特发性脊柱侧凸患者支架治疗监测方案

Bhavani Anantapur Bache, Omar Iftikhar, O. Dehzangi
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引用次数: 3

摘要

脊柱侧凸是一种发生在青少年的医学病症,个体的脊柱发展为弯曲。胸腰骶矫形器(TLSO)是一种用于控制脊柱侧弯的支撑。这是一种非手术治疗,目的是防止特发性脊柱侧凸患者的弯曲进展。为了成功监测支架治疗的依从性,我们设计并开发了一种可穿戴的多模态传感器解决方案,该解决方案嵌入到患者的支架中。定制设计的硬件包括传感器板、力传感器、加速度计和陀螺仪。力传感器收集施加在病人背部的力,而加速度计和陀螺仪产生线索来确定病人的活动和生活方式。在本文中,我们提出了一种新的数据挖掘方法来识别患者的活动,并基于连续力和惯性运动记录的融合来评估支架治疗的有效性。我们的目的是设计一个情境感知远程监测系统,用于无处不在的评估和提高青少年特发性脊柱侧凸患者支架治疗依从性。我们研究了一个实验场景,在这个场景中,患者在佩戴支具的白天进行一系列预先定义的活动,在无处不在的传感器数据记录期间。实验结果表明,我们对半监督活动检测的总体准确率达到100%。在4周的时间内,支架配合的松紧程度逐渐降低了33%。
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Brace Treatment Monitoring Solution for Idiopathic Scoliosis Patients
Scoliosis is a medical condition which occurs in adolescents, where an individual’s spine develops curvature. A Thoracolumbosacral orthosis (TLSO) is a type of brace used to control the lateral curvature of the spine in scoliosis. It is a nonsurgical treatment with the goal of preventing curve progression in patients with idiopathic scoliosis. To successfully monitor compliance with brace treatment, we designed and developed a wearable multi-modal sensor solution is embedded into the patient’s brace. The custom designed hardware consists of a sensor board, a force sensor, an accelerometer and a gyroscope. The force sensor collects the force being exerted on the patient’s back, while the accelerometer and gyroscope generate cues to determine the patient’s activities and lifestyle. In this paper, we propose a novel data-mining method to identify patient activities and evaluate the effectiveness of the brace treatment pervasively based on fusion of continuous force and inertial motion recordings. Our aim is to design a context-aware remote monitoring system for ubiquitous evaluation and enhancement of brace treatment compliance of adolescent idiopathic scoliosis patients. We investigated experimental scenario in which, the patient performs a series of pre-defined activities at home during day long segments of brace wear, during pervasive sensor data recordings. The experimental results demonstrated that we achieved an overall accuracy of a 100% for semi-supervised activity detection. The level of tightness of brace-fit reduced gradually over a period of 4 weeks by 33%.
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