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Technology-Based Education and Training System for Nursing Professionals

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Biomedical Engineering Systems and Technologies (BIOSTEC 2021)

Abstract

Musculoskeletal Disorders (MSD) are one of the most significant health hazards for nurses causing a high rate of sick leave and exit the profession before the retirement age. In this context, physically heavy tasks like lifting patients frequently in awkward stooped or forced postures lead to constant high physical stresses and thus to MSD and physical deterioration. Therefore, in order to reduce physical load, a focus must be placed on the education and training of nurses on ergonomically correct working techniques. At present, technical assistance for the analysis of ergonomic working methods is rarely used in nursing training. In this work, we present a novel sensor system to improve the educational processes in the healthcare profession. The system includes three-dimensional optical sensors, a wearable sensor suit, a ground reaction force plate and surface electromyography to record and analyze nursing tasks. The system is tested and evaluated in a case study with nursing students (n \(=\) 13) during a simulated transfer task. The system provided in-depth evaluation of the conducted transfer and increased the feedback quality of an instructor compared to conventional training methods.

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Acknowledgements

The study work was carried out at the Evangelische Altenpflegeschule e.V. Oldenburg (Evangelical Nursing School) and was funded by the German Federal Ministry of Education and Research (Project No. 02L14A240). The development of the posture analyses system was funded by the Lower Saxony Ministry of Science and Culture under grant number 11-76251-12-10/19 ZN3491 within the Lower Saxony “Vorab” of the Volkswagen Foundation and supported by the Center for Digital Innovations (ZDIN).

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Correspondence to Conrad Fifelski-von Böhlen .

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Böhlen, C.Fv., Brinkmann, A., Fudickar, S., Hellmers, S., Hein, A. (2022). Technology-Based Education and Training System for Nursing Professionals. In: Gehin, C., et al. Biomedical Engineering Systems and Technologies. BIOSTEC 2021. Communications in Computer and Information Science, vol 1710. Springer, Cham. https://doi.org/10.1007/978-3-031-20664-1_7

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  • DOI: https://doi.org/10.1007/978-3-031-20664-1_7

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