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Non-contact real-time estimation of intrapulmonary pressure and tidal volume for chronic heart failure patients

机译:对慢性心力衰竭患者的肺肺压力和潮气量的非接触式实时估计

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Long-term continuous patient monitoring is required in many health systems for monitoring and analytical diagnosing purposes. It has been recognized that these types of monitoring systems have shortcomings related to patient comfort and/or functionality. Non-contact monitoring systems have been developed to address some of these shortcomings. One of such systems is non-contact physiological vital signs assessments for Chronic Heart Failure (CHF) patients. This paper presents a novel pulmonary ventilation model that defines the relationship between the intrapulmonary pressure and the chest displacement. A novel intrapulmonary pressure and tidal volume estimation algorithm is also proposed. A database consisting of twenty CHF patients with New York Heart Association (NYHA) Heart Failure Classification Class II & III; whose underwent full Polysomnography (PSG) analysis for diagnosis of sleep apnea, disordered sleep, or both, was selected for the verification of the proposed model and algorithm. The proposed algorithm analyzes the non-contact sensor data and estimate the patient's intrapulmonary pressure and tidal volume. The output of the algorithm is compared with the gold-standard PSG recordings. Across all twenty CHF patients' recordings with mean recorded sleep duration of 7.76 hours, the tidal volume estimation median accuracy achieved 83.13% with a median error of 57.32 milliliters. A potential application would be non-contact continuous monitoring of intrapulmonary pressure and tidal volume during sleep in the home.
机译:许多卫生系统需要长期连续患者监测,用于监测和分析诊断目的。已经认识到,这些类型的监测系统具有与患者舒适和/或功能相关的缺点。已经开发出非联系监控系统来解决这些缺点中的一些。这种系统之一是对慢性心力衰竭(CHF)患者进行的非接触生理生命体征评估。本文介绍了一种新颖的肺气通风模型,其定义了片内压力和胸部位移之间的关系。还提出了一种新型的肺内压力和潮气体积估计算法。由纽约心脏协会(NYHA)心力衰竭分类级II&III组成的数据库组成的数据库;选择既往诊断睡眠呼吸暂停,无序睡眠或两者的诊断,验证所提出的模型和算法的诊断。该算法分析了非接触式传感器数据并估计患者的肺部压力和潮气量。将算法的输出与金标准PSG录制进行比较。遍布所有二十次CHF患者的录音,患睡眠持续时间为7.76小时,潮气量估计中值准确度83.13%,中位数误差为57.32毫升。潜在的应用将在家庭睡眠期间对血管压力和潮气的不接触连续监测。

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