Tey Chuang-Kit, An Jinyoung, Chung Wan-Young
Department of Electronic Engineering, Pukyong National University, Busan 608-737, Republic of Korea.
Comput Math Methods Med. 2017;2017:5823740. doi: 10.1155/2017/5823740. Epub 2017 May 3.
Chronic obstructive pulmonary disease is a type of lung disease caused by chronically poor airflow that makes breathing difficult. As a chronic illness, it typically worsens over time. Therefore, pulmonary rehabilitation exercises and patient management for extensive periods of time are required. This paper presents a remote rehabilitation system for a multimodal sensors-based application for patients who have chronic breathing difficulties. The process involves the fusion of sensory data-captured motion data by stereo-camera and photoplethysmogram signal by a wearable PPG sensor-that are the input variables of a detection and evaluation framework. In addition, we incorporated a set of rehabilitation exercises specific for pulmonary patients into the system by fusing sensory data. Simultaneously, the system also features medical functions that accommodate the needs of medical professionals and those which ease the use of the application for patients, including exercises for tracking progress, patient performance, exercise assignments, and exercise guidance. Finally, the results indicate the accurate determination of pulmonary exercises from the fusion of sensory data. This remote rehabilitation system provides a comfortable and cost-effective option in the healthcare rehabilitation system.
慢性阻塞性肺疾病是一种由长期气流不畅导致呼吸困难的肺部疾病。作为一种慢性疾病,它通常会随着时间的推移而恶化。因此,需要长期进行肺部康复锻炼和患者管理。本文提出了一种基于多模态传感器的远程康复系统,适用于患有慢性呼吸困难的患者。该过程涉及将立体相机捕获的运动数据和可穿戴式PPG传感器的光电容积脉搏波信号等感官数据进行融合,这些数据是检测和评估框架的输入变量。此外,我们通过融合感官数据,将一套专门针对肺部患者的康复锻炼纳入系统。同时,该系统还具有满足医疗专业人员需求的医疗功能以及方便患者使用应用程序的功能,包括锻炼进度跟踪、患者表现、锻炼任务分配和锻炼指导。最后,结果表明通过感官数据融合能够准确确定肺部锻炼情况。这种远程康复系统在医疗康复系统中提供了一种舒适且经济高效的选择。