Role of Internet of Things (IoT), Artificial Intelligence and Machine Learning in Musculoskeletal Pain: A Scoping Review

被引:4
|
作者
Hasan, Fatima [1 ]
Mudey, Abhay [1 ]
Joshi, Abhishek [1 ]
机构
[1] Datta Meghe Inst Med Sci, Jawaharlal Nehru Med Coll, Community Med, Wardha, India
关键词
exercise adherence; machine learning; internet of things (iot); artificial intelligence; musculoskeletal pain; WEB-BASED INTERVENTION; LOW-BACK-PAIN; KNEE OSTEOARTHRITIS; EFFICACY; RECOMMENDATIONS; MANAGEMENT; HIP;
D O I
10.7759/cureus.37352
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Artificial intelligence (AI), Internet of Things (IoT), and machine learning (ML) have considerably increased in numerous critical medical sectors and significantly impacted our daily lives. Digital health interventions support cost-effective, accessible, and preferred interventions that meet time and resource constraints for large patient populations. Musculoskeletal conditions significantly impact society, the economy, and people's life. Adults with chronic neck and back pain are frequently the victims, rendering them physically unable to move. They often experience discomfort, necessitating them to take over-the-counter medications or painkilling gels. Technologies driven by AI have been suggested as an alternative approach to improve adherence to exercise therapy, which in turn helps patients undertake exercises every day to relieve pain associated with the musculoskeletal system. Even though there are many computer-aided evaluations available for physiotherapy rehabilitation, current approaches to computer-aided performance and monitoring lack flexibility and robustness. A thorough literature search was conducted using key databases like PubMed and Google Scholar, as well as Medical Subject Headings (MeSH) terms and related keywords. This research aimed to determine if AI-operated digital health therapies that use cutting-edge IoT, brain imaging, and ML technologies are beneficial in lowering pain and enhancing functional impairment in patients with musculoskeletal diseases. The secondary goal was to ascertain whether solutions driven by machine learning or artificial intelligence can improve exercise compliance and be viewed as a lifestyle choice.
引用
收藏
页数:8
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