A biofeedback cycling training to improve locomotion: a case series study based on gait pattern classification of 153 chronic stroke patients

Abstract

BackgroundThe restoration of walking ability is the main goal of post-stroke lower limb rehabilitation and different studies suggest that pedaling may have a positive effect on locomotion. The aim of this study was to explore the feasibility of a biofeedback pedaling treatment and its effects on cycling and walking ability in chronic stroke patients. A case series study was designed and participants were recruited based on a gait pattern classification of a population of 153 chronic stroke patients.MethodsIn order to optimize participants selection, a k-means cluster analysis was performed to subgroup homogenous gait patterns in terms of gait speed and symmetry.The training consisted of a 2-week treatment of 6 sessions. A visual biofeedback helped the subjects in maintaining a symmetrical contribution of the two legs during pedaling. Participants were assessed before, after training and at follow-up visits (one week after treatment). Outcome measures were the unbalance during a pedaling test, and the temporal, spatial, and symmetry parameters during gait analysis.Results and discussionThree clusters, mainly differing in terms of gait speed, were identified and participants, representative of each cluster, were selected.An intra-subject statistical analysis (ANOVA) showed that all patients significantly decreased the pedaling unbalance after treatment and maintained significant improvements with respect to baseline at follow-up. The 2-week treatment induced some modifications in the gait pattern of two patients: one, the most impaired, significantly improved mean velocity and increased gait symmetry; the other one reduced significantly the over-compensation of the healthy limb. No benefits were produced in the gait of the last subject who maintained her slow but almost symmetrical pattern. Thus, this study might suggest that the treatment can be beneficial for patients having a very asymmetrical and inefficient gait and for those that overuse the healthy leg.ConclusionThe results demonstrated that the treatment is feasible and it might be effective in translating progresses from pedaling to locomotion. If these results are confirmed on a larger and controlled scale, the intervention, thanks to its safety and low price, could have a significant impact as a home- rehabilitation treatment for chronic stroke patients.

The Application of Cycling and Cycling Combined with Feedback in the Rehabilitation of Stroke Patients: A Review

“…Regarding stroke phases, cycling exercise has been applied in subacute 4,14,40,43,45 and chronic 7,17,18,26,27,[29][30][31][46][47][48]51,52 phase patients. The majority of the studies considered the time after stroke as an inclusion criterion; others 3,40,43,49 did not.…”

“…Different therapies have been used together with cycling leg exercise to improve cycling's potential as a rehabilitation method, such as limb-load cycling, 4,7 functional electrical stimulation (FES), [8][9][10][11][12][13][14] and feedback. 7,[15][16][17][18][19] However, first, it is important to clarify several issues before the use of cycling as a rehabilitation method, such as the similarities and differences between cycling and walking, the advantages and limitations of cycling leg exercise when compared with walking on the rehabilitation of motor impairments, and the type of stroke patients, which may benefit from cycling therapies. Moreover, information about the type of purposes where cycling leg exercise can be used, the applied protocols as well as the tools used to assess the state and the recovery of patients, are important to analyze the potential of cycling as a rehabilitation method.…”

Rehabilitation of Walking After Stroke

“…Ferrante performed a cluster analysis to first group subjects based on symmetry and speed of walking, and performed a cycling task to improve symmetry [37]. Results suggest that a larger study on a more targeted population would be appropriate for further investigation, and that biofeedback as a treatment should be considered as a relatively low cost additive to physical therapy practice to improve lower extremity function.…”

An Adaptive Real-Time Algorithm to Detect Gait Events Using Inertial Sensors

“…Thus, the detection of temporal gait parameters is crucial for monitoring or assessment purposes [1]. A real-time detection of gait temporal parameters, such as the initial contact (IC) and end contact (EC), is also needed to develop goal-oriented rehabilitation treatments based on biofeedback [2] or on Functional Electrical Stimulation (FES) [3,4].…”