Musculoskeletal simulation for patient transfer using hand load measurement device

Ryo Uchimura; Ryohei Fushitani; Kodai Kitagawa; Chikamune Wada

doi:10.18203/issn.2455-4510.IntJResOrthop20243773

Authors

Ryo Uchimura Graduate School of Life Science and Systems Engineering, Kyushu Institute of Technology, Kitakyushu, Japan
Ryohei Fushitani Graduate School of Life Science and Systems Engineering, Kyushu Institute of Technology, Kitakyushu, Japan
Kodai Kitagawa Mechanical and Medical Engineering Course, National Institute of Technology, Hachinohe College, Hachinohe, Japan
Chikamune Wada Graduate School of Life Science and Systems Engineering, Kyushu Institute of Technology, Kitakyushu, Japan

DOI:

https://doi.org/10.18203/issn.2455-4510.IntJResOrthop20243773

Keywords:

Caregiver, Patient transfer, Muscle activity, Spinal load, Musculoskeletal simulation, Hand load

Abstract

Background: Unsuitable posture in patient transfer motion causes lower back pain (LBP) among caregivers. The suitable postures to reducing lumbar loads during patient transfer are investigated by musculoskeletal simulation. However, existing musculoskeletal simulation cannot accurately predict lumbar loads because the existing musculoskeletal models are generated by only motion data. Thus, this study aimed to propose and evaluate an accurate musculoskeletal model using hand load data obtained from a hand load measurement device.

Methods: Motion and hand load data for the musculoskeletal model were measured during patient transfer by an inertial measurement unit (IMU)-based motion capture system and hand load measurement device. The existing model without using hand load data and the proposed model using hand load data predicted the activity of the erector spinae muscles and the compressive force of L4-L5. The correlation of erector spinae muscle activity was compared between the predicted and ground truth (surface electromyography) values. Furthermore, predicted compressive forces of L4-L5 were compared with reference value reported by previous study related to in vivo intradiscal pressures measurement.

Results: The proposed model could predict erector spinae muscle activity with a correlation that was significantly greater than that of the existing model (p<0.05). Furthermore, the proposed model could predict compressive forces of L4-L5 with approximate values close to in vivo intradiscal pressures measurement.

Conclusions: Proposed musculoskeletal model may more accurately predict lumbar loads during patient transfer than the existing model. Proposed musculoskeletal model will be applied to explore suitable postures for preventing LBP.

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