| Autor: |
Luis Perotti, Oskar Stamm, Lisa Mesletzky, Susan Vorwerg, Marc Fournelle, Ursula Müller-Werdan |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| Předmět: |
|
| Zdroj: |
International Journal of Environmental Research and Public Health; Volume 20; Issue 6; Pages: 4927 |
| ISSN: |
1660-4601 |
| DOI: |
10.3390/ijerph20064927 |
| Popis: |
Chronic back pain has a high prevalence, especially in older adults, and seriously affects sufferers’ quality of life. Segmental stabilization exercise (SSE) is often used during physiotherapy to enhance core stability. The execution of SSE requires the selective contraction of deep abdominal and back muscles. Motor learning can be supported using ultrasound imaging as visual biofeedback. ULTRAWEAR is a mobile ultrasound system that provides deep learning-based biofeedback on SSE execution, which is currently under development. We interviewed 15 older chronic back pain patients (CBPPs) to investigate their pain management behavior, experience with SSE, as well as their needs and requirements for ULTRAWEAR. We also gathered information about future-usage scenarios. CBPPs reported a high willingness to use the system as a feedback tool both in physiotherapeutic practices and at home. The automated detection and evaluation of muscle contraction states was highlighted as a major benefit of the system compared to the more subjective feedback provided by traditional methods such as palpation. The system to be developed was perceived as a helpful solution to support learning about SSE. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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