# Evaluation of the Efficacy of an Artificial Intelligence-Based Assessment and Correction System in the Rehabilitation of Patients Following Anterior Cruciate Ligament Reconstruction Surgery

**Authors:** Tingting Zhu, Ying Huang, Jingjing Pu, Chaolong Wang, Min Ruan, Ping Lu, Xiaojiang Yang, Nirong Bao, Yueying Chen, Aiqin Zhang

PMC · DOI: 10.3390/jcm15020575 · Journal of Clinical Medicine · 2026-01-10

## TL;DR

An AI-based rehabilitation system improves recovery and exercise adherence after ACL surgery compared to traditional methods.

## Contribution

This study demonstrates the efficacy of an AI-based rehabilitation system in enhancing postoperative recovery and adherence in ACL reconstruction patients.

## Key findings

- The trial group showed significantly better knee function scores and balance compared to the control group.
- AI-guided rehabilitation resulted in greater joint range of motion and higher exercise adherence.
- Digital rehabilitation models outperformed conventional methods in postoperative ACL recovery.

## Abstract

Background: Arthroscopic anterior cruciate ligament (ACL) reconstruction is widely recognised as the primary treatment for ACL injuries. However, with the increasing incidence of sports-related injuries and growing demand for rehabilitation services, conventional rehabilitation models—largely reliant on therapists’ experience and subjective assessment—are increasingly insufficient to meet the clinical need for precise and individualised rehabilitation programmes. This study aimed to evaluate the effectiveness of a rehabilitation protocol incorporating an artificial intelligence (AI)-based assessment and correction system on functional recovery following ACL reconstruction. Methods: Using convenience sampling, 80 patients undergoing ACL reconstruction between June to December 2024 were recruited for this randomised controlled trial. Participants were randomly assigned to either a control group (n = 40), which received conventional functional exercise training, or a trial group (n = 40), which received rehabilitation intervention guided by an AI-based assessment and correction system. Knee function scores (Lysholm score, IKDC score), Berg Balance Scale (BBS) scores, joint range of motion (ROM), and rehabilitation exercise compliance scores were collected and analysed 1, 2, 3, and 4 months postoperatively. Results: Compared with the control group, the trial group demonstrated significantly greater improvements in Lysholm score, IKDC score, BBS score, and active knee joint ROM (p < 0.05) at postoperative assessment points. Additionally, rehabilitation exercise adherence was significantly higher in the trial group compared to the control group (p < 0.05). Conclusions: Rehabilitation protocols integrating AI-based assessment and correction systems effectively enhance knee function recovery, joint mobility and balance ability following ACL reconstruction. Moreover, these protocols significantly improve rehabilitation exercise adherence, demonstrating superior efficacy compared to conventional rehabilitation approaches. This digital rehabilitation model represents an efficient and promising intervention for postoperative ACL rehabilitation.

## Full-text entities

- **Diseases:** injuries (MESH:D014947), ACL (MESH:D000070598)
- **Species:** Homo sapiens (human, species) [taxon 9606]

## Full text

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## Figures

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## References

23 references — full list in the complete paper: https://tomesphere.com/paper/PMC12842572/full.md

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Source: https://tomesphere.com/paper/PMC12842572