Circular Grid GUI for Tracking Daily Activities
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Solution Overview
Problem
Conventional data collection methods for human behavior analysis, such as questionnaires, often require high sampling rates and result in excessive information, leading to user fatigue and decreased data quality due to the complexity of capturing varied daily activities in a succinct manner.
Innovation Solution
A graphical user interface (GUI) featuring a circular grid with concentric circles divided into radial slices, allowing users to easily input and track activities over time, with each slice representing a time segment and each circle representing an activity category, facilitating efficient data entry and organization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high sampling rates are used to capture short time-scale neurological responses, then measurement precision is improved, but loss of time increases due to the significant amount of information that needs to be processed
Solution Approach 1:
The patent extracts only the essential activity information needed for analysis, discarding redundant detailed data. The system identifies and collects key behavioral events rather than continuously sampling all neurological responses, thus maintaining measurement precision for important events while reducing overall data volume and processing time.
Solution Approach 2:
The patent segments continuous time into discrete activity periods or epochs. Instead of analyzing continuous high-rate data, the system divides behavior into distinct segments or bouts of activity, which reduces the computational burden while preserving the essential temporal patterns of behavior.
2Measurement precision
If questionnaire methods are used to collect detailed behavioral data, then measurement precision is improved, but device complexity increases due to the large number of questions required
Solution Approach 1:
The patent extracts only the most relevant behavioral variables needed for the research questions, eliminating unnecessary questionnaire items. By identifying and collecting only essential data points related to circadian rhythms and sleep-wake behavior, the system maintains data quality while significantly reducing questionnaire length and complexity.
3Adaptability or versatility
If all permutations of human activities are explicitly included in the questionnaire, then adaptability is improved, but device complexity increases due to the very large number of potential answers
Solution Approach 1:
The patent uses universal activity categories that can encompass multiple specific permutations of human activities. Instead of listing every possible activity variation, the system employs broad categories (such as sleep-wake states, activity intensity levels, or general activity types) that can represent numerous specific behaviors, thus maintaining adaptability while reducing complexity.
4Adaptability or versatility
If conventional questionnaire formats are used to capture varied daily activities, then adaptability is improved, but ease of operation deteriorates due to user fatigue from excessive questions
Solution Approach 1:
The patent extracts and prioritizes only the most critical behavioral information needed for circadian rhythm analysis, removing extraneous questions that contribute to user fatigue. By focusing on essential sleep-wake patterns and major activity transitions, the system maintains comprehensive behavior capture capability while significantly improving ease of operation and reducing dropout rates.
Data Source
AI summary
A system for generating a graphical user interface for tracking and displaying user activities over a predetermined time period is provided. The system includes a presentation component configured to display a graphical user interface that facilitates receiving user input regarding daily activities of the user, wherein the interface comprises a chart comprising a plurality of input compartments defined by a plurality of concentric circles divided into a plurality of slices, wherein each of the concentric circles are associated with a different input category and each of the slices are associated with a different time frame of a time period.