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Estimation of Lumbar Spine Loading of Low Back Pain Participant During Lifting Using an Open Source Musculoskeletal Model.

Preethi ManoharanAdrian PranataKwong Ming TseRifai Chai
Published in: Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference (2024)
Biomechanical modeling of spinal load during lifting in OpenSim has the potential for rehabilitation and clinical assessment. In the literature, several spinal models have been developed and validated with movement data from healthy individuals. Although these models are valid for predicting spinal load in healthy individuals, it is unknown whether these models are applicable for people with chronic low back pain (CLBP). This study aims to compare the application of the lifting full body (LFB) model between a healthy participant and a participant with CLBP. The participants performed the lifting activity, and the motion capture data was used to analyze how an open-source model predicts the loading of the lumbar spine. Peak spinal loading at L5/S1 joint was estimated as 3.9 kN for the healthy participant and 3.1 kN for the CLBP participant. The results suggest that a longer duration of lift and lower lumbar range of motion reduces lumbar spinal loading.
Keyphrases
  • spinal cord
  • systematic review
  • big data
  • spinal cord injury
  • high speed
  • artificial intelligence
  • high resolution
  • clinical evaluation