title: A pilot clinical trial on a Variable Automated Speed and Sensing Treadmill (VASST) for hemiparetic gait rehabilitation in stroke patients.
abstract: BACKGROUND
  Impairments in walking speed and capacity are common problems after stroke which may benefit from treadmill training. However, standard treadmills, are unable to adapt to the slower walking speeds of stroke survivors and are unable to automate training progression. This study tests a Variable Automated Speed and Sensing Treadmill (VASST) using a standard clinical protocol. VASST is a semi-automated treadmill with multiple sensors and micro controllers, including wireless control to reposition a fall-prevention harness, variable pre-programmed exercise parameters and laser beam foot sensors positioned on the belt to detect subject's foot positions.
  
  
  METHODS
  An open-label study with assessor blinding was conducted in 10 community-dwelling chronic hemiplegic patients who could ambulate at least 0.1 m/s. Interventions included physiotherapist-supervised training on VASST for 60 min three times per week for 4 weeks (total 12 h). Outcome measures of gait speed, quantity, balance, and adverse events were assessed at baseline, 2, 4, and 8 weeks.
  
  
  RESULTS
  Ten subjects (8 males, mean age 55.5 years, 2.1 years post stroke) completed VASST training. Mean 10-m walk test speed was 0.69 m/s (SD = 0.29) and mean 6-min walk test distance was 178.3 m (84.0). After 4 weeks of training, 70% had significant positive gains in gait speed (0.06 m/s, SD = 0.08 m/s, P = 0.037); and 90% improved in walking distance. (54.3 m, SD = 30.9 m, P = 0.005). There were no adverse events.
  
  
  CONCLUSIONS
  This preliminary study demonstrates the initial feasibility and short-term efficacy of VASST for walking speed and distance for people with chronic post-stroke hemiplegia.
authors.affiliation: Department of Rehabilitation Medicine, Tan Tock Seng Hospital Rehabilitation Centre Singapore, Singapore.
authors.forename: Karen S G
authors.initials: KS
authors.lastname: Chua
authors.affiliation: Division of Electronic and Computer Engineering, Biomedical Engineering Centre, Ngee Ann Polytechnic Singapore.
authors.forename: Johnny
authors.initials: J
authors.lastname: Chee
authors.affiliation: Department of Rehabilitation Medicine, Tan Tock Seng Hospital Rehabilitation Centre Singapore, Singapore.
authors.forename: Chin J
authors.initials: CJ
authors.lastname: Wong
authors.affiliation: Department of Rehabilitation Medicine, Tan Tock Seng Hospital Rehabilitation Centre Singapore, Singapore.
authors.forename: Pang H
authors.initials: PH
authors.lastname: Lim
authors.affiliation: Department of Rehabilitation Medicine, Tan Tock Seng Hospital Rehabilitation Centre Singapore, Singapore.
authors.forename: Wei S
authors.initials: WS
authors.lastname: Lim
authors.affiliation: Division of Electronic and Computer Engineering, Biomedical Engineering Centre, Ngee Ann Polytechnic Singapore.
authors.forename: Chuan M
authors.initials: CM
authors.lastname: Hoo
authors.affiliation: Division of Electronic and Computer Engineering, Biomedical Engineering Centre, Ngee Ann Polytechnic Singapore.
authors.forename: Wai S
authors.initials: WS
authors.lastname: Ong
authors.affiliation: Clinical Research Unit, Tan Tock Seng Hospital Singapore, Singapore.
authors.forename: Mira L
authors.initials: ML
authors.lastname: Shen
authors.affiliation: Division of Electronic and Computer Engineering, Biomedical Engineering Centre, Ngee Ann Polytechnic Singapore.
authors.forename: Wei S
authors.initials: WS
authors.lastname: Yu
keywords: automated; gait; hemiplegia; sensing; stroke; treadmill