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Background: Advanced sensor insoles and motion capture technology can significantly enhance the monitoring of patient's rehabilitation progress with distal tibial fractures [1], [2]. This study utilizes the potential of these innovative tools to provide a more comprehensive assessment of a patient's gait and weight-bearing capacity following surgical intervention, offering a possibility for improved patient outcomes.
Methods: A patient who underwent distal medial tibial LCP surgery in August 2023 and a subsequent revision surgery involving the insertion of an intramedullary nail in December 2023 was meticulously monitored over 12 weeks. Initial assessments in November 2023 revealed pain upon full weight-bearing without crutches. Post-revision, precise weekly measurements were taken starting two days after surgery, instilling confidence in the ability to accurately track the patient's progress from initial crutch-assisted walking to full recovery.
Objectives: The study aimed to evaluate the hypothesis that the approximation and formation of a healthy gait curve are decisive for healing. Specifically, it investigated whether cadence, imbalance factors, ground reaction forces, joint angles, and segment acceleration could be significant indicators of the healing status and potential disorders.
Results: The kinetic and kinematic gait parameters significantly correlate with the patient's recovery trajectory. These metrics allow for the early identification of deviations from expected healing patterns and facilitate timely interventions, underscoring the transformative potential of these technologies in patient care.
Conclusion: Integrating sensor insoles and motion capture technology offers a promising approach for monitoring the recovery process in patients with distal tibial fractures. This method provides valuable insights into the patient's healing status, potentially predicting and addressing healing disorders more effectively. Future studies are recommended to validate these findings across a larger cohort and explore the possibility of integrating these technologies into clinical practice.
REFERENCES
[1] Orth, M., et al., Simulation-based prediction of bone healing and treatment recommendations for lower leg fractures: Effects of motion, weight-bearing and fibular mechanics, Front. Bioeng. Biotechol., 11(February), 1–13. (2023)
[2] Warmerdam, E. et al., Gait Analysis to Monitor Fracture Healing of the Lower Leg, Bioeng. (Vol. 10, Issue 2). MDPI. (2023)
