Background: Low back pain is an extremely prevalent issue with an extensive impact, ranging from decreased quality of life to lost years of productivity. Many interventions have been developed to alleviate chronic lower back pain, yet it remains a widespread problem. The objective of this study was to examine the role of artificial intelligence guided resistance training relative to clinical variables in subjects experiencing lower back pain.
Methods: 69 out of 108 enrolled and 92 accrued subjects completed the 8-week intervention. Subjects were randomized into four groups (Control, Training, Clinical, or Combined). The Training cohort received supervised artificial-intelligence-guided core-focused resistance training while the Clinical group received clinical care. The Combined group received both clinical care and artificial-intelligence-guided training and the Control group received no treatment. Participants were evaluated using functional testing and patient-reported outcomes at baseline, 4 weeks, and 8 weeks.
Findings: In the clinical tests, the Clinical and Combined cohorts showed increased total time for isometric extensor endurance and the Clinical cohort increased total distance traveled in the 6-min walk test at 8 weeks. The Training, Clinical, and Combined groups showed improvements in Patient-reported outcomes after 8 weeks. Most of the significant improvements were only seen at the 8-week evaluation for both the clinical evaluations and Patient-reported outcomes. The Control group did not show significant improvements in any outcome measures.
Interpretation: The present data indicate that core-focused interventions, including artificial-intelligence-guided moderate-resistance exercise, can increase objective functional outcomes and patient satisfaction using Patient-reported outcomes in individuals with lower back pain.
Keywords: Artificial intelligence; Biomechanics; Chiropractic, exercise; Lower back pain; Physical intervention.
Copyright © 2023. Published by Elsevier Ltd.