Internet of medical things. Measurement of respiratory dynamics using wearable sensors in post-COVID-19 patients.

Cecilia E García Cena, Luís Silva, Fabian H Diaz Palencia, María Islán Moríñigo, Cristina P Santos, Roque Saltarén Pazmiño, Julian Benito-León, David Gómez-Andrés
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Abstract

Nowadays, the measurement of respiratory dynamics is underrated at clinical setting and in the daily life of a subject and it still represents a challenge from a technical and medical point of view. In this article we propose a concept to measure some of its parameters, such as the respiratory rate (RR), using four inertial sensors. Two different experiments were performed to validate the concept. We analyzed the most suitable placement of each sensor to assess those features and we studied the reliability of the system to measure abnormal parameters of respiration (tachypnea, bradypnea and breath holding). Finally, we measured post-COVID-19 patients, some of them with breath alterations after more than a year of the diagnosis. Experimental results showed that the proposed system could be potentially used to measure the respiratory dynamics at clinical setting. Moreover, while RR can be easily calculated by any sensor, other parameters need to be measured with a sensor in a particular position.

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医疗物联网。使用可穿戴传感器对COVID-19后患者的呼吸动力学进行测量。
如今,呼吸动力学的测量在临床环境和受试者的日常生活中被低估了,从技术和医学角度来看,它仍然是一个挑战。在本文中,我们提出了一个概念,使用四个惯性传感器来测量它的一些参数,如呼吸频率(RR)。进行了两个不同的实验来验证这一概念。我们分析了每个传感器的最合适位置,以评估这些特征,并研究了该系统测量呼吸异常参数(呼吸急促、呼吸缓慢和屏气)的可靠性。最后,我们测量了COVID-19后的患者,其中一些患者在诊断一年多后出现了呼吸改变。实验结果表明,该系统可用于临床环境下的呼吸动力学测量。此外,虽然RR可以通过任何传感器容易地计算,但其他参数需要通过特定位置的传感器来测量。
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