Predictive COPD Monitoring Device (PCMD)

초록

Using an automated system to manage chronic illnesses such as obstructive pulmonary disease can provide prompt assistance to help the patient reduce outlays for medical care and prevent premature death. The proposed method predicts and possible detections of exacerbations so individuals may self-manage their condition and avoid going to the hospital. The system comprises sensor nodes combined into a single unit that can gather precise, objective physiological data, such as breathing patterns (respiratory rate or R.R.), SpO2 level, and distance traveled by the patient. Such a system can help to alert the patient about an unrecognized health condition that he may have while providing the health monitoring team to interpret the data using probabilistic reasoning. Also, the obtained data are kept and sent to an S.D. card and cloud for the future needs of healthcare professionals. This study evaluates the probabilistic model using an independent dataset by performing a cross-validation analysis. Moreover, several volunteers, most of whom were smokers, participated in using assessing the device's technical feasibility, and feedback was obtained for further configuration of the device. Exacerbations might be accurately detected by the outcome of the model's evaluation. © 2022 IEEE.

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