Research on Rehabilitation Assessment Methods for Patients After Rotator Cuff Surgery Based on Attitude Sensors and XGBoost Algorithm

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原文链接

NETL

外文摘要：The rotator cuff, as a complex and flexible key part of the human musculoskeletal system, necessitates frequent and precise evaluations during its rehabilitation process after injury. However, traditional evaluation methods heavily rely on doctors' subjective judgments, which not only leads to inconsistent evaluation standards but also increases the number of patient visits to the hospital due to the long evaluation cycles, causing much inconvenience. To address this issue, this paper introduces wearable posture sensor technology. By collecting patients' real-time posture data and combining it with the XGBoost algorithm model, the rehabilitation progress of patients can be objectively and efficiently evaluated. Experimental results have demonstrated that this method performs excellently in assessing the rehabilitation status of patients with rotator cuff injuries, exhibiting good application prospects and practical value.

外文关键词：

Musculoskeletal systemAccuracyQuantum computingSurgeryPatient rehabilitationReal-time systemsClassification algorithmsReliabilityInjuriesStandards

作者：

Kang Xu、Hao Feng、Gang He、Minghui Li

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作者单位：

College of Computer Science and Technology, Southwest University of Science and Technology, Mianyang, China

Southwest University of Science and Technology, Sichuan Electronic and Mechanic Vocational College, Mianyang, China

会议名称：

International Conference on Computing, Communication, Perception and Quantum Technology

会议地点：

Zhuhai(CN)

会议母体文献：

2024 3rd International Conference on Computing, Communication, Perception and Quantum Technology

页码：

312-316

出版时间：

2024

DOI：

10.1109/CCPQT64497.2024.00067