Control of work rate-driven exercise facilitates cardiopulmonary training and assessment during robot-assisted gait in incomplete spinal cord injury

Kenneth J Hunt, L. P. Jack, Andrew Pennycott, C Perret, M Baumberger, Tanja H Kakebeeke

Research output: Contribution to journalArticle

24 Citations (Scopus)

Abstract

Treadmill training is used for gait rehabilitation in various neurological conditions. Robot-assisted treadmill training automates repetition of the gait cycle and can reduce the load on therapists. Here we investigate the use of robot-assisted treadmill technology in cardiopulmonary rehabilitation and assessment.

Using a new approach to exercise work rate estimation and volitional control, we propose cardiopulmonary assessment protocols for robot-assisted gait exercise, designed for estimation of cardiopulmonary performance parameters. Feasibility was explored in three subjects with incomplete spinal cord injury using the Lokomat system.

Estimation and visual feedback of exercise work rate allowed all subjects to accurately follow specified work rate profiles in real time by means of volitional control. We were able to estimate the main cardiopulmonary performance parameters from constant work rate and incremental tests. “Passive” walking elicited a substantial metabolic response: on average, oxygen uptake (VO2
) was a factor of 1.8 higher than during rest. The magnitude of peak VO2
above rest, obtained from incremental tests, was a factor of 4–6 higher than the increment in VO2 for passive walking, thus emphasising the importance of the subjects’ active participation in the exercise.

Visual feedback and volitional control of estimated exercise work rate facilitates the imposition of work rate profiles for estimation of cardiopulmonary performance parameters in robot-assisted gait. This new approach could be used to guide a patient’s training regime during a cardiopulmonary rehabilitation programme, and for periodic assessment of cardiopulmonary status.
Original languageEnglish
Pages (from-to)19-28
Number of pages10
JournalBiomedical Signal Processing and Control
Volume3
Issue number1
DOIs
Publication statusPublished - 1 Jan 2008

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