joint angle was decreased. Before and after the rehabilitation training on the unaffected sides, there were no significant changes in other joint angle parameters, except the increased maximum flexion angle of the knee joint in stride phase （P 〈 0. 05）. Conclusion The gait analysis base on digital video and digital image processing contributes to qualitatively evaluate the gait characteristics and the efficacy of rehabilitation treatment in patients with stroke.
出处
《中国脑血管病杂志》
CAS
2009年第9期456-460,共5页
Chinese Journal of Cerebrovascular Diseases
基金
“十一五”国家科技支撑计划课题(2006BAI01A14)
关键词
卒中
康复
步态
信号处理
计算机辅助
Stroke
Rehabilitation
Gait
Signal processing, computer-assisted
