# US 2014/0195221 A1 · Utilizing semantic analysis to determine how to measure affective response > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2014/0195221 A1 - Document ID: US20140195221A1 - Status: Published application - Kind: A1 - Application number: 14/227,020 - Filed: 2014-03-27 - Published: 2014-07-10 - Earliest claimed: 2012-10-14 - Inventors: Ari M. Frank; Gil Thieberger - Web page: https://patentgrep.com/patent/US20140195221A1 ## CPC - G06F 1/3206: Monitoring of events, devices or parameters that trigger a change in power modality - G06F 1/28: Supervision thereof, e.g. detecting power-supply failure by out of limits supervision - G06F 1/3212: Monitoring battery levels, e.g. power saving mode being initiated when battery voltage goes below a certain level - G06F 1/3234: Power saving characterised by the action undertaken - G06F 1/3296: by lowering the supply or operating voltage - G06F 3/013: {Eye tracking input arrangements (G06F3/015 takes precedence)} - G06F 3/015: {Input arrangements based on nervous system activity detection, e.g. brain waves [EEG] detection, electromyograms [EMG] detection, electrodermal response detection} - G06F 9/46: Multiprogramming arrangements - G06F 40/40: Processing or translation of natural language (natural language analysis G06F40/20; semantic analysis G06F40/30) - G06N 5/04: Inference or reasoning models - G06N 7/01: Probabilistic graphical models, e.g. probabilistic networks - G06N 20/00: Machine learning - G06F 40/30: Semantic analysis - G06F 2203/011: Emotion or mood input determined on the basis of sensed human body parameters such as pulse, heart rate or beat, temperature of skin, facial expressions, iris, voice pitch, brain activity patterns - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) - G06N: COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS ## Abstract A semantic analyzer receives a segment of content, analyzes it utilizing semantic analysis, and outputs an indication regarding whether a value related to a predicted emotional response to the segment reaches a predetermined threshold. Based on the indication, a controller selects a measuring rate, from amongst at least first and second measuring rates, at which a device is to take measurements of affective response of a user to the segment. The first rate may be selected when the value does not reach the predetermined threshold, while the second mode may be selected when the value does reach it. The device takes significantly fewer measurements while operating at the first measuring rate, compared to number of measurements it takes while operating at the second measuring rate. ## Claims ### Claim 1 A system configured to use semantic analysis to measure affective response at varying measuring rates, comprising: a semantic analyzer configured to: receive a first segment of content, analyze the first segment utilizing semantic analysis, and output a first indication that a first value related to a predicted emotional response to the first segment does not reach a first predetermined threshold; wherein the first segment comprises data representing text; and a controller configured to select, based on the first indication, a first measuring rate for a device for measuring affective response of a user to the first segment; the semantic analyzer is further configured to: receive a second segment of content, analyze the second segment utilizing semantic analysis, and output a second indication that a second value related to a predicted emotional response to the second segment does reach a second predetermined threshold; wherein the second segment comprises data representing text; the controller is further configured to select, based on the second indication, a second measuring rate for the device for measuring affective response of the user to the second segment; wherein the device takes significantly fewer measurements of affective response, per unit of measurement time, while operating at the first measuring rate, compared to number of measurements of affective response the device takes while operating at the second measuring rate. ### Claim 2 (depends on 1) The system of claim 1, wherein the first and second predetermined thresholds represent first and second confidence levels in predictions of emotional response, respectively; and wherein the first and second values represent confidence in predictions of emotional response to the first and second segments, respectively; whereby the first measuring rate is selected when the first indication indicates that confidence in a prediction of emotional response to the first segment does not reach the first confidence level, and the second measuring rate is selected when the second indication indicates that confidence in a prediction of emotional response to the second segment does reach the second confidence level. ### Claim 3 (depends on 1) The system of claim 1, wherein the first and second predetermined thresholds represent first and second magnitudes of change in affective response, respectively; and wherein the first and second values represent predicted changes in affective response due to exposure to the first and second segments, respectively; whereby the first measuring rate is selected when the first indication indicates that a predicted change in affective response due to exposure to the first segment does not reach the first magnitude, and the second measuring rate is selected when the second indication indicates that a predicted change in affective response due to exposure to the second segment does reach the second magnitude. ### Claim 4 (depends on 1) The system of claim 1, wherein the first and second predetermined thresholds represent first and second benefit levels, respectively; and wherein the first and second values represent predicted benefits to measuring affective response to the first and second segments, respectively; whereby the first measuring rate is selected when the first indication indicates that a predicted benefit of measuring affective response to the first segment does not reach the first benefit level, and the second measuring rate is selected when the second indication indicates that a benefit of measuring affective response to the second segment does reach the second benefit level. ### Claim 5 (depends on 1) The system of claim 1, wherein the first measuring rate is substantially zero, and when operating at the first measuring rate the device substantially does not take affective response measurements of the user. ### Claim 6 (depends on 1) The system of claim 1, wherein the device is one or more of the following: a physiological sensor, and an image capturing