Wearable Gesture Recognition via Sensor Correlation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing user interfaces, particularly pressure-sensitive membranes, face challenges in distinguishing between intended and unintended gestures, leading to false positives and inefficient interaction.
Innovation Solution
A method and apparatus that utilize pressure sensors and environmental sensors to correlate inputs, determining whether a gesture is intentional by analyzing parameters such as peak number, magnitude, time of start and stop, and speed of change, and comparing these with environmental conditions to classify inputs accurately.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If pressure sensors are used to detect user input on flexible material, then input detection capability is improved, but false positives from unintended gestures increase
Solution Approach 1:
The patent introduces environmental sensors as intermediary components that detect contextual information (motion, orientation, ambient conditions) to mediate between the pressure sensor input and the final gesture recognition decision. These sensors provide additional data that helps distinguish intended gestures from unintended movements, thereby reducing false positives while maintaining detection accuracy.
Solution Approach 2:
The system changes the parameters used for gesture recognition by incorporating multiple sensor types (pressure, motion, orientation, environmental conditions) and analyzing temporal patterns, peak characteristics, and correlation between different sensor inputs. This multi-parameter approach enables more accurate differentiation between intentional and unintentional gestures.
2Measurement precision
If multiple sensors are used to differentiate gestures, then accuracy is improved, but device complexity increases
Solution Approach 1:
The patent makes the sensor system multi-functional by using environmental sensors to serve multiple purposes: detecting motion, orientation, ambient conditions, and temporal patterns. This allows a single sensor to contribute to multiple aspects of gesture recognition, improving accuracy without proportionally increasing system complexity.
Solution Approach 2:
The system merges data from multiple sensor types (pressure sensors, motion sensors, environmental sensors) into a unified gesture recognition process. By combining these sensor inputs and analyzing their correlations, the system achieves high classification accuracy while managing complexity through integrated processing.
3Reliability
If environmental sensors are integrated with pressure sensors, then intended gesture detection is improved, but manufacturing complexity increases
Solution Approach 1:
The patent implements sensors on flexible material that can be conformally integrated into wearable devices. This flexible substrate approach simplifies manufacturing by allowing sensors to be manufactured as thin-film structures that can be easily integrated into the wearable device architecture, reducing the complexity of assembling rigid sensor components.
Data Source
AI summary
Techniques are described to discern between intentional and unintentional gestures. A device receives a first input from one or more sensors that are coupled to a flexible material to detect input from the user provided by manipulation of the flexible material. In addition, the device receives a second input from one or more environmental sensors that are coupled to the user to detect environmental conditions associated with the user. The device correlates the first input and the second input to determine whether the first input is an intentional input by the user.