EMG-Guided Input Element Prediction for Low-Latency Controls
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Solution Overview
Problem
Existing input devices introduce noticeable delays in providing input to computing devices, which can impact performance in critical applications such as automotive control, motorsports, and assisted robotic surgery, due to inherent delays in user interaction, signal transmission, and processing.
Innovation Solution
The use of muscle activity sensors, such as electromyography (EMG), in conjunction with proximity sensors, to predict user input before physical interaction, reducing delays by detecting muscle signals associated with intended input elements and generating signals based on these predictions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If traditional physical input devices are used, then device complexity is reduced, but input delay increases
Solution Approach 1:
The system detects muscle activity signals before the user physically interacts with the input device, allowing the system to predict and prepare for the intended input in advance. This preliminary detection of muscle signals enables the system to reduce input delay by acting before the physical interaction occurs.
Solution Approach 2:
The patent replaces the traditional mechanical interaction system with a bioelectrical signal detection system. Instead of waiting for physical button presses or mouse movements, the system uses muscle activity sensors to detect electrical signals from muscle contractions, substituting the mechanical input method with a physiological signal-based method.
2Loss of time
If muscle activity sensors are added to predict input, then input delay is reduced, but device complexity increases
Solution Approach 1:
The system introduces muscle activity sensors as an intermediary between the user's intent and the physical interaction with the input device. These sensors detect muscle signals that indicate the user's intention to interact, serving as a mediator that provides advance notice of the intended input without requiring direct physical contact with the device.
Solution Approach 2:
The system implements feedback by continuously monitoring muscle activity signals and using this information to predict upcoming inputs. The feedback loop detects muscle contractions, processes the signals to determine intended interactions, and triggers the corresponding input actions, creating a closed-loop system that reduces delay through continuous physiological monitoring.
3Measurement precision
If multiple sensors are used for prediction, then prediction accuracy is improved, but device complexity increases
Solution Approach 1:
The patent combines multiple sensor types (muscle activity sensors and proximity sensors) into a unified input detection system. By merging the data from these different sensors, the system achieves more accurate prediction of user intent, as the combination of muscle activity detection and proximity information provides complementary information about the user's intended interaction.
Solution Approach 2:
The system creates a multi-functional input device that can detect both muscle activity signals and proximity information, allowing a single device to perform multiple detection functions. This universal approach enables the device to use different sensor modalities depending on the situation, improving prediction accuracy while consolidating functionality into one integrated system.
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 significantly reduces input delays by predicting user interactions up to 70 ms earlier than traditional methods, enhancing responsiveness and efficiency in input devices.
Implementation Method 1
receiving, via a muscle activity sensor associated with an input device, a first signal
Implementation Method 2
a second signal is received via a proximity sensor associated with the input device
Data Source
AI summary
Systems and methods are provided for receiving input via an input device. A first signal is received via a muscle activity sensor. It is determined that the first signal corresponds to a movement of a user digit that does not correspond to a first interaction with an input element of the input device. A digit movement direction is identified, and a prediction of a second interaction with an input element is generated. A first confidence level associated with the prediction is below a threshold, and a second signal is received via a proximity sensor. A velocity of the user digit is determined, and a prediction of the second interaction with a first input element is made. It is identified that a second confidence level associated with the prediction is above the threshold, and a third signal associated with the first input element of the input device is generated for output.