Brainsourcing: Crowdsourcing Recognition Tasks via Collaborative Brain-Computer Interfacing

被引：13

作者：

Davis, Keith M., III ^{[1
]}

Kangassalo, Lauri ^{[1
]}

Spape, Michiel ^{[2
]}

Ruotsalo, Tuukka ^{[1
]}

机构：

[1] Univ Helsinki, Dept Comp Sci, Helsinki, Finland

[2] Univ Helsinki, Dept Psychol & Logoped, Helsinki, Finland

来源：

PROCEEDINGS OF THE 2020 CHI CONFERENCE ON HUMAN FACTORS IN COMPUTING SYSTEMS (CHI'20) | 2020年

基金：

芬兰科学院;

关键词：

Crowdsourcing; Brainsourcing; Brain-computer interfaces; P300; EEG; CLASSIFICATION; DIAGNOSIS; FEEDBACK; SYSTEMS; ISSUES; SKULL;

D O I：

10.1145/3313831.3376288

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper introduces brainsourcing: utilizing brain responses of a group of human contributors each performing a recognition task to determine classes of stimuli. We investigate to what extent it is possible to infer reliable class labels using data collected utilizing electroencephalography (EEG) from participants given a set of common stimuli. An experiment (N=30) measuring EEG responses to visual features of faces (gender, hair color, age, smile) revealed an improved F1 score of 0.94 for a crowd of twelve participants compared to an F1 score of 0.67 derived from individual participants and a random chance of 0.50. Our results demonstrate the methodological and pragmatic feasibility of brainsourcing in labeling tasks and opens avenues for more general applications using brain-computer interfacing in a crowdsourced setting.

引用

页数：14

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