Glove Joint Calibration Using Dynamic Angle Mapping
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Solution Overview
Problem
Existing technologies face challenges in accurately calibrating glove data for precise recognition and restoration of hand movements due to individual differences and variations in finger flexibility and strength, leading to inaccurate mapping relationships between sensing data and joint angles.
Innovation Solution
A method and system for calibrating glove data by updating preset data ranges and mapping relationships using designated hand actions, such as fist-clenching and finger-spreading, to adapt to individual user variations, incorporating strain and inertial sensors to measure finger joint angles accurately.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If preset data ranges and mapping relationships are fixed, then device complexity is reduced, but measurement precision deteriorates due to individual differences in finger flexibility and strength
Solution Approach 1:
The system performs preliminary calibration actions (fist clenching, finger spreading) to collect sensing data before establishing the mapping relationship. This preliminary data collection allows the system to adapt to individual user characteristics before actual measurement, resolving the contradiction by preparing personalized parameters in advance without requiring complex real-time adjustment mechanisms
Solution Approach 2:
The calibration process enables the system to automatically adapt to each user's individual characteristics through self-collected sensing data during designated actions. The system serves itself by generating personalized mapping relationships without requiring external calibration equipment or complex manual adjustment, thereby improving measurement precision while maintaining simple device architecture
2Adaptability or versatility
If fixed mapping relationships are used, then ease of operation is improved, but adaptability deteriorates due to variations in finger flexibility and strength among different users
Solution Approach 1:
The mapping relationship transitions from a static fixed value to a dynamic personalized parameter. The system dynamically adjusts the mapping relationship based on sensing data collected during calibration actions, allowing the glove to adapt to each user's unique finger characteristics while maintaining simple operation through automated adjustment processes
Solution Approach 2:
The system changes the parameters of the mapping relationship based on collected sensing data. By adjusting the mapping parameters according to individual user characteristics obtained during calibration actions, the system achieves high adaptability without requiring complex manual configuration, as the parameter adjustment is automatically performed based on measured data
Data Source
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AI summary
Provided is a method for calibrating glove data. The method includes: obtaining first sensing data relating to a target finger joint of a user, the first sensing data being collected using at least one sensor, each of the at least one sensor being arranged in a glove body worn by the user and located at or near the target finger joint; obtaining a preset data range corresponding to the first sensing data, there is a first mapping relationship between data in the preset data range and a joint angle of the target finger joint; in response to determining that the first sensing data is outside the preset data range, updating the preset data range; and determining a second mapping relationship between data in the updated preset data range and the joint angle of the target finger joint.