一种自主声学项圈,通过分析声音和呼吸系统的振动成分来量化covid-19影响的严重程度

V. Elias, A. Rabih, S. Bin, H. Aziz, G. Nassar
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引用次数: 0

摘要

在这项工作中,设计了一种基于纳米线机电传感器的声学宽带装置,用于评估Covid-19影响导致的病理生理状态严重程度。该系统由一个柔性项圈组成,生物相容的声学和热电传感器与人工智能算法相关联,以提供有关感染疾病影响的客观分析。该设计能够提供多维信息和决策支持工具,以确定表征所探索症状的病理生理状态。在对30名受试者进行测试后,该设备能够区分症状轻微的患者和出现急性呼吸衰竭症状的患者。凭借这一潜力,它有助于对病变进行非侵入性评估和动态观察,从而为医疗操作员提供支持,以改善危机时期的最佳临床管理。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An autonomous acoustic collar to quantify the severity of covid-19 effects by analyzing the vibratory components of vocal and respiratory systems
In this work, an acoustic wide band devise based on a nano-wire electromechanical sensor has been designed to assess the pathophysiology state severity resulting from the effect of Covid-19 affectation. The system consists of a flexible collar to which biocompatible acoustic and thermoelectric sensors associated at an Artificial Intelligence algorithm to provide an objective analysis regarding the effects of the infection disease. This devise able to offers multidimensional information and a decision support tool for determining a pathophysiological state representative of the symptoms explored. Having tested the device on 30 subjects, it was able to differentiate patients with mild symptoms from those who have developed acute signs of respiratory failure. With this potential, it contributes to the non-invasive assessment and dynamic observation of lesions in order to provide support for medical operators to improve an optimal clinical management in times of crisis.
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