title: Balance and knee extensibility evaluation of hemiplegic gait using an inertial body sensor network.
abstract: BACKGROUND
  Most hemiplegic patients have difficulties in their balance and posture control while walking because of the asymmetrical posture and the abnormal body balance. The assessment of rehabilitation of hemiplegic gait is usually made by doctors using clinical scale, but it is difficult and could not be used frequently. It is therefore needed to quantitatively analyze the characteristics of hemiplegic gait. Thus the assessment would be simple, and real-time evaluation of rehabilitation could be carried out.
  
  
  METHODS
  Twenty subjects (ten hemiplegic patients, ten normal subjects) were recruited. The subjects walked straight for five meters at their self-selected comfortable speed towards a target line on the floor.Xsens MTx motion trackers were used for acquiring gestures of body segments to estimate knee joint angles and identify gait cycles. A practical method for data acquisition that does not need to obtain accurate distances between a knee joint and its corresponding sensors is presented.
  
  
  RESULTS
  The results showed that there were significant differences between the two groups in the three nominated angle amplitudes. The mean values of balance level of each parameter in hemiplegic gait and normal gait were: 0.21 versus 0.01, 0.18 versus 0.03, and 0.92 versus 0.03, respectively. The mean values of added angles of each parameter in hemiplegic gait and normal gait were: 74.64 versus 91.31, -76.48 versus -132.4, and 6.77 versus 35.74.
  
  
  CONCLUSIONS
  It was concluded that the wearable bio-motion acquisition platform provided a practical approach that was effective in discriminating gait symptoms between hemiplegic and asymptomatic subjects. The extensibility of hemiplegic patients' lower limbs was significantly lower than that of normal subjects, and the hemiplegic gait had worse balance level compared with normal gait. The effect of rehabilitation training of hemiplegic gait could be quantitatively analyzed.
authors.affiliation: Shenzhen Institutes of Advanced Technology, The Shenzhen Key Laboratory for Low-cost Healthcare, Shenzhen University Town, 1068 Xueyuan Avenue, Shenzhen 518055, PR China. wang.lei@siat.ac.cn.
authors.forename: Yanwei
authors.initials: Y
authors.lastname: Guo
authors.forename: Guoru
authors.initials: G
authors.lastname: Zhao
authors.forename: Qianqian
authors.initials: Q
authors.lastname: Liu
authors.forename: Zhanyong
authors.initials: Z
authors.lastname: Mei
authors.forename: Kamen
authors.initials: K
authors.lastname: Ivanov
authors.forename: Lei
authors.initials: L
authors.lastname: Wang
mesh_terms: D001696:Biomechanical Phenomena; D016022:Case-Control Studies; D005260:Female; D005684:Gait / Q000502:physiology*; D006429:Hemiplegia / Q000503:physiopathology*; D006801:Humans; D007719:Knee Joint / Q000503:physiopathology*; D008297:Male; D008875:Middle Aged; D004856:Postural Balance