Optical Sensor Venous Pulsation Filtering for Biometric Accuracy
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Solution Overview
Problem
Pulse oximetry measurements are compromised by venous pulsation, which can lead to reduced accuracy in biometric data collection due to the inclusion of low-oxygen saturation venous blood phases offsetting arterial blood oxygen saturation values.
Innovation Solution
An electronic device equipped with optical sensors that emit light of different wavelengths (e.g., infrared, red, and green) to detect and compare optical signals, identifying venous pulsation by analyzing similarity information and determining if a section is abnormal to prevent biometric data collection, ensuring accurate arterial pulsation-based measurements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If pulse oximetry measurements are performed using optical sensors to detect blood oxygen saturation, then biometric information can be obtained for health monitoring, but measurement accuracy is reduced due to venous pulsation interfering with arterial blood detection
Solution Approach 1:
The patent segments the optical signal into multiple wavelength components (e.g., red and infrared wavelengths) and processes each wavelength separately to extract arterial pulsation characteristics. By dividing the measurement into distinct wavelength channels, the system can isolate arterial blood signals from venous pulsation interference, thereby improving measurement accuracy while accounting for the harmful venous pulsation effect.
Solution Approach 2:
The patent introduces an intermediary processing step that uses similarity comparison between different wavelength signals to identify and filter venous pulsation. By comparing the temporal patterns and similarity of optical signals across multiple wavelengths, the system acts as an intermediary filter to distinguish arterial from venous components, resolving the measurement accuracy problem caused by venous interference.
2Measurement precision
If multiple optical signals with different wavelengths are used to improve measurement accuracy by distinguishing arterial and venous pulsations, then biometric information precision increases, but device complexity increases due to additional signal processing requirements
Solution Approach 1:
The patent implements a self-service approach where the system automatically performs similarity comparison and venous pulsation identification using the optical signals it already collects. The device uses its own multi-wavelength optical signals to self-diagnose and filter venous interference without requiring external intervention or complex additional hardware, thereby improving accuracy while limiting the increase in processing complexity to what is already inherent in multi-wavelength pulse oximetry.
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
Enhances the accuracy of biometric information, particularly blood oxygen saturation, by distinguishing between arterial and venous pulsations, thereby maintaining high measurement precision.
Implementation Method 1
The at least one processor may control the at least one optical sensor to receive light reflected from the user's body part
Implementation Method 2
obtain a plurality of optical signals having different wavelengths from the received light in the specified section
Data Source
AI summary
An electronic device is provided. The electronic device includes at least one optical sensor, a memory, and at least one processor electrically connected to the at least one optical sensor and the memory. The at least one processor may radiate light onto a user's body part in a specified section. The at least one processor may control the at least one optical sensor to receive light reflected from the user's body part. The at least one processor may obtain a plurality of optical signals having different wavelengths from the received light in the specified section. The at least one processor may obtain similarity information by comparing similarities between at least two specified optical signals among the plurality of optical signals. The at least one processor may identify the specified section as an abnormal section.