Wearable EEG Sensor Layout for Comfortable VR Brain-State Feedback
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Solution Overview
Problem
Existing wearable devices lack efficient and comfortable methods for capturing and interpreting bio-signals, particularly brainwave patterns, for enhanced user interaction and control in mediated reality environments.
Innovation Solution
A wearable computing device equipped with bio-signal sensors, including EEG sensors, galvanometer sensors, and other sensors, that communicate with a computing device to analyze brainwave patterns and provide feedback for improved user interaction, using a system that includes cloud-based processing for enhanced accuracy and adaptability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If electrophysiological sensors are integrated into wearable computing devices, then health monitoring capability is improved, but device complexity increases
Solution Approach 1:
The patent combines electrophysiological sensors (ECG, EEG, EMG), motion sensors, and computing components into a single integrated wearable device. The sensor array includes multiple electrode types (Ag/AgCl, carbon, gold) integrated with signal processing circuits and wireless communication modules, creating a unified health monitoring system that captures cardiac, neural, and muscular activity simultaneously.
Solution Approach 2:
The wearable device performs multiple health monitoring functions including cardiac rhythm analysis, neural activity detection, muscle function assessment, and fall detection. The same device platform supports various sensor types and measurement modes, allowing it to adapt to different health monitoring needs without requiring separate specialized devices.
2Measurement precision
If multiple sensor types are integrated into the wearable device, then measurement capability is improved, but manufacturing complexity increases
Solution Approach 1:
The device divides the sensor system into distinct functional modules: ECG electrodes with preamplifiers, EEG electrodes with bandpass filters, EMG sensors with amplification circuits, and motion sensors. Each module can be manufactured and tested independently before final assembly, reducing overall manufacturing complexity while maintaining comprehensive measurement capability.
Solution Approach 2:
Different electrode materials and sensor configurations are applied to specific body contact points based on their optimal performance characteristics. Ag/AgCl electrodes are used for ECG where stable electrical contact is needed, while other electrode types are positioned for EEG and EMG measurements. This localized optimization allows each sensor to perform its specific measurement function with high precision.
3Loss of information
If the wearable device monitors multiple physiological parameters, then health insight is improved, but power consumption increases
Solution Approach 1:
The device employs periodic sampling of physiological signals at optimized rates for each parameter type. ECG is sampled at higher frequencies during detected cardiac events, while baseline monitoring uses lower sampling rates. Motion sensors activate periodically to detect falls or significant activity changes, reducing continuous power consumption while maintaining comprehensive health monitoring capability.
Solution Approach 2:
The system continuously analyzes incoming sensor data and adjusts its monitoring strategy based on detected patterns. When abnormal cardiac rhythms or fall events are detected, the device increases sampling intensity and activates additional sensors. During normal conditions, it reduces power consumption by lowering sampling rates and putting non-essential components into sleep mode, thereby optimizing the balance between health insight and power usage.
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 precise user interaction and control through brainwave analysis, providing real-time feedback and adaptability, enhancing user experience in mediated reality environments.
Implementation Method 1
Wearable computing devices may include electrophysiological sensors, such as electrocardiogram (ECG) sensors, electroencephalogram (EEG) sensors, and electromyogram (EMG) sensors
Data Source
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AI summary
A wearable computing device with bio-signal sensors and a feedback module provides an interactive mediated reality ("VR") environment for a user. The bio-signal sensors receive bio- signal data (for example, brainwaves) from the user and include bio-signal sensors embedded in a display isolator, having a deformable surface, and having an electrode extendable to contact the user's skin. The wearable computing device further includes a processor to: present content in the VR environment via the feedback module; receive bio-signal data of the user from the bio-signal sensor; process the bio-signal data to determine user states of the user, including brain states, using a user profile; modify a parameter of the content in the VR environment in response to the user states of the user. The user receives feedback indicating the modification of the content via the feedback module.