title: Controlling patient participation during robot-assisted gait training.
abstract: BACKGROUND
  The overall goal of this paper was to investigate approaches to controlling active participation in stroke patients during robot-assisted gait therapy. Although active physical participation during gait rehabilitation after stroke was shown to improve therapy outcome, some patients can behave passively during rehabilitation, not maximally benefiting from the gait training. Up to now, there has not been an effective method for forcing patient activity to the desired level that would most benefit stroke patients with a broad variety of cognitive and biomechanical impairments.
  
  
  METHODS
  Patient activity was quantified in two ways: by heart rate (HR), a physiological parameter that reflected physical effort during body weight supported treadmill training, and by a weighted sum of the interaction torques (WIT) between robot and patient, recorded from hip and knee joints of both legs. We recorded data in three experiments, each with five stroke patients, and controlled HR and WIT to a desired temporal profile. Depending on the patient's cognitive capabilities, two different approaches were taken: either by allowing voluntary patient effort via visual instructions or by forcing the patient to vary physical effort by adapting the treadmill speed.
  
  
  RESULTS
  We successfully controlled patient activity quantified by WIT and by HR to a desired level. The setup was thereby individually adaptable to the specific cognitive and biomechanical needs of each patient.
  
  
  CONCLUSIONS
  Based on the three successful approaches to controlling patient participation, we propose a metric which enables clinicians to select the best strategy for each patient, according to the patient's physical and cognitive capabilities. Our framework will enable therapists to challenge the patient to more activity by automatically controlling the patient effort to a desired level. We expect that the increase in activity will lead to improved rehabilitation outcome.
authors.affiliation: Sensory-Motor Systems Lab, Department of Mechanical Engineering and Process Engineering, ETH Zurich, Switzerland. koenig@mavt.ethz.ch
authors.forename: Alexander
authors.initials: A
authors.lastname: Koenig
authors.forename: Ximena
authors.initials: X
authors.lastname: Omlin
authors.forename: Jeannine
authors.initials: J
authors.lastname: Bergmann
authors.forename: Lukas
authors.initials: L
authors.lastname: Zimmerli
authors.forename: Marc
authors.initials: M
authors.lastname: Bolliger
authors.forename: Friedemann
authors.initials: F
authors.lastname: Müller
authors.forename: Robert
authors.initials: R
authors.lastname: Riener
mesh_terms: D000328:Adult; D004594:Electrophysiology / Q000379:methods; D005080:Exercise Test / Q000295:instrumentation / Q000379:methods*; D005081:Exercise Therapy / Q000295:instrumentation / Q000379:methods*; D005260:Female; D005684:Gait; D020233:Gait Disorders, Neurologic / Q000534:rehabilitation; D006339:Heart Rate / Q000502:physiology; D006801:Humans; D008297:Male; D008875:Middle Aged; D009043:Motor Activity / Q000502:physiology*; D010358:Patient Participation; D012371:Robotics; D000071939:Stroke Rehabilitation; D016896:Treatment Outcome