Details

Autor(en) / Beteiligte

• Salleh, Nurul Izah Md
• Diah, Norizan Mat
• Ahmad, Suzana
• Omar, Nasiroh
• Idrus, Zainura
• Nordin, Sharifalillah

Titel

Prediction Exercise on Rehabilitation for Chronic Disease: A Review

Ist Teil von

• 2023 IEEE 8th International Conference on Recent Advances and Innovations in Engineering (ICRAIE), 2023, p.1-6

Ort / Verlag

IEEE

Erscheinungsjahr

2023

Quelle

IEEE Electronic Library (IEL)

Beschreibungen/Notizen

• Rehabilitation is restoring someone's health or normal life from imprisonment, addiction, or illness through training and therapy. A physiotherapist's assistance is critical for monitoring and providing effective training or exercise to optimise physical functionality recovery, such as muscle strength, balance, and mobility, particularly during the first three to four months of critical time. This paper discusses the rehabilitation prediction exercise for chronic disease patients and compares several algorithms commonly applied in the prediction field. Each technique produces a different level of accuracy, and each method is applied to a specific rehabilitation exercise. The data and results of this study were analysed from several research reviews and related existing works. Accuracy level, recovery time, and suitability depend on the specific dataset and area of the disease. According to the findings, most of the studies used machine learning (random forest, neural network, and logistic regression) in their research and development, which could be effectively used as a feature algorithm for prediction in chronic disease rehabilitation.