Study on the effect of rehabilitation therapy based on deep learning on functional recovery of stroke patients with hemiplegia

Abstract

Objective: Based on deep learning, to explore the clinical effect of early rehabilitation intervention management model on the recovery of neurological function in patients with acute stroke. Methods: A total of 86 inpatients in our department from June 2019 to August 2020 were selected. According to the ward distribution, the hospital was randomly divided into routine drug treatment group (control group, 44 cases) and another ward was divided into early comprehensive rehabilitation treatment group (treatment group, 42 cases). The treatment group received regular rehabilitation training in addition to clinical medication, while the control group received clinical medication and self-exercise without guidance. They were evaluated 24 hours before treatment and 7-10 weeks after treatment. The motor function was evaluated by Furl—Meyer motor function integral method (FMA), and the daily living ability was scored by Barthel index. Results: There was no significant difference in Barthel index and FMA score between the treatment group and the control group before treatment. After treatment, the two indexes in the control group improved to a certain extent, but compared with the treatment group, the improvement degree was far less than that in the treatment group, and the difference was statistically significant (P < 0.01). The effective rate and total effective rate in the treatment group were significantly higher than those in the control group, with statistical difference between the two groups (P<0.05). Conclusion: Early rehabilitation intervention management model can effectively improve the neurological function of patients with acute stroke and improve the clinical efficacy, which is worthy of further promotion and use in clinical practice.