Gesture Struggle Detection via Interaction Data Analysis
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Solution Overview
Problem
Current technologies lack effective methods to accurately detect user struggles while interacting with user interfaces on computing devices, which can lead to poor user experience and inefficient UI design.
Innovation Solution
A method that involves obtaining user interaction data, identifying user gestures, calculating a struggle factor score, and comparing it to a baseline value derived from historical data to determine if a user is experiencing struggle, allowing for UI modifications to improve user interaction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If user interaction data is collected and analyzed to detect gesture struggle, then user experience can be improved through UI modifications, but device complexity increases due to data processing requirements
Solution Approach 1:
The patent extracts and analyzes specific gesture characteristics from user interaction data, such as touch duration, movement trajectory, and interaction frequency. By focusing on these specific extracted features rather than processing all raw interaction data, the system reduces processing complexity while still achieving effective struggle detection.
Solution Approach 2:
The patent segments the user interaction process into distinct gestures and interaction patterns. Each gesture is analyzed separately for struggle indicators, allowing the system to process data in manageable units rather than handling the entire interaction stream at once, thus reducing overall processing complexity.
2Measurement precision
If historical data is collected and compared to establish baseline values, then detection accuracy improves, but loss of time increases due to data storage and processing requirements
Solution Approach 1:
The patent uses partial historical data for establishing baseline values rather than requiring complete historical records. By using a representative sample of historical interaction data, the system achieves sufficient detection accuracy without the time cost of processing and storing all historical data.
Solution Approach 2:
The patent performs preliminary analysis of historical data to establish baseline values before actual struggle detection occurs. These pre-computed baselines serve as reference points for rapid comparison during real-time interaction analysis, reducing the time needed for detection while maintaining accuracy.
Data Source
AI summary
A computer implemented method is disclosed. The method includes obtaining, by at least one processor, data of user interaction with an application in a user session in a given computing environment. The method further includes identifying a user gesture interacting with a user interface of the application on a screen of a computing device based on the data. The method further includes calculating a struggle factor score for the user gesture based on the data. The method further includes comparing the struggle factor score with a baseline value, wherein the baseline value is derived from historical information of past user sessions in a computer environment like the given computing environment. The method further includes determining that the user gesture indicates a user struggle in response to a determination that the struggle factor score is above the baseline value.