EVALUATION OF MACHINE LEARNING AND DEEP LEARNING TECHNIQUES APPLIED IN SCI INJURY

A SYSTEMATIC REVIEW

Abstract

The application of different technologies from the 4th industrial revolution, such as the use of Machine Learning (ML) and Deep Learning (DL), increasingly permeates different domains of knowledge, ensuring greater efficiency for specialists facing the challenges of their occupations. However, in the medical and physiotherapeutic fields, one of the greatest challenges is the effective treatment of Spinal Cord Injury (SCI), making it essential to implement support systems that are catalyst vectors of the therapeutic process using Artificial Intelligence (AI) techniques, while also taking information security into consideration. Objective: To evaluate different treatment techniques and procedures for SCI that use AI techniques. Methodology: Through a systematic review using the PRISMA-P methodology, reporting a synthesis of the impact of the studies. Results: 168 studies were identified in literature, which, after the application of selection criteria, resulted in 12 (7.14%) eligible references. Conclusion: The studies point to different therapeutic interventions with the application of Brain-Machine Interfaces for use in the healthcare field, bringing challenging approaches to the heterogeneity of computer systems, sensors, and actuators.