Toward Measuring Target Perception: First-Order and Second-Order Deep Network Pipeline for Classification of Fixation-Related Potentials

Joint Authors

Zeng, Hong
Shen, Junjie
Zheng, Wenming
Liu, Jia
Song, Aiguo

Source

Journal of Healthcare Engineering

Issue

Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-15, 15 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2020-11-19

Country of Publication

Egypt

No. of Pages

15

Main Topic

Public Health
Medicine

Abstract EN

The topdown determined visual object perception refers to the ability of a person to identify a prespecified visual target.

This paper studies the technical foundation for measuring the target-perceptual ability in a guided visual search task, using the EEG-based brain imaging technique.

Specifically, it focuses on the feature representation learning problem for single-trial classification of fixation-related potentials (FRPs).

The existing methods either capture only first-order statistics while ignoring second-order statistics in data, or directly extract second-order statistics with covariance matrices estimated with raw FRPs that suffer from low signal-to-noise ratio.

In this paper, we propose a new representation learning pipeline involving a low-level convolution subnetwork followed by a high-level Riemannian manifold subnetwork, with a novel midlevel pooling layer bridging them.

In this way, the discriminative power of the first-order features can be increased by the convolution subnetwork, while the second-order information in the convolutional features could further be deeply learned with the subsequent Riemannian subnetwork.

In particular, the temporal ordering of FRPs is well preserved for the components in our pipeline, which is considered to be a valuable source of discriminant information.

The experimental results show that proposed approach leads to improved classification performance and robustness to lack of data over the state-of-the-art ones, thus making it appealing for practical applications in measuring the target-perceptual ability of cognitively impaired patients with the FRP technique.

American Psychological Association (APA)

Zeng, Hong& Shen, Junjie& Zheng, Wenming& Song, Aiguo& Liu, Jia. 2020. Toward Measuring Target Perception: First-Order and Second-Order Deep Network Pipeline for Classification of Fixation-Related Potentials. Journal of Healthcare Engineering،Vol. 2020, no. 2020, pp.1-15.
https://search.emarefa.net/detail/BIM-1186487

Modern Language Association (MLA)

Zeng, Hong…[et al.]. Toward Measuring Target Perception: First-Order and Second-Order Deep Network Pipeline for Classification of Fixation-Related Potentials. Journal of Healthcare Engineering No. 2020 (2020), pp.1-15.
https://search.emarefa.net/detail/BIM-1186487

American Medical Association (AMA)

Zeng, Hong& Shen, Junjie& Zheng, Wenming& Song, Aiguo& Liu, Jia. Toward Measuring Target Perception: First-Order and Second-Order Deep Network Pipeline for Classification of Fixation-Related Potentials. Journal of Healthcare Engineering. 2020. Vol. 2020, no. 2020, pp.1-15.
https://search.emarefa.net/detail/BIM-1186487

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1186487