Brainsourcing: Crowdsourcing Recognition Tasks via Collaborative Brain-Computer Interfacing

被引：14
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
收藏
页数：14
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