Neuromuscular Gesture Detection for Minimal-Motion Text Editing
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Solution Overview
Problem
Existing wearable devices require full-range and socially unacceptable movements for gesture recognition, limiting their use in confined spaces and increasing energy expenditure, and lack efficient integration of multiple input modalities for text production and modification.
Innovation Solution
Wearable devices detect neuromuscular signals from in-air hand gestures, such as thumb-to-finger gestures, to perform commands with minimal movement, reducing energy expenditure and enabling efficient integration of speech-to-text and neuromuscular gesture control for text input and modification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If full-range user movements are used for gesture detection, then gesture recognition capability is improved, but energy expenditure and space requirements increase
Solution Approach 1:
The patent segments the gesture recognition task into two parts: (1) detecting neuromuscular signals at the wrist to identify intended gestures, and (2) using computer vision to verify hand positions. This segmentation allows detection of subtle muscle signals without requiring full-range movements, thereby reducing energy expenditure while maintaining recognition accuracy.
Solution Approach 2:
The patent introduces neuromuscular sensors as an intermediary between the user's intent and the device control. These sensors detect electrical signals from muscle contractions before the actual movement occurs, enabling gesture recognition with minimal physical movement and reduced energy consumption.
2Measurement precision
If full-range user movements are used for gesture detection, then gesture recognition capability is improved, but social acceptability deteriorates
Solution Approach 1:
By segmenting gesture detection into neuromuscular signal detection and computer vision verification, the system can recognize gestures from subtle muscle signals that do not require large visible movements, making the interaction socially acceptable in public settings.
Solution Approach 2:
The neuromuscular sensors detect muscle activation signals before the actual hand movement occurs. This preliminary detection allows the system to prepare for the gesture in advance, enabling recognition of intended gestures with minimal visible movement, thereby improving social acceptability.
3Adaptability or versatility
If multiple input modalities are integrated for text production and modification, then functionality is improved, but system complexity increases
Solution Approach 1:
The patent merges multiple input modalities (neuromuscular gesture detection, computer vision, and speech-to-text) into a unified system that works synergistically. The neuromuscular sensors provide intent detection, computer vision verifies hand positions, and speech-to-text handles verbal commands, creating a cohesive multi-modal input system for comprehensive text production and modification.
Solution Approach 2:
The system implements multi-functionality by enabling the wearable device to handle various text operations (input, editing, formatting, sending) through a single integrated platform that supports multiple input modalities. This universal approach allows one system to perform diverse text-related tasks without requiring separate specialized devices.
Data Source
AI summary
The various implementations described herein include methods and systems for producing and modifying text using neuromuscular-signal-sensing devices. In one aspect, a method includes causing the display of a plurality of text terms input by a user. Using data from one or more neuromuscular-signal sensors in communication with the wearable device, an in-air hand gesture performed by the user is detected while the text terms are displayed. In response to the in-air hand gesture, a text-modification mode is enabled that allows for modifying the text terms input by the user. A target term is identified and, while the text-modification mode is enabled, data about a voice input provided by the user for modifying the target term is received. The method further includes causing a modification to the target term in accordance with the voice input from the user.