Is robot-assisted gait less cardiorespiratory stressful or energy consuming than walking without robot-assistance?

Background. Over the years, the effects of robot-assistance on gait-related parameters have been investigated considerably. However, regarding the effects of robot-assistance on fatigue and cardiorespiratory parameters, still little is known. Aims. The objective of this review is to summarize the effects of walking with robot-assistance compared to walking without robot-assistance on fatigue and cardiorespiratory parameters. Methods. In February 2015, the electronic databases PubMed and Web of Science were searched for eligible articles. Two researchers rated methodological quality and risk of bias of the identified studies independently. Inter-rater agreement was determined by calculating Cohen’s Kappa coefficients. Results. After eligibility assessment, 13 studies were included, concerning 147 participants (77 healthy subjects, 39 stroke and 31 spinal cord injury patients), 8 different robotic devices (most commonly the Lokomat, the Gait Trainer and a bilateral ankle-foot exoskeleton), and 7 different outcome parameters (most commonly oxygen consumption, heart rate and metabolic cost). Methodological quality ranged from 50% to 65% (mean: 59% or 28.5/48) and inter-rater agreement was strong (κ = 0.80). In all studies that measured oxygen consumption (n=7), the values were in the majority of the conditions significantly lower during robot-assisted gait. Also heart rate (n=5) and metabolic cost (n=3) were significantly lower during most robot-assisted walking conditions, in all studies except one. Only 1 study assessed the Borg 0-10 scale and found less perceived fatigue during walking with robot-assistance. Summary and conclusions. In general, the results suggest that robot-assisted walking is less energy consuming and cardiorespiratory stressful than walking without robot-assistance in stroke patients, spinal cord injury patients and healthy subjects. Additional research with more homogenous studies (regarding participants, type of robot, walking conditions and outcome parameters) is needed to draw firm conclusions.