{"title":"MultiMind: Multi-Brain Signal Fusion to Exceed the Power of a Single Brain","authors":"A. Stoica","doi":"10.1109/EST.2012.47","DOIUrl":null,"url":null,"abstract":"We propose a Multi-Brain (multi bio-signal) Fusion (MBF) technology, which consists in the aggregation and analysis of brain and other biometric signals collected from a number of individuals. Often performed in the context of some common stimulus, MBF aims to facilitate rapid/enhanced collective analysis and decision making, or to assess aggregate characteristics, such as a group emotional index (GEI). The wide range of potential applications may justify an ongoing, distributed program of research into the biometric correlates of conscious and unconscious human cognitive functions (practical intelligence). An example is MBF-enabled joint analysis, which would combine cues from several intelligence analysts who are examining the same visual scene in order to rapidly highlight important features that might not be salient to any individual analyst, and which might be difficult to elicit from the group by conventional means. An experiment in presented in which a GEI is obtained by aggregating the information from two people wearing EMOTIV Epoc™ 'neuroheadsets', which collect electroencephalogram (EEG) / electromyogram (EMG) signals from 14 sensors on the scalp. As subjects watch a sequence of slides with emotion-triggering content, their decoded emotions are fused to provide a group emotional response, a collective assessment of the presented information. MBF has the potential to surpass single-brain limitations by accessing and integrating more information than can be usefully shared within even small human groups by means of speech, prosody, facial expression and other nonverbal means One may speculate that the automated aggregation of signals from multiple human brains may open a path to super-human intelligence.","PeriodicalId":314247,"journal":{"name":"2012 Third International Conference on Emerging Security Technologies","volume":"3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"16","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 Third International Conference on Emerging Security Technologies","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EST.2012.47","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 16
Abstract
We propose a Multi-Brain (multi bio-signal) Fusion (MBF) technology, which consists in the aggregation and analysis of brain and other biometric signals collected from a number of individuals. Often performed in the context of some common stimulus, MBF aims to facilitate rapid/enhanced collective analysis and decision making, or to assess aggregate characteristics, such as a group emotional index (GEI). The wide range of potential applications may justify an ongoing, distributed program of research into the biometric correlates of conscious and unconscious human cognitive functions (practical intelligence). An example is MBF-enabled joint analysis, which would combine cues from several intelligence analysts who are examining the same visual scene in order to rapidly highlight important features that might not be salient to any individual analyst, and which might be difficult to elicit from the group by conventional means. An experiment in presented in which a GEI is obtained by aggregating the information from two people wearing EMOTIV Epoc™ 'neuroheadsets', which collect electroencephalogram (EEG) / electromyogram (EMG) signals from 14 sensors on the scalp. As subjects watch a sequence of slides with emotion-triggering content, their decoded emotions are fused to provide a group emotional response, a collective assessment of the presented information. MBF has the potential to surpass single-brain limitations by accessing and integrating more information than can be usefully shared within even small human groups by means of speech, prosody, facial expression and other nonverbal means One may speculate that the automated aggregation of signals from multiple human brains may open a path to super-human intelligence.