A motor learning-based postural intervention with a robotic trunk support trainer to improve functional sitting in...

Single-subject-research-design.

To improve seated postural control in a participant with spinal cord injury (SCI) with a robotic Trunk-Support-Trainer (TruST).

Laboratory.

TruST delivered "assist-as-needed" forces on the participant's torso during a motor learning-and-control-based intervention (TruST-intervention). TruST-assistive forces were progressed and matched to the participant's postural trunk control gains across six intervention sessions. The T-shirt test was used to capture functional improvements while dressing the upper body. Kinematics were used to compute upper body excursions (cm) and velocity (cm²), and sitting workspace area (cm²). Functional trunk dynamometry was used to examine muscle force (Kg). Surface electromyography (sEMG) was applied to measure trunk muscle activity. The Borg Rating of Perceived Exertion (RPE) was used to monitor physical exertion during TruST-intervention. A two-standard-deviation bandwidth method was adopted for data interpretation.

After TruST-intervention, the participant halved the time needed to don and doff a T-shirt, increased muscle force of trunk muscles (mean = 3 kg), acquired a steadier postural sitting control without vision (mean excursion baseline: 76.0 ± 2 SD = 5.25 cm and post-intervention: 44.1 cm; and mean velocity baseline: 3.0 ± 2 SD = 0.2 cm/s and post-intervention: 1.8 cm/s), and expanded his sitting workspace area (mean baseline: 36.7 ± 2 SD = 36.6 cm² and post-intervention: 419.2 cm²). The participant increased his tolerance to counteract greater TruST-force perturbations in lateral and posterior directions. Furthermore, abdominal muscle activity substantially augmented after completion of TruST-intervention across all perturbation directions.

Our data indicate a potential effectiveness of TruST-intervention to promote functional sitting in SCI.