Model reference adaptive control of heart rate during wheelchair ergometry

This study used parametric methods to identify a model of the wheelchair user's heart rate response to changes in physical workload while on a wheelchair dynamometer. A model reference adaptive control (MRAC) algorithm was developed based upon the results of the system identification process. Based upon subject's maximum speed, ten random levels from zero to maximal speed were selected to form a tracking input vector. Two autoregressive models with exogenous inputs were developed using a stepwise regression-based algorithm. Analysis of variance results imply that the model development and model validation groups were different. Linear regression was used to compare the model predicted heart rates with recorded heart rates for the validation group. The application of indirect MRAC appears to be feasible for controlling heart rate kinetics of people with paraplegia or lower limb impairments during wheelchair propulsion on a computer-controlled wheelchair dynamometer.