{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,30]],"date-time":"2026-06-30T17:44:56Z","timestamp":1782841496137,"version":"3.54.5"},"reference-count":0,"publisher":"ECMS","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,6,23]]},"abstract":"<jats:p>Low back pain (LBP) is a leading cause of disability worldwide, motivating scalable rehabilitation solutions that support long-term monitoring beyond the clinic. This paper presents the Lithuanian use case of a multimodal telerehabilitation framework integrating video-based movement analysis and electromyography (EMG) for remote exercise assessment. The work reported here constitutes a laboratory-based feasibility study and system prototype. Clinical EMG recordings and controlled video capture were used to validate signal acquisition pipelines and kinematic analysis procedures under supervised conditions prior to real-world telerehabilitation deployment. In the clinic, baseline EMG recordings from lumbar musculature are acquired, while in the intended home-use scenario, exercise execution will be monitored using markerless pose estimation. Pilot EMG analyses were performed using amplitude-based (RMS), coordination-based (Pearson correlation), and divergence-based (NRMSD) descriptors to characterise muscle activation patterns across exercises. Results demonstrate task-dependent differences in activation magnitude and inter-channel behaviour, highlighting variable and often asymmetric recruitment patterns. The proposed processing pipeline establishes a structured foundation for scalable data collection and future development of exercise-quality assessment models within telerehabilitation contexts.<\/jats:p>","DOI":"10.7148\/2026-0426","type":"proceedings-article","created":{"date-parts":[[2026,6,30]],"date-time":"2026-06-30T16:55:14Z","timestamp":1782838514000},"page":"426-432","source":"Crossref","is-referenced-by-count":0,"title":["A multimodal telerehabilitation framework integrating pose estimation and emg for low back pain monitoring"],"prefix":"10.7148","author":[{"given":"Egle","family":"Butkeviciute","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Austeja","family":"Jakimaviciute","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gintaras","family":"Stankevicius","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Liepa","family":"Bikulciene","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"4144","published-online":{"date-parts":[[2026,6,23]]},"event":{"name":"40th ECMS International Conference on Modelling and Simulation"},"container-title":["ECMS 2026 Proceedings edited by Filippo Sanfilippo, Florenc Demrozi, Fabio Sgarbossa, Mohammad Poursina"],"original-title":[],"deposited":{"date-parts":[[2026,6,30]],"date-time":"2026-06-30T16:55:17Z","timestamp":1782838517000},"score":1,"resource":{"primary":{"URL":"http:\/\/www.scs-europe.net\/dlib\/2026\/ecms2026acceptedpapers\/0426_simai_ecms2026_0094.pdf"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,6,23]]},"references-count":0,"URL":"https:\/\/doi.org\/10.7148\/2026-0426","relation":{},"subject":[],"published":{"date-parts":[[2026,6,23]]}}}