Selective neural stimulation methods improve cycling exercise performance after spinal cord injury: a case series

Exercise after paralysis can help prevent secondary health complications, but achieving adequate exercise volumes and intensities is difficult with loss of motor control. Existing electrical stimulation-driven cycling systems involve the paralyzed musculature but result in rapid force decline and muscle fatigue, limiting their effectiveness. This study explores the effects of selective stimulation patterns delivered through multi-contact nerve cuff electrodes on functional exercise output, with the goal of increasing work performed and power maintained within each bout of exercise.

Three people with spinal cord injury and implanted stimulation systems performed cycling trials using conventional (S-Max), low overlap (S-Low), low duty cycle (C-Max), and/or combined low overlap and low duty cycle (C-Low) stimulation patterns. Outcome measures include total work (W), end power (P_end), power fluctuation indices (PFI), charge accumulation (Q), and efficiency (η). Mann-Whitney tests were used for statistical comparisons of W and P_end between a selective pattern and S-Max. Welch's ANOVAs were used to evaluate differences in PFIs among all patterns tested within a participant (n ≥ 90 per stimulation condition).

At least one selective pattern significantly (p < 0.05) increased W and P_end over S-Max in each participant. All selective patterns also reduced Q and increased η compared with S-Max for all participants. C-Max significantly (p < 0.01) increased PFI, indicating a decrease in ride smoothness with low duty cycle patterns.

Selective stimulation patterns can increase work performed and power sustained by paralyzed muscles prior to fatigue with increased stimulation efficiency. While still effective, low duty cycle patterns can cause inconsistent power outputs each pedal stroke, but this can be managed by utilizing optimized stimulation levels. Increasing work and sustained power each exercise session has the potential to ultimately improve the physiological benefits of stimulation-driven exercise.