Physiological Content Selection Using Pre-Extracted Variables
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Solution Overview
Problem
Existing systems for selecting content data based on user physiological responses require a learning period to accumulate data, limiting their functionality before adaptation and failing to provide accurate recommendations when encountering new or vastly different content styles.
Innovation Solution
A method that stores and updates data on the relation between content element characteristics and user physiological responses, allowing for selection based on data from other users, enabling immediate and personalized content recommendations without a learning period, using a database that associates content items with physiological responses and incorporates user personality types for tailored suggestions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the system accumulates data through a learning period to improve recommendation accuracy, then measurement precision improves, but loss of time increases due to the required learning period before functionality begins
Solution Approach 1:
The system performs preliminary actions by pre-processing content data items during ingestion, extracting variables and storing them in the database before they are needed for recommendations. This allows the system to be immediately functional when a user first uses it, without requiring a learning period to accumulate data about user preferences for content styles that have already been analyzed and stored
Solution Approach 2:
The system uses universal content variables (tempo, energy, duration, genre) that can be extracted from any content data item regardless of style or type. This multi-functional approach allows the same data structure and processing methodology to handle diverse content types, enabling immediate recommendations across different content styles without requiring separate learning periods for each style
2Ease of operation
If the system uses mood or genre classifications to categorize content, then ease of operation improves, but manufacturing precision deteriorates because no well-defined relation exists between genre classifications and music characteristics
Solution Approach 1:
The system changes the parameters used for classification from subjective categories (mood, genre) to objective, measurable variables (tempo, energy, duration). These physical parameters can be precisely extracted from content data and directly correlated with physiological responses, providing both ease of operation through standardized measurements and manufacturing precision through well-defined quantitative relationships
Solution Approach 2:
The system replaces the mechanical/classification-based approach (manual mood or genre labeling) with a data-driven approach using extracted variables from content analysis. Instead of relying on predefined categorical systems that lack consistent relationships with physiological responses, the system uses measurable content characteristics that have direct, quantifiable correlations with user physiological data
Data Source
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AI summary
A method of enabling the selection of an item of content data based on an expected physiological response of a user, each item of content data being associated with at least one recording of a perceptible content element, includes storing a first set (18) of data representative of a relation between at least one variable for characterizing an aspect of a perceptible content element and a physiological response of at least one first user when the perceptible content element is rendered. The first set (18) of data representative of the relation is adapted on the basis of a measured physiological response of the at least one first user to a rendition of a perceptible content element and values of the at least one variable for characterizing an aspect of the perceptible content element. An expected physiological response is associated with an item of content data using a further set (20,21) of data representative of a relation between at least one variable for characterizing an aspect of a perceptible content element and a physiological response of a user, which further set (20,21) is based on the physiological response of at least one other user than the first user.