Wearable Biosignal Detection System with Segmented Sensor Array
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Solution Overview
Problem
Contemporary sensors and data collection systems fail to effectively capture and analyze cognitive, mental, and affective states of individuals, limiting their ability to provide insights similar to physical and digital data, and struggle to efficiently aggregate biosignal data from multiple individuals for analysis.
Innovation Solution
A wearable biosignal detection and measurement system comprising a biosignal sensor subsystem, electronics subsystem, and housing designed to detect bioelectrical signals such as EEG, with pre-processing sensor interfaces and a comfortable, aesthetically pleasing design that maintains contact during daily activities, allowing for the collection and processing of various biosignals including cognitive and affective states.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If contemporary sensors and data collection systems are used, then physical and digital data can be collected, but cognitive, mental, and affective states cannot be captured
Solution Approach 1:
The system segments the sensor array into multiple individual sensors distributed across the head, each detecting specific biosignals (EEG, EOG, EMG, etc.) from different brain regions. This segmentation enables comprehensive capture of cognitive states by measuring electrical activity across multiple locations simultaneously, resolving the limitation of single-point measurement.
Solution Approach 2:
The wearable system integrates multiple sensor types (EEG electrodes, EOG sensors, EMG sensors, respiratory sensors, temperature sensors) into a single multi-functional device. This universal approach allows simultaneous measurement of various biosignals related to cognitive, mental, and affective states, eliminating the need for separate specialized devices.
2Productivity
If biosignal data is collected from multiple individuals, then comprehensive analysis is enabled, but efficient aggregation and location of data is not achieved
Solution Approach 1:
The system merges data collection from multiple individuals into a unified database structure that automatically aggregates biosignal data, demographic information, and contextual data. The centralized processing system combines data from all participants in real-time, enabling efficient multi-subject analysis without manual consolidation.
Solution Approach 2:
The system implements feedback mechanisms where collected biosignal data is immediately processed and made available for analysis. Real-time feedback loops allow the system to adjust sampling rates, filter noise, and prepare data for analysis as it is collected, significantly reducing the time required for data aggregation and preparation.
3Ease of operation
If a wearable design is used, then comfort and aesthetics are improved, but contact maintenance during daily activities becomes challenging
Solution Approach 1:
The system employs dynamic pressure adjustment mechanisms that allow the headband to adapt its contact pressure according to the user's head shape and movement. The flexible materials and adjustable components enable the sensor array to maintain optimal contact with the scalp during various activities while preserving comfort and aesthetics.
Solution Approach 2:
The headband utilizes flexible shells and thin film materials that conform to the contours of the user's head. These flexible components ensure consistent sensor contact with the scalp surface while maintaining a comfortable, aesthetically pleasing wearable design that can accommodate daily activities.
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 the efficient detection and measurement of biosignals, providing valuable insights into cognitive and affective states, and facilitating the aggregation and analysis of data from multiple individuals, enhancing understanding and application in various fields.
Implementation Method 1
detect bioelectrical signals
Data Source
AI summary
A system for detecting bioelectrical signals of a user comprising: a set of sensors configured to detect bioelectrical signals from the user, each sensor in the set of sensors configured to provide non-polarizable contact at the body of the user; an electronics subsystem comprising a power module configured to distribute power to the system and a signal processing module configured to receive signals from the set of sensors; a set of sensor interfaces coupling the set of sensors to the electronics subsystem and configured to facilitate noise isolation within the system; and a housing coupled to the electronics subsystem, wherein the housing facilitates coupling of the system to a head region of the user.