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基于模板互相关的多模态生物信号椅的信号质量指数用于智能医疗保健。

Signal Quality Index Based on Template Cross-Correlation in Multimodal Biosignal Chair for Smart Healthcare.

机构信息

Division of Data Science, The University of Suwon, Wauan-gil 17, Hwaseong-si 18562, Korea.

LG Electronics CTO Division Future Technology Center A.I. Lab., Seoul 06763, Korea.

出版信息

Sensors (Basel). 2021 Nov 14;21(22):7564. doi: 10.3390/s21227564.

DOI:10.3390/s21227564
PMID:34833639
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8624550/
Abstract

We investigated the effects of a quality screening method on unconstrained measured signals, including electrocardiogram (ECG), photoplethysmogram (PPG), and ballistocardiogram (BCG) signals, in our collective chair system for smart healthcare. Such an investigation is necessary because unattached or unbound sensors have weaker connections to body parts than do conventional methods. Using the biosignal chair, the physiological signals collected during sessions included a virtual driving task, a physically powered wheelchair drive, and three types of body motions. The signal quality index was defined by the similarity between the observed signals and noise-free signals from the perspective of the cross-correlations of coefficients with appropriate individual templates. The goal of the index was to qualify signals without a reference signal to assess the practical use of the chair in daily life. As expected, motion artifacts have adverse effects on the stability of physiological signals. However, we were able to observe a supplementary relationship between sensors depending on each movement trait. Except for extreme movements, the signal quality and estimated heart rate (HR) remained within the range of criteria usable for status monitoring. By investigating the signal reliability, we were able to confirm the suitability of using the unconstrained biosignal chair to collect real-life measurements to improve safety and healthcare.

摘要

我们研究了一种质量筛选方法对非约束测量信号的影响,包括心电图(ECG)、光体积描记图(PPG)和心冲击图(BCG)信号,这些信号都是在我们的集体智能医疗椅系统中进行的。这种研究是必要的,因为无附件或未绑定的传感器与身体部位的连接比传统方法更弱。使用生物信号椅,在会话期间收集的生理信号包括虚拟驾驶任务、电动轮椅驱动以及三种类型的身体运动。从系数的互相关与适当的个体模板的相似性的角度来看,信号质量指数是由观察信号与无噪声信号之间的相似性来定义的。该指数的目的是在没有参考信号的情况下对信号进行定性,以评估椅子在日常生活中的实际使用情况。正如预期的那样,运动伪影对生理信号的稳定性有不利影响。然而,我们能够观察到根据每个运动特征传感器之间的补充关系。除了极端运动外,信号质量和估计的心率(HR)仍然在可用于状态监测的标准范围内。通过研究信号可靠性,我们能够确认使用无约束生物信号椅来收集真实生活测量数据以提高安全性和医疗保健的适用性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/52f5/8624550/c9fbe8878d0d/sensors-21-07564-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/52f5/8624550/369c00704a68/sensors-21-07564-g001.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/52f5/8624550/811b48a2668d/sensors-21-07564-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/52f5/8624550/366a429d13dd/sensors-21-07564-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/52f5/8624550/c9fbe8878d0d/sensors-21-07564-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/52f5/8624550/369c00704a68/sensors-21-07564-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/52f5/8624550/4d51a05724fb/sensors-21-07564-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/52f5/8624550/ca7e119512f4/sensors-21-07564-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/52f5/8624550/084b6ccdc1a7/sensors-21-07564-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/52f5/8624550/811b48a2668d/sensors-21-07564-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/52f5/8624550/366a429d13dd/sensors-21-07564-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/52f5/8624550/c9fbe8878d0d/sensors-21-07564-g007.jpg

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