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用于用户状态评估的脑电和非脑电活动的相关性和相似性。

Correlation and Similarity between Cerebral and Non-Cerebral Electrical Activity for User's States Assessment.

机构信息

Department of Molecular Medicine, Sapienza University of Rome, Piazzale Aldo Moro, 5, 00185 Rome, Italy.

BrainSigns srl, via Sesto Celere, 00152 Rome, Italy.

出版信息

Sensors (Basel). 2019 Feb 9;19(3):704. doi: 10.3390/s19030704.

Abstract

Human tissues own conductive properties, and the electrical activity produced by human organs can propagate throughout the body due to neuro transmitters and electrolytes. Therefore, it might be reasonable to hypothesize correlations and similarities between electrical activities among different parts of the body. Since no works have been found in this direction, the proposed study aimed at overcoming this lack of evidence and seeking analogies between the brain activity and the electrical activity of non-cerebral locations, such as the neck and wrists, to determine if i) cerebral parameters can be estimated from non-cerebral sites, and if ii) non-cerebral sensors can replace cerebral sensors for the evaluation of the users under specific experimental conditions, such as eyes open or closed. In fact, the use of cerebral sensors requires high-qualified personnel, and reliable recording systems, which are still expensive. Therefore, the possibility to use cheaper and easy-to-use equipment to estimate cerebral parameters will allow making some brain-based applications less invasive and expensive, and easier to employ. The results demonstrated the occurrence of significant correlations and analogies between cerebral and non-cerebral electrical activity. Furthermore, the same discrimination and classification accuracy were found in using the cerebral or non-cerebral sites for the user's status assessment.

摘要

人体组织具有导电性,由于神经递质和电解质的存在,人体器官产生的电活动可以在全身传播。因此,假设身体不同部位之间的电活动存在相关性和相似性是合理的。由于在这方面没有发现相关研究,因此本研究旨在克服这一证据不足的问题,并寻求大脑活动与非脑部位置(如颈部和手腕)的电活动之间的相似性,以确定:i)是否可以从非脑部部位估计大脑参数;以及 ii)非脑部传感器是否可以在特定实验条件下(如睁眼或闭眼)代替脑部传感器来评估用户。实际上,脑部传感器的使用需要高素质的人员和可靠的记录系统,而这些仍然很昂贵。因此,使用更便宜、更易于使用的设备来估计大脑参数的可能性将使一些基于大脑的应用程序变得不那么侵入性和昂贵,并且更容易使用。研究结果表明,大脑和非大脑电活动之间存在显著的相关性和相似性。此外,在使用大脑或非大脑部位评估用户状态时,发现了相同的区分和分类准确性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e064/6387465/c74cb18e58ed/sensors-19-00704-g001.jpg

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