Smart Ring Gesture Activation Using Context-Aware Recognition Windows
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Solution Overview
Problem
Existing devices are difficult to use in hands-free or one-handed manners, especially when users are wearing gloves, have wet or dirty hands, or have motor skill challenges, and current gesture recognition systems are often large, expensive, power-hungry, and limited to specific applications.
Innovation Solution
A hand-wearable device, such as a smart ring, uses sensor data to generate embeddings based on user movement and device activity, determining when to initiate gesture recognition through contextual awareness and machine learning to differentiate between casual and intentional motions, reducing false positives and conserving power.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If gesture recognition is continuously performed, then gesture control accuracy is improved, but power consumption increases
Solution Approach 1:
The system dynamically adjusts gesture recognition activation based on contextual conditions. Gesture recognition is enabled only when specific conditions are met (proximity detection, device state, motion patterns), rather than running continuously. This dynamic activation reduces power consumption while maintaining gesture control accuracy when needed.
Solution Approach 2:
The system uses feedback from sensors (proximity sensors, motion sensors, device state monitors) to determine when to activate gesture recognition. This feedback mechanism allows the system to intelligently decide when gesture recognition should be performed, balancing accuracy requirements with power conservation by avoiding unnecessary recognition attempts.
2Ease of operation
If gesture recognition is always active, then gesture identification capability is improved, but false positives increase
Solution Approach 1:
The system performs preliminary checks before activating gesture recognition, including proximity detection and device state verification. These preliminary actions filter out conditions that would likely result in false positives, ensuring that gesture recognition is only attempted when the context suggests intentional user input.
Solution Approach 2:
The system changes operational parameters (activation state of gesture recognition) based on detected conditions. By adjusting when gesture recognition is active versus inactive based on sensor inputs and device state, the system maintains high gesture identification capability while minimizing false positives through contextual parameter adjustment.
3Adaptability or versatility
If traditional gesture recognition systems are used, then gesture control functionality is provided, but device size and cost increase
Solution Approach 1:
The system uses existing sensors (proximity sensors, motion sensors, device state monitors) for multiple purposes: their primary functions plus gesture recognition activation. This multi-functionality eliminates the need for dedicated gesture recognition hardware, reducing device size and cost while maintaining gesture control functionality.
Solution Approach 2:
The system leverages data already being collected by existing sensors for gesture recognition purposes. Rather than requiring separate dedicated sensors or hardware components, the system repurposes existing sensor data, allowing the device to serve itself for gesture control without additional complexity.
Data Source
AI summary
A method includes obtaining information associated with movement of a hand-wearable device that is worn by a user of an electronic device, information identifying a proximity of the hand-wearable device to the electronic device, and information associated with activity of the electronic device including usage of the electronic device and one or more applications of the electronic device by the user. The method also includes generating embeddings associated with body motion by the user and with the activity of the electronic device using at least some of the information. The method further includes determining whether gesture recognition is to be performed based on the embeddings. In addition, the method includes, in response to determining that gesture recognition is to be performed, identifying a gesture recognition window and initiating gesture recognition in order to identify one or more gestures by the user involving the hand-wearable device during the gesture recognition window.