Biological Sensor Differential Measurement System
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Solution Overview
Problem
Current biological sensors lack efficient methods for comparative measurement and adverse condition detection, particularly in monitoring multiple body parts and managing sensor data effectively, which hinders timely and accurate health monitoring and intervention.
Innovation Solution
A system comprising biological sensors that can be placed on various body parts, a processor, and a memory to receive and compare sensor data, detecting adverse biological conditions by generating differential measurements and exceeding thresholds, with features for decommissioning and data management to prevent misuse or overuse.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If biological sensors are used to monitor multiple body parts, then comprehensive health monitoring is improved, but data management complexity and risk of sensor misuse increase
Solution Approach 1:
The system segments sensor management by implementing decommissioning procedures that divide sensor lifecycle into distinct phases (active, deprecated, removed). This segmentation allows comprehensive monitoring across multiple body parts while managing data complexity through structured sensor state transitions and dedicated management routines.
Solution Approach 2:
The system employs feedback mechanisms through threshold-based detection that compares sensor data against predetermined limits. When adverse conditions are detected, the system provides feedback by triggering alerts or interventions, enabling effective monitoring while reducing management complexity through automated decision-making rules.
2Measurement precision
If sensor data is continuously monitored and compared, then detection accuracy of adverse conditions is improved, but processing time and computational resources increase
Solution Approach 1:
The system performs preliminary actions by establishing predetermined thresholds and comparison criteria before actual monitoring begins. This preconfiguration enables accurate detection of adverse conditions through simple threshold comparisons rather than complex real-time analysis, improving detection accuracy while minimizing processing time.
Solution Approach 2:
The system applies partial action by monitoring only critical parameters that exceed predetermined thresholds rather than analyzing all sensor data continuously. This selective approach maintains high detection accuracy for adverse conditions while reducing overall processing time and computational resource requirements.
3Reliability
If sensor decommissioning procedures are implemented, then sensor misuse prevention is improved, but system operational complexity increases
Solution Approach 1:
The system implements self-service through automated decommissioning procedures that manage sensor lifecycle without requiring complex manual intervention. Sensors are automatically deprecated or removed based on predefined criteria and usage patterns, preventing misuse while maintaining simple operational procedures through self-managing sensor states.
Data Source
AI summary
Aspects of the subject disclosure may include, for example, a system or biological sensor configured to detect an adverse biological condition from a comparative measurement from two or more body parts. Other embodiments are disclosed.