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Some aspects of this disclosure include systems, methods, and/or computer programs that may be used to filter measurements of affective response collected using sensors that measure physiological signals and/or behavioral cues of users. A bias may be tendency, attitude, and/or inclination, which may influence the affective response a user has to an experience. Some embodiments described herein involve learning a model of biases of the user from measurements of affective response of the user and descriptions of events to which the measurements correspond. The model may be used to filter measurements of the user, which may be provided to other entities, if the model indicates that the measurements are likely to contain a certain level and/or type of bias (e.g., bias to certain factors). Such a filtration process can help make results generated based on the measurements more accurate and also may help protect the privacy of the user.


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Document History
  • Publication: Aug 4, 2016
  • Application: Jan 29, 2016
    DE DE 102016101661 A
  • Priority: Jun 26, 2015
    US US 201562185304 P
  • Priority: Jan 29, 2015
    US US 201562109456 P

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