Physiological Sensor Headset for Objective Media Rating
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Solution Overview
Problem
Existing methods for analyzing viewers' responses to media are limited by cognitive biases and lack objectivity, as they rely on averaged survey responses or incomplete physiological data, which fail to accurately benchmark or compare media or events objectively.
Innovation Solution
A bottom-up analysis approach that derives physiological responses from measured data to calculate scores for event types and aggregate them for media rating, using sensors to record physiological data such as heart rate and brain waves, and an integrated headset for automated processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If top-down analysis using averaged survey responses or viewer knobs is used, then the analysis process is simple and easy to operate, but the measurement precision is poor due to cognitive bias and incomplete memory of viewers
Solution Approach 1:
The patent replaces the mechanical/cognitive system of survey responses and viewer memory with an automated physiological measurement system. Sensors objectively capture physiological data (heart rate, brain waves, muscle movement, galvanic skin response) during media consumption, eliminating cognitive bias and memory limitations while providing precise, objective measurements of viewer engagement and emotional response.
Solution Approach 2:
The system automatically collects, processes, and analyzes physiological data without requiring active participant input or memory recall. The physiological sensors continuously monitor and record viewer responses during media consumption, and the system autonomously processes this data to generate engagement metrics, removing the need for viewers to actively report their experiences.
2Reliability
If physiological data collection is implemented, then objective measurement of media ratings is improved, but the device complexity and data processing requirements increase
Solution Approach 1:
The patent segments the complex physiological data into distinct measurable components (heart rate, brain waves, muscle movement, galvanic skin response) and processes each separately. By breaking down the complex physiological signals into individual parameters that can be independently measured and analyzed, the system manages complexity while maintaining comprehensive objective measurement capability.
Solution Approach 2:
The system uses a multi-functional approach where a single integrated sensor suite captures multiple physiological parameters simultaneously, and the processing system handles diverse data types (cardiac signals, neural signals, muscular signals, skin conductance) through unified algorithms, reducing overall system complexity while achieving comprehensive measurement.
3Measurement precision
If bottom-up analysis aggregating individual physiological responses is used, then the accuracy and objectivity of media rating are improved, but the processing time and computational resources increase
Solution Approach 1:
The system performs preliminary processing of physiological data during the media consumption period itself, continuously monitoring and pre-processing signals to identify engagement patterns in real-time. This preliminary action reduces the computational burden during post-processing, as the bulk of data preparation and initial analysis is completed concurrently with media viewing, thereby reducing overall processing time.
Solution Approach 2:
The physiological data collection and preliminary analysis continue continuously during media consumption rather than requiring separate discrete processing steps. The system maintains continuous monitoring of physiological signals and continuously updates engagement metrics, eliminating idle processing time and ensuring that analysis is always current and ready for immediate use.
Data Source
AI summary
Various embodiments of the present invention enable a bottom up analysis approach that derives physiological responses from measured physiological data of viewers of a media, and calculates scores of instances of an event type based on the physiological responses. The scores are then aggregated to rate the event type in addition to scoring the individual event instances. The approach can also form an overall rating of the media by aggregating the event ratings of set of event types within the media.