Literature DB >> 30872232

Age-Related Changes in Vibro-Tactile EEG Response and Its Implications in BCI Applications: A Comparison Between Older and Younger Populations.

Mei Lin Chen, Dannie Fu, Jennifer Boger, Ning Jiang.   

Abstract

The rapid increase in the number of older adults around the world is accelerating research in applications to support age-related conditions, such as brain-computer interface (BCI) applications for post-stroke neurorehabilitation. The signal processing algorithms for electroencephalogram (EEG) and other physiological signals that are currently used in BCI have been developed on data from much younger populations. It is unclear how age-related changes may affect the EEG signal and therefore the use of BCI by older adults. This research investigated the EEG response to vibro-tactile stimulation from 11 younger (21.7±2.76 years old) and 11 older (72.0±8.07 years old) subjects. The results showed that: 1) the spatial patterns of cortical activation in older subjects were significantly different from those of younger subjects, with markedly reduced lateralization; 2) there is a general power reduction of the EEG measured from older subjects. The average left vs. right BCI performance accuracy of older subjects was 66.4±5.70%, 15.9% lower than that of the younger subjects (82.3±12.4%) and statistically significantly different (t(10)= -3.57, p= 0.005). Future research should further investigate age-differences that may exist in electrophysiology and take these into consideration when developing applications that target the older population.

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Year:  2019        PMID: 30872232     DOI: 10.1109/TNSRE.2019.2890968

Source DB:  PubMed          Journal:  IEEE Trans Neural Syst Rehabil Eng        ISSN: 1534-4320            Impact factor:   3.802


  6 in total

1.  eldBETA: A Large Eldercare-oriented Benchmark Database of SSVEP-BCI for the Aging Population.

Authors:  Bingchuan Liu; Yijun Wang; Xiaorong Gao; Xiaogang Chen
Journal:  Sci Data       Date:  2022-05-31       Impact factor: 8.501

2.  EEG-based vibrotactile evoked brain-computer interfaces system: A systematic review.

Authors:  Xiuyu Huang; Shuang Liang; Zengguang Li; Cynthia Yuen Yi Lai; Kup-Sze Choi
Journal:  PLoS One       Date:  2022-06-03       Impact factor: 3.752

3.  Analysis of the Relationship Between Motor Imagery and Age-Related Fatigue for CNN Classification of the EEG Data.

Authors:  Xiangyun Li; Peng Chen; Xi Yu; Ning Jiang
Journal:  Front Aging Neurosci       Date:  2022-07-14       Impact factor: 5.702

4.  Age-related differences in the transient and steady state responses to different visual stimuli.

Authors:  Xin Zhang; Yi Jiang; Wensheng Hou; Ning Jiang
Journal:  Front Aging Neurosci       Date:  2022-09-08       Impact factor: 5.702

5.  Trajectories of brain entropy across lifetime estimated by resting state functional magnetic resonance imaging.

Authors:  Yan Niu; Jie Sun; Bin Wang; Yanli Yang; Xin Wen; Jie Xiang
Journal:  Hum Brain Mapp       Date:  2022-05-26       Impact factor: 5.399

6.  Analysis of Prognostic Risk Factors Determining Poor Functional Recovery After Comprehensive Rehabilitation Including Motor-Imagery Brain-Computer Interface Training in Stroke Patients: A Prospective Study.

Authors:  Qiong Wu; Yunxiang Ge; Di Ma; Xue Pang; Yingyu Cao; Xiaofei Zhang; Yu Pan; Tong Zhang; Weibei Dou
Journal:  Front Neurol       Date:  2021-06-10       Impact factor: 4.003

  6 in total

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