Wearable Sensor Confidence Indicator for Motion Artifact Noise
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Solution Overview
Problem
Physiological measurements in portable applications are plagued by noise introduced by motion artifacts, which degrade the accuracy of data collected from wearable sensors.
Innovation Solution
A wearable sensor platform that captures both physiological and artifact data, using a confidence indicator engine to assess the reliability of the physiological data signal by processing noise and artifact data, and provides this information to the user, allowing for improved data interpretation and filtering.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If motion artifacts are present in portable physiological measurements, then the portability and mobility of the sensor platform is improved, but the measurement precision and reliability of the physiological data deteriorates
Solution Approach 1:
The patent segments the physiological measurement signal from the noise/artifact signal by processing them separately through different algorithms. The confidence indicator engine divides the overall signal analysis into distinct components: physiological signal processing and artifact/noise processing, allowing each to be handled with specialized techniques that preserve measurement accuracy while maintaining portability.
Solution Approach 2:
The confidence indicator serves as an intermediary metric that bridges the gap between raw physiological measurements and artifact-contaminated signals. By introducing this intermediate confidence assessment layer, the system can evaluate data quality without requiring complex real-time filtering, thus maintaining portability while improving measurement precision through informed data selection and processing.
2Speed
If motion artifacts are present in portable physiological measurements, then the mobility and real-time monitoring capability is improved, but the reliability of the physiological data deteriorates
Solution Approach 1:
The system performs preliminary confidence assessment on physiological measurements before they are fully processed or stored. By calculating confidence indicators in advance during data acquisition, the system prepares quality metrics that can quickly guide subsequent processing decisions, maintaining real-time monitoring speed while ensuring data reliability through pre-evaluated confidence levels.
Solution Approach 2:
The confidence indicator provides continuous feedback about data quality to the processing system. This feedback mechanism allows real-time monitoring to adapt to changing signal conditions by adjusting processing parameters or data selection based on confidence levels, thereby maintaining both speed and reliability in mobile applications.
3Quantity of substance
If noise data is included in physiological measurements, then the completeness of the raw data is improved, but the measurement precision deteriorates
Solution Approach 1:
The patent segments noise data and physiological data into separate processing streams. By maintaining complete raw data (including noise) for completeness while processing them through separate algorithms that identify and isolate physiological signals, the system preserves data completeness for analysis purposes while achieving measurement precision through targeted signal extraction and confidence-based filtering.
Data Source
AI summary
Embodiments include a method and system for providing data to a user of a wearable sensor platform. The method may be performed by a least one software component executing on at least one processor. The method includes capturing data for the user using at least one sensor in the wearable sensor platform. The data includes physiological data and artifact data. The physiological data includes noise data therein. A confidence indicator for the data is determined based on at least one of the physiological data and the artifact data. A physiological data signal corresponding to the physiological data and the confidence indicator is provided to the user on the wearable device platform.