Abstract: Wearable devices for taking symmetric thermal measurements. One device includes first and second thermal cameras physically coupled to a frame worn on a user's head. The first thermal camera takes thermal measurements of a first region of interest that covers at least a portion of the right side of the user's forehead. The second thermal camera takes thermal measurements of a second ROI that covers at least a portion of the left side of the user's forehead. Wherein the first and second thermal cameras are not in physical contact with their corresponding ROIs, and as a result of being coupled to the frame, the thermal cameras remain pointed at their corresponding ROIs when the user's head makes angular movements.

Abstract: Wearable devices for taking symmetric thermal measurements. One device includes first and second thermal cameras physically coupled to a frame worn on a user's head. The first thermal camera takes thermal measurements of a first region of interest that covers at least a portion of the right side of the user's forehead. The second thermal camera takes thermal measurements of a second ROI that covers at least a portion of the left side of the user's forehead. Wherein the first and second thermal cameras are not in physical contact with their corresponding ROIs, and as a result of being coupled to the frame, the thermal cameras remain pointed at their corresponding ROIs when the user's head makes angular movements.

Abstract: A user may be exposed to multiple token instances representing stimuli that may influence the affective state of the user. Described herein are embodiments of systems, method, and computer programs for estimating affective response to a token instance of interest, selected from among the token instances. The token instance of interest is selected based on attention levels computed utilizing a model for predicting interest in token instances. In one example embodiment, the token instance of interest is a token instance for which attention level of the user is higher than at least one other token instance.

Abstract: Systems and methods that enable a reduction in the power consumption involved in measuring a user's affective response to content. The reduction in the power consumption is achieved by utilizing tags that indicate a mode of operation in which to operate a sensor when measuring affective response of the user to certain segments of the content. By using at different times, different modes of operation for operating the sensor, which are characterized by different energy consumption rates, the total power consumption of the sensor may be reduced.

Abstract: Utilizing eye tracking to collect naturally expressed affective responses for training an emotional response predictor, comprising: receiving a vote of a user on a segment of content consumed by the user; receiving eye tracking data of the user taken while the user consumed the segment of content; determining, based on the eye tracking data, that a gaze-based attention level to the segment reaches a predetermined threshold; utilizing the vote to generate a label related to an emotional response to the segment; receiving an affective response measurement of the user taken substantially while the user consumed the segment of content; and training a measurement emotional response predictor with the label and the affective response measurement.

Abstract: Some aspects of this disclosure include systems, methods, and/or computer programs that may be used to determine a cause of an inaccuracy in predicted affective response to an event that involves a user who has an experience. Some embodiments described herein involve identifying when a difference between a measurement of affective response corresponding to an event is different from the predicted affective response corresponding to the event. When such a discrepancy is identified, a presentation is made to the user of at least one of the following: one or more factors characterizing the event, and effects of the one or more factors on the user, as determined based on a model of the user. Based on a comment made by the user in response to the presentation, at least one of the following is identified: a discrepancy in a description of the event, and an inaccuracy in the model.

Abstract: Some aspects of this disclosure include systems, methods, and/or computer programs that may be used to notify a user about a cause of emotional imbalance. Some embodiments described herein involve determining when a user is in a state of emotional imbalance based on a measurement of affective response of the user, which is taken with a sensor. Factors characterizing an event to which the measurement corresponds are examined in order to select a certain factor that, based on a model of the user, has an effect on the user that is congruous with the measurement of affective response. The user is notified about the certain factor in order to make the user more aware of the certain factor and its effect on the user.

Abstract: Some aspects of this disclosure include systems, methods, and/or computer programs that may be used to collect measurements of affective response of users and to utilize the collected measurements to generate a crowd-based result, such as a score for an experience which the users had. Some embodiments described herein involve sending requests for measurements of affective response to software agents operating on behalf of the users. The requests may provide details regarding the type of measurements requested and may also provide assurances. The assurances may relate to various aspects such as the number of users whose measurements are to be used to generate the crowd-based result, the disclosure of the crowd-based result (e.g., regarding the recipients of the crowd-based result), and the compensation for providing the measurements. Software agents that accept the assurances and have relevant measurements may provide the measurements, which are then utilized to generate the crowd-based result.

Abstract: 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.

Abstract: Some aspects of this disclosure involve generation of crowd-based results based on measurements of affective response of users. In some embodiments described herein, sensors are used to take measurements of affective response of at least ten users who were at a certain location. The measurements may include various values indicative of physiological signals and/or behavioral cues of the at least ten users. Some examples of locations in this disclosure include vacation destinations, businesses, establishments that provide entertainment, certain geographical regions, and virtual environments. User interfaces are configured to receive data describing a location score computed based on the measurements of the at least ten users, which represents the affective response of the at least ten users to being at the certain location. The user interfaces may be used to report the location score (e.g., to a user who may be interested in visiting the certain location).

