Wearable-based Pain Assessment in Patients with Adhesive Capsulitis Using Machine Learning

Chih Hsing Chen, Kai Chun Liu, Ting Yang Lu, Chih Ya Chang, Chia Tai Chan, Yu Tsao

研究成果: Conference contribution同行評審

摘要

Reliable shoulder function and pain assessment tools are critical for managing patients with adhesive capsulitis (AC). Particularly, objective pain assessment plays an important role, which could support just-in-time treatment or intervention, monitor short-term and temporal dynamic within-person changes, and provide real-time feedback. Currently, pain assessment for AC still relies on a self-report approach that often suffers issues in substantial recall biases, social desirability, and measurement error. To augment typical self-report for clinical decision-making and treatment in AC, the present pilot study proposed a novel pain assessment tool using wearable inertial measurement units (IMUs) and machine learning (ML) approaches. Twenty-three patients with AC performed 5 shoulder tasks and reported pain scores based on the shoulder pain and disability index. Two wearable IMUs were placed on the wrist and arm to collect upper limb movement signals while performing shoulder tasks. We analyzed correlations between pain scores and IMU feature categories (e.g., smoothness, power, and speed). The results revealed that smoothness-related features exhibited higher Spearman correlations with patient-reported pain scores than power and speed features. Meanwhile, we built pain prediction models with the extracted IMU features and different ML approaches. The ML-based pain prediction model using Gaussian process regression showed strong and significant Spearman correlations (0.795, p < 0.01), with a mean absolute error of 5.680 and root mean square error of 6.663.

原文English
主出版物標題11th International IEEE/EMBS Conference on Neural Engineering, NER 2023 - Proceedings
發行者IEEE Computer Society
ISBN(電子)9781665462921
DOIs
出版狀態Published - 2023
事件11th International IEEE/EMBS Conference on Neural Engineering, NER 2023 - Baltimore, United States
持續時間: 25 4月 202327 4月 2023

出版系列

名字International IEEE/EMBS Conference on Neural Engineering, NER
2023-April
ISSN(列印)1948-3546
ISSN(電子)1948-3554

Conference

Conference11th International IEEE/EMBS Conference on Neural Engineering, NER 2023
國家/地區United States
城市Baltimore
期間25/04/2327/04/23

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