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经济实惠、便于携带且可自主操作的电阻抗断层成像技术可实现全球和区域性肺功能评估。

Affordable, portable and self-administrable electrical impedance tomography enables global and regional lung function assessment.

机构信息

Gense Technologies Ltd., Hong Kong, China.

Department of Electrical and Electronic Engineering, Faculty of Engineering, The University of Hong Kong, Hong Kong, China.

出版信息

Sci Rep. 2022 Nov 30;12(1):20613. doi: 10.1038/s41598-022-24330-2.

Abstract

Accessibility of diagnostic screening and treatment monitoring devices for respiratory diseases is critical in promoting healthcare and reducing sudden complications and mortality. Spirometry is the standard for diagnosing and monitoring several lung diseases. However, it lacks regional assessment capabilities necessary for detecting subtle regional changes in certain diseases. It also requires challenging breathing maneuvers difficult for elderlies, children, and diseased patients. Here, we actualized an affordable, portable, and self-administrable electrical impedance tomography (EIT) system for home-based lung function assessment and telemedicine. Through simultaneous EIT-spirometry trials on healthy subjects, we demonstrated that our device can predict spirometry indicators over a wide range and can provide regional mapping of these indicators. We further developed a close-to-effortless breathing paradigm and tested it by longitudinally monitoring a COVID-19 discharged subject and two healthy controls with results suggesting the paradigm can detect initial deterioration followed by recovery. Overall, the EIT system can be widely applicable for lung function screening and monitoring both at homes and clinics.

摘要

诊断性筛查和治疗监测设备的可及性对于促进医疗保健、减少突发并发症和死亡率至关重要。肺量计是诊断和监测多种肺部疾病的标准设备。然而,它缺乏检测某些疾病中细微区域性变化所需的区域性评估能力。它还需要进行具有挑战性的呼吸动作,这对于老年人、儿童和患病患者来说是困难的。在这里,我们实现了一种经济实惠、便携式且可自行管理的电阻抗断层成像(EIT)系统,用于家庭肺功能评估和远程医疗。通过对健康受试者进行同时的 EIT-肺量计试验,我们证明了我们的设备可以在广泛的范围内预测肺量计指标,并提供这些指标的区域映射。我们进一步开发了一种接近无需努力的呼吸范式,并通过对一名 COVID-19 出院患者和两名健康对照者进行纵向监测来测试它,结果表明该范式可以检测到最初的恶化,然后再恢复。总的来说,EIT 系统可以广泛应用于家庭和诊所的肺功能筛查和监测。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4e83/9712422/10ccb7c40197/41598_2022_24330_Fig1_HTML.jpg

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