EMG-Sensing Game Controller Configurations for Reduced Control Latency
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Solution Overview
Problem
Existing gaming systems experience noticeable latency in user controls and game data processing, especially in networked and streaming games, limiting the immersion and responsiveness of virtual and augmented reality environments.
Innovation Solution
Implementing electromyography (EMG) sensing to detect user muscle activity through wearable sensors, allowing for the early detection of control signals before traditional button presses, and using machine learning to identify and communicate these signals to reduce latency in game control systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If traditional button presses and control inputs are used, then the gaming system operates with standard processing latency, but the user experience suffers from noticeable delay and reduced responsiveness
Solution Approach 1:
The EMG sensors detect muscle electrical activity before the user actually presses the button or moves the controller, allowing the system to prepare for the input in advance. This preliminary detection of physiological signals precedes the mechanical action, effectively reducing perceived latency by processing the control intent before the traditional input occurs.
Solution Approach 2:
The patent replaces or supplements the mechanical button press detection system with an electrical/physiological detection system using EMG sensors. Instead of waiting for mechanical contact or movement, the system detects electrical signals from muscle activity, substituting the mechanical sensing approach with an electrical field-based sensing approach that provides earlier detection.
2Speed
If EMG sensors are integrated into the game controller, then control signals can be detected earlier to reduce latency, but the device complexity and processing requirements increase
Solution Approach 1:
The EMG sensing system is merged with the existing game controller structure. The sensors, processing circuitry, and traditional controls are integrated into a single unified device, allowing both functions to operate together. This merging enables early signal detection while maintaining the familiar controller form factor and user interface.
Solution Approach 2:
The game controller is designed to perform multiple functions: traditional mechanical input detection and EMG-based physiological signal detection. This multi-functionality allows the single device to provide both conventional control options and advanced early-detection capabilities, making the system versatile and adaptable to different user needs and game types.
3Measurement precision
If machine learning operations are used to characterize EMG signals, then control accuracy is improved, but processing time and computational requirements increase
Solution Approach 1:
Machine learning models are trained in advance during a calibration phase before actual gameplay. The system learns and stores the user's specific EMG signal patterns, muscle activation characteristics, and control mappings beforehand. During gameplay, the pre-trained model quickly classifies new EMG signals without requiring extensive real-time computation, thus maintaining high accuracy while minimizing processing time during critical gameplay moments.
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
Reduces latency in gaming systems by providing control signals ahead of traditional input detection, enhancing responsiveness and immersion in virtual and augmented reality gaming.
Implementation Method 1
receiving, by a device, output of at least one electromyography (EMG) sensor for a user of an electronic game, the output including at least one EMG signal for the user
Data Source
AI summary
Systems, processes and device configurations are provided for electronic game control with electromyography (EMG) sensing. Embodiments include processes for receiving EMG sensor output and detection of EMG user controls, such as user electrical activity in connection with movement of fingers and hands, and output of user EMG control signals for control of electronic game content. EMG signals may be detected by a one or more sensors on a wrist strap to detect user signals and secure user controllers. Embodiments include game controller configurations and systems for electronic game content presentation. Game controller configurations may include at least one of an interface for receiving EMG data and for powering EMG sensors. System configurations may include processing EMG signals and user activation signals of a game controller to reduce latency of generated game content. Machine learning models are described for training and use to identify user control signals from the EMG signal.