Wrist-Worn Biopotential Sensor for Gesture Control
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Solution Overview
Problem
Current user interface technologies rely on physical devices for input, which can be cumbersome and inefficient, especially in applications requiring rapid and precise interactions, such as gaming and e-sports, where reaction time and accuracy are critical.
Innovation Solution
A user interface system that detects nerve and tissue electrical signals at the wrist to interpret intended muscle contractions, allowing for direct control of responsive devices without physical device actuation, enabling faster and more accurate input recognition.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If physical devices are used for input, then control is achieved, but reaction time is delayed and accuracy is reduced
Solution Approach 1:
The system performs preliminary detection of muscle contraction signals before the physical actuation occurs. By monitoring electrical signals from muscles, the system predicts intended actions 20-150 ms before the user actually moves or presses physical controls, enabling advance preparation and faster response execution.
Solution Approach 2:
The patent replaces traditional mechanical input devices (keyboards, mice, buttons) with a biological signal detection system. Electrical signals from muscle contractions are detected and processed to generate control inputs, substituting the mechanical actuation path with a direct neuro-muscular signal pathway that eliminates mechanical response delays.
2Measurement precision
If physical devices are used for input, then control is achieved, but accuracy is reduced
Solution Approach 1:
The system introduces an intermediary layer between the user's intent and the control system. Muscle electrical signals serve as an intermediary that objectively represents the user's intended action, providing a more precise and reliable input signal compared to mechanical device actuation, which can suffer from imprecision and variability.
3Productivity
If traditional input methods are used, then control is achieved, but performance in time-sensitive tasks is limited
Solution Approach 1:
The system performs preliminary detection of muscle contraction signals before the physical actuation occurs. By monitoring electrical signals from muscles, the system predicts intended actions 20-150 ms before the user actually moves or presses physical controls, enabling advance preparation and faster response execution.
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
This approach reduces reaction time and improves accuracy by predicting intended actions 20-150 ms earlier than traditional methods, enhancing performance in time-sensitive tasks and providing intuitive control for a wider range of users.
Implementation Method 1
a sensor to detect nerve or other tissue electrical signals associated with an intended contraction of a muscle
Data Source
AI summary
System and methods for gesture-based control are described. In some embodiments, a system may include a wearable device configured to be worn at a person's wrist. The wearable device may include a biopotential sensor and a wrist motion sensor. The system may be configured to determine that the person performed an initial gesture based on biopotentials detected by the biopotential sensor. The system may be configured to determine that the person performed a supplemental gesture based on at least the wrist motion data obtained by the wrist motion sensor. The system may be further configured to generate a command to be executed by a responsive device based on the combination of at least the initial gesture and the supplemental gesture.