Garment Biometric Sensor Platform for Adaptive Network Control
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Solution Overview
Problem
Current biometric sensing technologies are cumbersome and lack adaptability to varying lifestyle conditions, particularly for athletes and medical patients, limiting their effectiveness in providing real-time data for influencing networked devices.
Innovation Solution
A biometric sensing platform integrated into garments that collects data from sensors such as ECG, bio impedance, and strain gauges, processing this information to send commands to networked devices for adjusting operational characteristics based on the wearer's physical and mental state.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If state of the art sensor arrangements are used, then biometric data can be collected, but the system becomes cumbersome and has limited adaptability to varied lifestyle conditions
Solution Approach 1:
The patent implements a universal sensor platform that can detect multiple types of biometric data (physiological, biomechanical, environmental) using a single integrated system. The sensor arrangement is designed to be lifestyle-agnostic, capable of adapting to various physical and mental states without requiring different sensor configurations, thereby achieving versatility without proportionally increasing complexity
Solution Approach 2:
The system dynamically adjusts its sensing and processing capabilities based on the wearer's varying lifestyle conditions. The computational processing adapts in real-time to differentiate between relevant and irrelevant biometric variations, allowing the same physical sensor arrangement to serve multiple lifestyle contexts effectively
2Reliability
If multiple biometric sensors are integrated into garments, then real-time monitoring capability is improved, but device complexity increases
Solution Approach 1:
The patent combines multiple sensor types (physiological, biomechanical, environmental) into a single integrated sensor platform embedded in the garment. This merging approach achieves comprehensive real-time monitoring capability while managing complexity through unified data processing and a single computational architecture that handles all sensor inputs collectively rather than through separate processing systems
Solution Approach 2:
The sensor platform incorporates onboard computational processing that automatically filters, interprets, and prioritizes biometric data without requiring external processing for basic functions. The system self-adjusts its monitoring focus based on detected lifestyle changes, reducing the need for complex external control systems while maintaining high monitoring reliability
3Adaptability or versatility
If biometric data is continuously monitored, then adaptability to physical and mental states is improved, but data processing complexity increases
Solution Approach 1:
The system continuously monitors all biometric parameters but selectively processes only the relevant subset based on current lifestyle context. Rather than fully processing all data streams equally, the computational system performs partial processing focused on detecting meaningful changes in physical and mental states, filtering out routine variations that do not require adaptive responses
Solution Approach 2:
The system implements continuous feedback loops where processed biometric data informs subsequent monitoring priorities. The computational processing adapts its focus based on feedback from previous detections, dynamically adjusting which biometric parameters require intensive processing versus those that can be monitored at lower complexity levels, thereby managing overall processing complexity while maintaining adaptability
Data Source
AI summary
A method of using a sensor platform of a garment of a wearer in order to interact with a remote networked device using a plurality of sensed biometric data, the method comprising: receiving from the sensors a set of the plurality of biometric data; comparing the set to a data model including a plurality of model data parameters; determining whether said comparing indicates a need for a command to be sent to the remote networked device in order to effect a change in an operational characteristic of the networked device; sending the command to the networked device; receiving a further set of the plurality of biometric data; further comparing the further set to the data model; and determining whether said further comparing indicates a need for a further command to be sent to the remote networked device in order to further effect a change in an operational characteristic of the networked device.