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Musculoskeletal care · 2025

Remote Sensor-Based Monitoring in Low Back Pain Management: A Review of Outcomes Related to Quality of Life and Rehabilitation Care.

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Gakhar Himanshu, Bhati Sarika, Pawaria Sonia

Аннотация

BACKGROUND: Low back pain (LBP) is one of the most prevalent musculoskeletal conditions globally, often leading to diminished quality of life, reduced physical function, and increased healthcare utilization. Recent advancements in remote sensor-based technologies have introduced innovative methods for continuous monitoring and personalised rehabilitation of individuals with LBP.

OBJECTIVE: This Narrative review aims to explore and synthesize current evidence on the use of remote sensor-based monitoring in the management of low back pain, with a focus on outcomes related to quality of life, functional recovery, and patient-centred care.

METHODS: A systematic search was performed across four major databases-PubMed, Scopus, Web of Science, and Google Scholar-for studies published between 2010 and 2025. Search terms included low back pain, remote monitoring, wearable sensors, digital health, and rehabilitation outcomes. Inclusion criteria comprised randomized controlled trials, cohort studies, systematic reviews, scoping and literature reviews that examined sensor-driven interventions in outpatient or home-based LBP rehabilitation settings.

RESULTS: The review identified evidence supporting the use of wearable sensors in enhancing patient engagement, tracking physical activity, and enabling real-time feedback during exercises. Improvements were noted in pain management, functional mobility, and patient-reported quality of life. Moreover, remote monitoring promoted adherence and early detection of relapses. Nonetheless, heterogeneity in sensor types, data interpretation, and outcome reporting was observed across studies.

CONCLUSION: Remote sensor-based monitoring holds significant potential to complement conventional rehabilitation strategies for low back pain. Future research should prioritise standardized frameworks, integration into clinical pathways, and evaluation of long-term cost-effectiveness and patient acceptability.

Предметные рубрики MeSH

ИП Урсолов Владлен Сергеевич

ИНН 500118482352 · ОГРНИП 314500117700049

Реквизиты и контакты