In-Air Hand Gesture Text Editing With Neuromuscular Signal Detection
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Solution Overview
Problem
Existing wearable devices for text production and modification in augmented-reality and virtual-reality environments require full-range user movements, which are socially unacceptable, energy-consuming, and space-demanding, limiting their adoption and use to specific cases like gaming in large open spaces.
Innovation Solution
The use of neuromuscular-signal-based detection for in-air hand gestures, such as thumb-to-finger gestures, allows for minimal user movement and efficient text input and modification, reducing the need for large gestures and energy expenditure, and enabling socially acceptable, compact device design.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If full-range user movements are used for gesture detection, then gesture recognition accuracy is improved, but energy consumption and space requirements increase
Solution Approach 1:
The patent segments the gesture recognition task into two parts: (1) detecting minimal hand/finger movements using wearable sensors, and (2) using voice commands to supplement and clarify intent. This segmentation allows accurate gesture recognition without requiring full-range movements, thereby reducing energy consumption while maintaining recognition accuracy.
Solution Approach 2:
The patent introduces voice commands as an intermediary modality that works synergistically with minimal hand gestures. The voice input serves as a mediator that confirms or clarifies the intent behind subtle hand movements, enabling accurate gesture recognition without requiring the user to perform energy-consuming full-range movements.
2Measurement precision
If full-range user movements are used for gesture detection, then gesture recognition accuracy is improved, but social acceptability deteriorates
Solution Approach 1:
The patent segments the interaction into subtle hand gestures detectable by wearable sensors combined with voice commands. This segmentation enables accurate gesture recognition using minimal, discreet movements that are socially acceptable in public settings, unlike full-range movements that would be conspicuous and socially unacceptable.
Solution Approach 2:
Voice commands serve as an intermediary that allows users to communicate intent without performing conspicuous hand movements. This combination of minimal gestures with voice input maintains gesture recognition accuracy while improving social acceptability by enabling discreet interaction in public spaces.
3Adaptability or versatility
If multiple input modalities are combined for text production and modification, then functionality is improved, but system complexity increases
Solution Approach 1:
The patent implements a universal input system where wearable sensors, voice recognition, and gesture detection work together as integrated modalities. This multi-functional approach enables both text production and text modification using the same sensor suite and processing framework, improving versatility without proportionally increasing system complexity through shared hardware and unified software architecture.
Solution Approach 2:
The patent merges gesture detection, voice recognition, and text processing functions into an integrated system. By combining these modalities into a unified input framework where sensors and voice processing work synergistically, the system achieves enhanced text production and modification functionality while managing complexity through integrated design rather than separate independent systems.
Data Source
AI summary
An example method includes causing the display of a plurality of text terms in a first mode. A first in-air hand gesture performed by a user is detected while the plurality of text terms are displayed in the first modes. In response to the first in-air hand gesture, a text-modification mode different from the first mode is enabled, that allows the user to identify and modify one or more of the plurality of text terms. A targe term is identified based at least in part on a first user action and, while the text-modification mode is enabled, modifying the target term based at least in part on a second user action. The method further includes that none of the plurality of displayed text terms can be identified or modified in the first mode.