Clinical effects of a novel deep learning-based rehabilitation application on cardiopulmonary function, dynamic and static balance, gait function, and activities of daily living in adolescents with hemiplegic cerebral palsy

Abstract

Background: Adolescents with hemiplegic cerebral palsy undergo conventional physical therapy (CPT) to improve static and dynamic balance, activities of daily living and cardiopulmonary function. To overcome this problem, we developed an innovative deep learning-based rehabilitation application (DRA) to provide a motivational and chaffed platform for such individuals. DRA evaluates the patients’ functional abilities and diagnosis an appropriate therapeutic intervention like CPT. Methods: We compared the effects of DRA and CPT on 6-minute walking test (6 MWT), Borg rating of perceived exertion scale, Berg balance scale, functional ambulation category, and modified Barthel index in adolescents with hemiplegic cerebral palsy. A convenience sample of 30 adolescents with hemiplegic cerebral palsy was randomized into either the DRA or CPT group. DRA and CPT were administered to the participants, with each session lasting 30 minutes and apportioned thrice a week for a total of 4 weeks. Results: Analysis of variance was performed and the level of significance was set at P < .05. The analysis indicated that DRA showed therapeutic effects on 6 MWT, Berg balance scale, and modified Barthel index compared to CPT. Conclusion: Our results provide evidence that DRA can improve cardiopulmonary function, balance, and activities of daily living more effectively than CPT in adolescents with hemiplegic cerebral palsy.