Morphology-Based Motion Detection for Implantable PPG Sensors
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Solution Overview
Problem
Implantable sensors, such as photoplethysmography (PPG) sensors, are highly sensitive to motion-induced noise, which can corrupt signals used for monitoring and adjusting parameters like heart rate and oxygen saturation, leading to unreliable data and increased system complexity when separate motion sensors are used.
Innovation Solution
The method estimates the level of motion-induced noise in implantable sensor signals by binning sample data based on magnitude, calculating ratios or fitting lines to distributions, and comparing these to thresholds to classify noise levels, allowing for reliable determination of signal reliability and potential adjustments in sensor performance over time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a separate motion sensor (accelerometer) is used to detect motion, then motion detection capability is improved, but device complexity and cost increase
Solution Approach 1:
The patent applies multi-functionality by enabling the PPG sensor to serve dual purposes: its primary function of monitoring physiological parameters and a secondary function of detecting motion artifacts. By analyzing the PPG signal characteristics (amplitude, morphology, frequency content) to infer motion presence, the system eliminates the need for a separate accelerometer while maintaining motion detection capability. This resolves the contradiction by making one component perform multiple functions.
Solution Approach 2:
The patent uses the PPG signal itself as an intermediary to detect motion. Instead of directly measuring motion with a separate sensor, the system analyzes changes in the PPG signal characteristics caused by motion artifacts. The PPG signal acts as a mediator that carries information about both physiological state and motion presence, allowing motion detection without additional hardware.
2Reliability
If a separate motion sensor is added to detect motion artifacts, then signal reliability is improved, but manufacturing cost increases
Solution Approach 1:
The existing PPG sensor is made multi-functional by adding signal processing capabilities that enable it to detect motion artifacts. The same hardware component serves both physiological monitoring and motion detection functions, eliminating the need for additional sensors and reducing manufacturing costs while maintaining signal reliability.
Solution Approach 2:
The PPG sensor system performs self-diagnosis by analyzing its own output signal characteristics to detect the presence of motion artifacts. The system uses its own signal as the basis for detecting contamination, eliminating the need for external motion sensors and reducing overall system cost while improving signal reliability through self-monitoring.
3Device complexity
If motion induced noise is present in PPG signals, then measurement accuracy deteriorates, but using the signal anyway maintains system simplicity
Solution Approach 1:
The patent implements feedback by continuously analyzing PPG signal characteristics and using this information to determine whether the signal is suitable for accurate measurement. The system monitors signal quality metrics (amplitude consistency, morphology matching, frequency analysis) and uses this feedback to decide whether to trust the PPG-derived parameters, thereby maintaining measurement precision without compromising system simplicity.
Solution Approach 2:
The patent applies dynamics by making the system's behavior adaptive based on real-time signal quality assessment. When motion artifacts are detected through signal characteristic analysis, the system dynamically adjusts its operation by discarding or flagging affected measurements. This dynamic response maintains measurement precision under varying conditions while keeping the system simple by using only the existing PPG sensor.
Data Source
AI summary
Provided herein are implantable systems, and methods for use therewith, for estimating a level of noise in a signal produced by an implantable sensor that is sensitive to motion induced noise. Sample data is obtained that is representative of a signal produced by the implantable sensor that is sensitive to motion induced noise. Such a sensor signal has a corresponding morphology. The morphology of a portion of the sensor signal is compared to a template, and a level of motion induced noise in the sensor signal is estimated, based on results of the morphology comparison.