title: New quantitative and qualitative measures on functional mobility prediction for stroke patients.
abstract: The purpose of this study was to explore whether we could provide supportive laboratory evidence for clinical observations that a stroke patient has lost functional mobility/locomotion capability based on dynamic balance responses (centre of pressure, COP sway patterns) and motor control activities (EMG patterns) during the motor task of sit-to-stand. A computerized controlled dynamic postural control assessment system was developed and used in this study. Various dynamic balance indices were introduced and derived from COP sway patterns expressed in four domains (i.e. space, time, force, and frequency). Motor control was assessed by multi-channel surface electromyography of each side of the lower limb during the same motor task. The functional mobility capability was evaluated using a traditional FIM method. Fourteen stroke patients with right hemiplegia and nine healthy elderly were recruited as the experimental and control groups respectively. Muscle activity was recorded for quadriceps, hamstrings, anterior tibialis, and triceps surae muscles and used for analysis. Centre of pressure sway patterns and ground reaction forces were registered. All signals were synchronized at 'seat-off'. Surface electromyographic patterns of activities recorded during sit-to-stand and dynamic balance indices computed from centre of pressure sway patterns were categorized and compared with the functional mobility scores. The results show that both the motor control patterns and dynamic balance indices correlated well to the extent of mobility impairment evaluated using the traditional FIM method. An important conclusion for rehabilitation medicine is that the functional mobility capability of stroke patients may be quantified analytically using dynamic balance indices and visualized graphically through EMG motor patterns.
authors.affiliation: Department of Mechanical Engineering, Chang Gung University, Taiwan.
authors.forename: M Y
authors.initials: MY
authors.lastname: Lee
authors.forename: M K
authors.initials: MK
authors.lastname: Wong
authors.forename: F T
authors.initials: FT
authors.lastname: Tang
authors.forename: P T
authors.initials: PT
authors.lastname: Cheng
authors.forename: W K
authors.initials: WK
authors.lastname: Chiou
authors.forename: P S
authors.initials: PS
authors.lastname: Lin
mesh_terms: D000203:Activities of Daily Living; D000328:Adult; D000368:Aged; D002561:Cerebrovascular Disorders / Q000503:physiopathology* / Q000534:rehabilitation; D003199:Computer Systems; D004576:Electromyography; D005260:Female; D005544:Forecasting; D006429:Hemiplegia / Q000503:physiopathology; D006801:Humans; D007866:Leg / Q000502:physiology; D008124:Locomotion / Q000502:physiology*; D008297:Male; D008875:Middle Aged; D009048:Motor Skills / Q000502:physiology; D009069:Movement Disorders / Q000503:physiopathology; D018482:Muscle, Skeletal / Q000503:physiopathology; D004856:Postural Balance / Q000502:physiology; D011187:Posture / Q000502:physiology; D011312:Pressure; D012678:Sensation Disorders / Q000503:physiopathology; D012815:Signal Processing, Computer-Assisted; D013314:Stress, Mechanical; D013997:Time Factors; D016474:Weight-Bearing / Q000502:physiology