EMG Sensor Neuromuscular Signal Prediction for Low Latency Control
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Solution Overview
Problem
Conventional techniques for controlling devices rely on waiting for user actions to be completed, leading to delays in response times, especially in applications requiring fast reactions, such as gaming or virtual reality interactions.
Innovation Solution
The use of EMG sensors to record neuromuscular signals and analyze them with a trained statistical model to predict the onset of motor tasks, allowing for early detection and control of device operations with short latency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If conventional techniques wait for user actions to be completed before controlling devices, then device control reliability is maintained, but response time increases and productivity decreases
Solution Approach 1:
The system performs preliminary detection of neuromuscular signals to predict user intent before the motor task is executed. EMG sensors detect electrical activity in muscles, and a statistical model analyzes these signals to predict the onset of motor tasks, enabling device control to begin before the user actually completes the action, thus reducing response time while maintaining reliability through predictive accuracy
2Productivity
If EMG sensors are used to predict motor task onset, then response time is reduced and productivity is improved, but device complexity increases
Solution Approach 1:
The system replaces traditional mechanical control interfaces (buttons, switches, joysticks) with a physiological sensing system. EMG sensors detect electrical signals from muscles, and a statistical model processes these signals to predict motor task onset, substituting the mechanical interaction paradigm with a physiological one that enables faster, more intuitive control without requiring physical contact with control devices
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
Enables improved control of devices with reduced latency, enhancing performance in applications that require swift reactions by predicting user intentions before they are executed.
Implementation Method 1
Electromyography (EMG) sensors placed on the surface of the human body record electrical activity produced by skeletal muscle cells upon their activation
Data Source
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AI summary
Methods and system for predicting the onset of a motor action using neuromuscular signals. The system comprises a plurality of sensors configured to continuously record a plurality of neuromuscular signals from a user and at least one computer processor programmed to provide as input to a trained statistical model, the plurality of neuromuscular signals or information based on the plurality of neuromuscular signals, predict, based on an output of the trained statistical model, whether an onset of a motor action will occur within a threshold amount of time; and send a control signal to at least one device based, at least in part, on the output probability, wherein the control signal is sent to the at least one device prior to completion of the motor action by the user.