Post-stroke rehabilitation remains a significant challenge, as traditional methods like Constraint-Induced Movement Therapy and Split-Belt Treadmill training fail to address the complex neuro-muscular and biomechanical aspects of walking. These approaches often focus on symmetry and repetition, neglecting the brain's potential for adaptation and natural recovery.
Our researchers developed a novel therapy for reducing gait asymmetry for stroke survivors. It introduces multimodal rhythmic asymmetric sensory cueing, which uses controlled variability to stimulate neuroplasticity and create new neural pathways for more effective rehabilitation. In detail, the therapy combines Auditory Rhythmic Asymmetric Cueing (A-RAC) and Tactile Rhythmic Asymmetric Cueing (T-RAC) using advanced systems like the Computer-Assisted Rehabilitation Environment (CAREN). The therapy was tested in a randomized controlled study with 18 able-bodied participants simulating post-stroke conditions, with gait parameters like vertical load distribution, braking force, and propulsion asymmetries analyzed. Results showed significant improvements in balance and stability, particularly with A-RAC and combined modalities (AT), reducing fall risks and enhancing walking efficiency. Future work includes testing stroke survivors, exploring long-term effects, and integrating wearable devices and virtual reality for better outcomes. This approach underscores the importance of tailored, multimodal sensory feedback in developing effective rehabilitation strategies.
Regarding BRK, which is crucial for controlled deceleration and stability during gait termination, both A-RAC and AT showed notable effects as shown in Table 3. Note that A-RAC vs. T-RAC during adaptation just missed the required statistical significance of p < 0.005; the differences in asymmetry should be further studied. Blue means the results are statistically significant from the baseline. Red means the values are not statistically different from the baseline. Yellow means the results just missed statistical significance.