Sensor Data Quality Assessment and Synthesis for Bio-Signal Accuracy
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Solution Overview
Problem
Existing electronic devices struggle to improve the quality of sensor data, particularly in determining bio-signals, due to issues like noise, artifacts, and missing data.
Innovation Solution
An apparatus and method that determine the quality of a data portion of an input sensor data stream based on a first data type, and decide between generating filtered or synthesized data streams of a second data type, where synthesis is based on the first data type, to enhance or replace the original data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If sensor data is used directly without processing, then data acquisition is simple and fast, but the quality and accuracy of bio-signal measurements deteriorate due to noise, artifacts, and missing data
Solution Approach 1:
The system performs preliminary quality assessment of sensor data portions before final bio-signal extraction. By evaluating data quality in advance and identifying suitable data portions, the system prepares clean input data for downstream processing, thereby improving measurement accuracy without adding complex real-time processing requirements during critical measurement phases.
Solution Approach 2:
The sensor data stream is divided into multiple data portions that are individually assessed for quality. This segmentation allows the system to identify and select high-quality segments while discarding or replacing low-quality portions, thereby improving overall measurement accuracy without requiring the entire data stream to be perfectly clean.
2Reliability
If sensor data quality is poor with noise and artifacts, then data collection is straightforward, but the reliability of determined bio-signals deteriorates
Solution Approach 1:
The system performs preliminary quality assessment of sensor data portions before final bio-signal extraction. By evaluating data quality in advance and identifying suitable data portions, the system prepares clean input data for downstream processing, thereby improving measurement accuracy without adding complex real-time processing requirements during critical measurement phases.
Solution Approach 2:
The system implements a feedback mechanism where the quality assessment results directly influence the selection and processing of data portions. High-quality portions are selected for bio-signal determination while low-quality portions are discarded or replaced, creating a closed-loop system that continuously improves reliability based on quality feedback.
3Measurement precision
If filtered or synthesized data streams are generated to improve data quality, then measurement accuracy improves, but computational complexity and processing time increase
Solution Approach 1:
The system applies filtering or synthesis operations selectively only to data portions that are identified as low-quality, rather than processing the entire data stream. This partial action approach maintains measurement precision for critical portions while minimizing unnecessary computational overhead and processing time for already high-quality data.
Solution Approach 2:
The system performs preliminary quality assessment of sensor data portions before final bio-signal extraction. By evaluating data quality in advance and identifying suitable data portions, the system prepares clean input data for downstream processing, thereby improving measurement accuracy without adding complex real-time processing requirements during critical measurement phases.
Data Source
AI summary
A method is provided that includes determining a quality of a data portion of an input sensor data stream based, at least in part, on data of a first data type and determining between, at least, generation of two or more streams of a second, different data type including at least one synthesised data stream of the second data type. Determining between generation of two or more streams of a second, different data type is based, at least in part, on the determined quality. The synthesis is based, at least in part, on the data of the first data type. The method further includes causing generation of at least one stream of the second, different data type based, at least in part, on the determination between generation of two or more streams of the second, different data type.