Abstract: Some aspects of this disclosure include systems, methods, and/or computed readable media that may be used to generate crowd-based results based on measurements of affective response of users. In some embodiments described herein, sensors are used to take measurements of affective response of at least ten users who have a certain experience. The measurements may include various values indicative of physiological signals and/or behavioral cues of the at least ten users. Some examples of experiences mentioned herein include going on vacations, eating in restaurants, and utilizing various products. User interfaces are configured to receive data describing a score computed based on the measurements of the at least ten users, which represents the affective response of the at least ten users to having the certain experience. The user interfaces may be used to report the score (e.g., to a user who may be interested in having the certain experience).

Abstract: Some aspects of this disclosure involve computation of a preference score for a certain type of food. In some embodiments described herein, measurements of affective response of at least ten users are collected. The measurements may include various values indicative of physiological signals and/or behavioral cues of the at least ten users. Each measurement of a user is taken with a sensor coupled to the user up to four hours after the user consumed the certain type of food. A preference score is computed based on the measurements. The preference score is indicative of how much the at least ten users enjoyed consuming the certain type of food and/or how well they felt after consuming the certain type of food.

Abstract: A system, method, and computer product for reducing volume of transmissions of measurements of affective response are described herein. In one embodiment, an interaction analyzer receives a description of an interaction of a user with a media controller that controls presentation of content to the user. The interaction analyzer identifies from the description an action that causes a deviation from a progression of presentation of the content that would have occurred had the action not taken place. A transmitter sends a request to transmit measurements of affective response, taken by a sensor, during a window during which the user likely expressed an affective response related to the action. In some embodiments, the request is received by a transceiver coupled to the sensor with memory sufficient to store measurements of affective response of the user taken since the start of the window, which precedes the time the request is sent.

Abstract: Described herein are methods for training a predictor of a user's emotional response to stimuli (e.g., digital content). In order to more accurately learn the nature of the emotional response of the user to the stimuli, in some embodiments, the training of the predictor involves collection of attention level data that indicates to which objects the user paid attention. The attention level data may be utilized to weight token instances representing visual objects from the stimuli. Such a weighting can help to train the emotional response predictor to better determine which objects influence the user's affective response and/or the extent of their influence on the user's affective response. In different embodiments, attention level information may come from different sources, such as eye tracking data of the user, and a model for predicting an interest level of the user in various visual objects.

Abstract: Systems and methods that enable a reduction in the power consumption involved in measuring a user's affective response to content. The reduction in the power consumption is achieved by utilizing tags that indicate a mode of operation in which to operate a sensor when measuring affective response of the user to certain segments of the content. By using at different times, different modes of operation for operating the sensor, which are characterized by different energy consumption rates, the total power consumption of the sensor may be reduced.

Abstract: This disclosure describes systems, methods, and computer program products that may be used to provide crowd-based scores for experiences, which are computed based on measurements of affective response of multiple users who had the experiences. The measurements of affective response may be collected using a wide array of sensors that measure physiological signals and/or behavioral cues. Additionally, the scores may be personalized for a certain user based on similarities between a profile of the certain user and profiles of the multiple users.

Abstract: Systems and methods that enable a reduction of the power consumption involved in measuring a user's affective response to content with a sensor belonging to a wearable device. The reduction in power consumption is achieved by utilizing eye tracking to determine when a user is paying attention to the content, and accordingly setting a mode of operation of the wearable device to measure the user. Thus, by using different modes of operation, which are characterized by different energy consumption rates, the total power consumption of the wearable device may be reduced, essentially without loss of relevant measurements.

Abstract: Generating a situation-dependent library comprising a user's expected response to tokens representing stimuli that influence the user's affective state, including: receiving samples comprising temporal windows of token instances to which the user was exposed, wherein the token instances have overlapping instantiation periods and are spread over a long period of time that spans different situations; wherein at least one token is expected to elicit from the user a noticeably different affective response in the different situations; receiving target values corresponding to the temporal windows of token instances; the target values represent the user's responses to the token instances from the temporal windows of token instances; training a machine learning-based user response model using the samples and the corresponding target values; and analyzing the machine learning-based user response model to generate the situation-dependent library comprising the user's expected response to tokens, which accounts for the

Abstract: Described herein are systems, methods, and computer program products for collecting naturally expressed affective responses for training an emotional response predictor utilizing voting on content. In one embodiment, a label generator is configured to receive a vote, provided by a user, on a segment of content consumed by the user. The label generator determines whether the user consumed the segment during a duration that is shorter than a predetermined threshold, and utilizes the vote to generate a label related to an emotional response to the segment. A training module receives the label and measurement of an affective response of the user taken, at least in part, during a period that starts at most 30 seconds before the vote is provided, and trains the emotional response predictor with the measurement and the label.

Abstract: Systems and methods that enable a reduction of the power consumption involved in measuring a user's affective response to content with a sensor belonging to a wearable device. The reduction in power consumption is achieved by utilizing eye tracking to determine when a user is paying attention to the content, and accordingly setting a mode of operation of the wearable device to measure the user. Thus, by using different modes of operation, which are characterized by different energy consumption rates, the total power consumption of the wearable device may be reduced, essentially without loss of relevant measurements.