Movement Sensor Impairment Detection via Reference Data Comparison
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Solution Overview
Problem
Current methods for detecting impairment indicators, such as cognitive, physical, or sensory impairments, are often invasive, costly, and inefficient, lacking continuous and non-intrusive monitoring capabilities, which can lead to safety risks and ineffective disease diagnosis.
Innovation Solution
A method utilizing a movement sensor attached to a person to measure and compare numerical descriptors of movement signals over time windows, with reference data collected during training or normal activities, to identify impairment indicators, and optionally incorporating location information to detect mental, visual, or physical impairments, triggering alarms when necessary.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If traditional impairment detection methods are used, then detection accuracy may be adequate, but the methods are invasive and costly
Solution Approach 1:
The patent replaces traditional mechanical or chemical impairment detection methods (such as breathalyzers, blood tests, or physical examinations) with an electronic movement sensor system that detects impairment through analysis of movement patterns. The movement sensor captures signals related to body movement, and a processor analyzes these signals to identify impairment indicators, thereby eliminating the need for invasive procedures while maintaining detection capability
Solution Approach 2:
The patent introduces movement signals as an intermediary medium to detect impairment. Instead of directly measuring impairment markers (such as alcohol concentration or cognitive function), the system measures movement patterns that are indirectly affected by impairment. The movement sensor captures these intermediary signals, which then serve as the basis for impairment detection through pattern recognition and comparison against reference data
2Reliability
If continuous monitoring is implemented, then safety risks are reduced, but device complexity increases
Solution Approach 1:
The patent designs the movement sensor system to perform multiple functions within a single integrated device. The same movement sensor that captures movement signals for impairment detection also provides data for activity recognition, location tracking, and various other monitoring functions. This multi-functionality reduces the need for separate specialized devices, thereby limiting the increase in overall system complexity while enabling continuous safety monitoring
Solution Approach 2:
The system incorporates automatic reference data generation and comparison capabilities that operate without continuous human intervention. The processor automatically compares movement signals against stored reference data, identifies impairment indicators, and triggers appropriate responses. This self-service operation reduces the complexity of manual monitoring procedures and enables reliable continuous monitoring with minimal human oversight
3Productivity
If traditional impairment testing is performed, then diagnostic accuracy is achieved, but time and cost resources are consumed
Solution Approach 1:
The patent implements continuous movement signal capture and analysis, eliminating the discrete, intermittent nature of traditional impairment testing. The movement sensor continuously monitors movement patterns, and the processor continuously analyzes signals for impairment indicators. This continuous operation provides real-time detection capability, dramatically improving detection efficiency and eliminating the time loss associated with scheduling and administering periodic tests
Solution Approach 2:
The system pre-stores reference data representing normal movement patterns for comparison against current signals. By having reference data readily available before testing occurs, the system can immediately compare and identify deviations indicating impairment without requiring time-consuming baseline establishment during each testing event. This preliminary preparation of reference data accelerates the detection process
Data Source
AI summary
A method for monitoring impairment indicators, the method includes measuring, with a movement sensor attached to the person, a first signal related to movement of a person during a first time window and electronically storing the at least one numerical descriptor derived from the first signal as reference data for the person. The method further includes measuring, with the movement sensor attached to the person, a second signal related to movement of the person during a second time window and comparing at least one numerical descriptor derived from the second signal to the reference data as a factor to identify an impairment indicator. The present disclosure also includes a device for monitoring impairment indicators.