Driver Heartbeat Interval Detection for Fast Abnormality Signs
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Solution Overview
Problem
Existing methods for detecting driver abnormality signs are either too responsive and prone to noise or too reliable but slow, failing to achieve both high responsiveness and reliability simultaneously, especially in short-time scale scenarios.
Innovation Solution
A driver abnormality sign detection method that estimates heartbeat intervals, standardizes the data, and calculates the probability of the standardized interval falling within a predetermined range centered at zero, allowing for quick detection of abnormalities using a processor and a heartbeat detection device, such as a driver camera, while maintaining high reliability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If heart rate variability analysis is performed using frequency region indices (SDNN, HF, LF, LF/HF), then abnormality detection reliability is improved, but the time required for analysis increases
Solution Approach 1:
The patent extracts only the essential characteristics needed for abnormality detection from the complex heart rate variability analysis. Instead of performing full frequency domain analysis (FFT, power spectral density), the invention uses a simplified time-domain approach that captures the key abnormality indicators without requiring extensive computational resources and time.
Solution Approach 2:
The patent changes the analysis parameters from frequency-domain metrics (SDNN, HF, LF, LF/HF ratios) to a simplified time-domain metric that measures the probability of heartbeat intervals falling within a specific range. This parameter transformation enables faster computation while maintaining detection reliability.
2Measurement precision
If non-linear analysis of heart rate variability is performed, then detection precision is improved, but computational complexity increases
Solution Approach 1:
The patent employs a computationally inexpensive method that sacrifices the complexity of non-linear analysis in favor of a simpler, more efficient approach. The invention uses basic statistical probability calculations instead of complex non-linear dynamics analysis, achieving adequate detection precision with minimal computational overhead.
3Reliability
If driving behavior changes are monitored to detect driver abnormality, then detection coverage is improved, but the response time increases due to the need for several minutes of monitoring
Solution Approach 1:
The patent performs preliminary analysis on heart rate data to identify early signs of driver abnormality before actual driving behavior changes occur. By analyzing heart rate variability patterns in real-time, the system can detect abnormalities and issue warnings before the driver's driving behavior deteriorates, enabling preventive action.
Data Source
AI summary
Driver abnormality sign detection method and device are provided that can detect an abnormality sign of a driver while realizing both high responsiveness and high reliability. A driver abnormality sign detection method includes estimating a heartbeat interval of a driver based on heartbeats detected by a driver camera, acquiring time-series data of the heartbeat interval of the driver in a predetermined time period, standardizing the time-series data of the heartbeat interval, calculating a probability PA that the standardized heartbeat interval falls within a predetermined range having zero as a center, in the time-series data of the standardized heartbeat interval CG-BIz, and determining that a sign of an abnormality of the driver is detected in a case where the probability PA is greater than a predetermined abnormality sign threshold value TA.