Pulse Wave Sensor Reliability Calculation for Motion Noise
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Solution Overview
Problem
Miniaturized sensors for heart rate and pulse rate variability measurement face challenges in reliability due to user movement, leading to noise in data and reduced accuracy of HRV indices when users are freely moving or not in a resting state.
Innovation Solution
An information processing apparatus and method that calculates a reliability degree of pulsation variability data from pulse wave sensors, allowing for controlled processing to improve measurement state and accuracy, including detection and correction of abnormal values to enhance HRV index calculation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If miniaturized pulse wave sensors are worn by users for constant measurement, then the measurement can be performed in freely moving states, but the measurement reliability deteriorates due to noise from user movement
Solution Approach 1:
The patent implements a feedback mechanism by calculating a reliability degree based on motion state information and using it to control subsequent processing. The system continuously monitors motion state, evaluates reliability, and adjusts processing accordingly, creating a closed-loop system that adapts to varying measurement conditions while maintaining reliability awareness.
Solution Approach 2:
The patent changes the parameter being measured from raw pulsation variability data to a derived reliability degree parameter. By transforming the measurement output into a reliability metric that accounts for motion interference, the system maintains measurement freedom while providing reliability information that can guide further processing or user behavior.
2Productivity
If HRV indices are calculated from pulsation variability data during movement, then continuous monitoring is achieved, but the measurement precision deteriorates due to noise
Solution Approach 1:
The patent performs preliminary evaluation by calculating the reliability degree before final HRV index calculation or usage. This preliminary assessment of measurement quality allows the system to prepare appropriate processing strategies in advance, such as filtering, weighting, or flagging data that may be affected by motion artifacts.
Solution Approach 2:
The reliability degree acts as an intermediary parameter between raw pulsation variability data and final HRV indices. This intermediate metric provides a bridge that allows continuous monitoring while accounting for measurement quality, enabling the system to process data continuously but with awareness of precision limitations.
3Device complexity
If the system processes all pulsation variability data uniformly, then processing simplicity is maintained, but processing accuracy deteriorates due to inclusion of low-reliability data
Solution Approach 1:
The patent introduces dynamic processing control based on the calculated reliability degree. Instead of uniform static processing, the system adapts its processing behavior according to the reliability assessment, creating dynamic processing paths that can adjust complexity based on measurement conditions while maintaining overall system efficiency.
Data Source
AI summary
There is provided an information processing apparatus including a reliability degree calculation section that calculates a reliability degree of pulsation variability data or a body index; and a control unit that controls various kinds of processing on the basis of the calculated reliability degree. The pulsation variability data is acquired from sensing data acquired by a pulse wave sensor worn by a user. The body index is calculated from the pulsation variability data and indicates a physical state of the user.