Abstract

Research and development in the art of cycling using functional electrical stimulation (FES) of the paralysed leg muscles has been going on for around thirty years. A range of physiological benefits has been observed in clinical studies but an outstanding problem with FES-cycling is that efficiency and power output are very low. The present work had the following aims: (i) to provide a tutorial introduction to a novel framework and methods of estimation of metabolic efficiency using example data sets, and to propose benchmark measures for evaluating FES-cycling performance; (ii) to systematically review the literature pertaining specifically to the metabolic efficiency of FES-cycling, to analyse the observations and possible explanations for the low efficiency, and to pose hypotheses for future studies which aim to improve performance. We recommend the following as benchmark measures for assessment of the performance of FES-cycling: (i) total work efficiency, delta efficiency and stimulation cost; (ii) we recommend, further, that these benchmark measures be complemented by mechanical measures of maximum power output, sustainable steady-state power output and endurance. Performance assessments should be carried out at a well-defined operating point, i.e. under conditions of well controlled work rate and cadence, because these variables have a strong effect on energy expenditure. Future work should focus on the two main factors which affect FES-cycling performance, namely: (i) unfavourable biomechanics, i.e. crude recruitment of muscle groups, non-optimal timing of muscle activation, and lack of synergistic and antagonistic joint control; (ii) non-physiological recruitment of muscle fibres, i.e. mixed recruitment of fibres of different type and deterministic constant-frequency stimulation. We hypothesise that the following areas may bring better FES-cycling performance: (i) study of alternative stimulation strategies for muscle activation including irregular stimulation patterns (e.g. doublets, triplets, stochastic patterns) and variable frequency stimulation trains, where it appears that increasing frequency over time may be profitable; (ii) study of better timing parameters for the stimulated muscle groups, and addition of more muscle groups: this path may be approached using EMG studies and constrained numerical optimisation employing dynamic models; (iii) development of optimal stimulation protocols for muscle reconditioning and FES-cycle training.

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