device. ### Claim 7 (depends on 1) The system of claim 1, further comprising a module configured to train an emotional response predictor (measurement ERP) based on feature values that are a product of measurements of the affective response of the user to the second segment of content and a label based on the second indication generated by the semantic analyzer. ### Claim 8 (depends on 1) The system of claim 1, wherein the semantic analyzer applies statistics on words that are correlated with certain emotional responses. ### Claim 9 (depends on 1) The system of claim 1, wherein the semantic analyzer applies Latent Semantic Analysis in order to associate a segment of content with a likely subject. ### Claim 10 (depends on 1) The system of claim 1, wherein the semantic analyzer evaluates the second segment shortly before the user is exposed to the second segment, whereby shortly is less than one minute. ### Claim 11 (depends on 1) The system of claim 1, wherein the second segment is received from an interactive computer game that provides context information about the second segment that may be utilized by the semantic analyzer to compute the second indication. ### Claim 12 A method for utilizing semantic analysis to set a measuring rate of a device that measures affective response, comprising: receiving a first indication derived from an evaluation comprising semantic analysis of a first segment of content; wherein the first segment comprises data representing text; determining that the first indication indicates that a first value related to a prediction of emotional response to the first segment does not reach a first predetermined threshold, and configuring the device to measure, at a first measuring rate, affective response of a user to the first segment; receiving a second indication derived from an evaluation comprising semantic analysis of a second segment of content; wherein the second segment comprises data representing text; and determining that the second indication indicates that a second value related to a prediction of emotional response to the second segment reaches a second predetermined threshold, and configuring the device to measure, at a second measuring rate, affective response of the user to the second segment; wherein the device takes significantly fewer measurements of affective response, per unit of measurement time, while operating at the first measuring rate, compared to number of measurements of affective response the device takes while operating at the second measuring rate. ### Claim 13 (depends on 12) The method of claim 12, wherein the semantic analysis of the data derived from the second segment is performed shortly before the user is exposed to the second segment, whereby shortly is less than one minute. ### Claim 14 (depends on 12) The method of claim 12, wherein the first and second indications indicate confidence in predictions of emotional response to the first and second segments, respectively; whereby based on the first indication, it is determined that confidence in the prediction of the emotional response to the first segment does not reach the first predetermined threshold, and based on the second indication, it is determined that confidence in the prediction of the emotional response to the second segment does reach the second predetermined threshold. ### Claim 15 (depends on 12) The method of claim 12, wherein the first and second indications indicate expected magnitudes of change in affective response due to exposure to the first and second segments, respectively; whereby based on the first indication, it is determined that expected magnitude of change in affective response due to exposure to the first segment does not reach the first predetermined threshold, and based on the second indication, it is determined that expected magnitude of change to affective response due to exposure to the second segment does reach the second predetermined threshold. ### Claim 16 (depends on 12) The method of claim 12, wherein the first and second indications indicate how beneficial it is to measure the affective response to the first and second segments, respectively; whereby based on the first indication, it is determined that benefit from measuring the affective response to the first segment does not reach the first predetermined threshold, and based on the second indication it is determined that benefit from measuring affective response to the second segment does reach the second predetermined threshold. ### Claim 17 (depends on 12) The method of claim 12, wherein the first measuring rate is substantially zero, and substantially no measuring of the affective response of the user to being exposed to the first segment takes place. ### Claim 18 (depends on 12) The method of claim 12, wherein the device comprises a battery powered physiological sensor, and measuring the affective response of the user to the second segment comprises utilizing the device to take a physiological measurement of the user. ### Claim 19 (depends on 12) The method of claim 12, wherein the device is part of a battery powered image capturing device, and measuring the affective response of the user to the second segment comprises utilizing the image capturing device to capture an image of the user. ### Claim 20 A system configured to enable a device to measure affective response at varying measuring rates based on semantic analysis of content, comprising: a receiver configured to receive first and second indications derived from evaluations comprising semantic analysis of first and second segments of content, respectively; wherein the first and second segments comprise data representing text; and wherein the first indication indicates that a first value, which is a function of emotional response the first segment, does not reach a first predetermined threshold, and the second indication indicates that a second value, which is a function of emotional response to the second segment, does reach a second predetermined threshold; a processor configured to select, based on the first and second indications, first and second measuring rates for measuring affective response, respectively; and a controller operable to configure the device to measure the affective response of a user according to the first and second measuring rates; wherein the device takes significantly fewer measurements, per unit of measurement time, while operating at the first measuring rate to measure affective response of the user to the first segment, compared to number of measurements the device takes while operating at the second measuring rate to measure affective response of the user to the second segment.