Wearable EMG Gesture Interface for Visual-Free Interaction
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Solution Overview
Problem
Current human-computer interfaces are cumbersome and unintuitive, failing to accurately recognize subtle gestures and requiring direct eye and finger concentration, which limits their effectiveness, especially with the shrinking size of IoT devices and the need for a closed feedback loop.
Innovation Solution
A wearable gesture-controlled system using bio-potential sensors, motion sensors, and haptic feedback actuators, integrated with a signal processor and communication controller, that detects and interprets electrical signals from nerve bundles in the wrist to enable intuitive gesture recognition and feedback without visual eye contact.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a touchscreen interface is used, then text input and general instructions can be given, but full concentration of eyes and fingers on the screen is required, making it inconvenient for complex interaction without visual contact
Solution Approach 1:
The patent replaces the mechanical touchscreen interface requiring finger contact with an EMG-based system that detects hand gestures through electrical signals from muscle activity. This substitution eliminates the need for direct finger contact with a screen, allowing gesture-based control without visual concentration on a display device.
Solution Approach 2:
The patent introduces EMG sensors as an intermediary between the user's hand gestures and the computer system. These sensors detect electrical signals from muscle activity and translate them into control commands, serving as a mediator that enables gesture recognition without requiring direct visual or tactile contact with the interface device.
2Ease of operation
If voice recognition is used, then hands are freed from typing, but the signal is difficult to decipher without additional signals and requires concentration
Solution Approach 1:
The patent substitutes voice recognition with EMG-based gesture recognition. Instead of processing acoustic signals that are difficult to decipher, the system directly detects electrical signals from muscle activity, providing more precise and easier-to-interpret control inputs that require less concentration.
3Ease of operation
If gesture recognition using computer vision is used, then hands are freed from typing, but the system is highly sensitive to numerous ambient parameters, reducing accuracy
Solution Approach 1:
The patent replaces computer vision-based gesture recognition with EMG sensor detection. This substitution eliminates sensitivity to ambient lighting, background complexity, and other environmental factors that plague vision-based systems, as EMG sensors directly measure electrical signals from muscle activity regardless of external conditions.
Solution Approach 2:
The patent uses EMG sensors as an intermediary that directly contacts the skin to detect muscle signals, providing a more reliable and less environmentally sensitive detection method compared to non-contact vision-based systems that are highly susceptible to ambient parameters.
4Measurement precision
If sEMG sensor array is located below the elbow, then hand gestures can be detected, but this location is inconvenient for most users and not widely accepted outside the medical community
Solution Approach 1:
The patent applies local quality by placing EMG sensors on the wrist, a location that is both convenient for users and effective for detecting hand gestures. This localized placement on the wrist rather than below the elbow maintains measurement precision while significantly improving ease of operation and user acceptance.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system provides accurate and intuitive gesture recognition, allowing users to interact with devices more efficiently and accessibly, enabling complex interactions without direct eye contact and enhancing usability for both general and visually impaired users.
Implementation Method 1
detects electrical signals from nerve bundles in the wrist
Implementation Method 2
at least one motion sensor capable of detecting movement
Implementation Method 3
at least one haptic feedback actuator capable of creating haptic feedback corresponding to signals from the computerized device
Data Source
AI summary
A gesture controlled system wearable by a user and operationally connected to a computerized device, the system comprising: at least one bio-potential sensor; at least one motion sensor; at least one haptic feedback actuator capable of creating haptic feedback corresponding to signals from the computerized device; a memory module, having a database with known records representing different gestures and a gesture prediction model; a signal processor, capable of identifying signal parameters from the sensors as known gestures; and a communication controller capable of transmitting information from the signal processor to the computerized device, wherein the at least one bio-potential sensor and the at least one feedback actuator are in direct contact with the skin of the user, wherein identified signals from the signal processor are transmitted to the computerized device, and wherein the at least one haptic feedback actuator is configured to allow reading text from the computerized device.