Ear Canal Accelerometer Cardiopulmonary Signal Extraction
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Solution Overview
Problem
Current systems for capturing cardiopulmonary signals are susceptible to environmental noise and low-frequency motion artifacts, making it difficult to simultaneously capture mechanical and acoustic signals with high fidelity.
Innovation Solution
The use of high-speed accelerometers in earbuds or headphones, which combine accelerometer and contact microphone characteristics, allows for the capture of mechano-acoustic signals in multiple frequency bands, effectively extracting cardiac features like ballistocardiogram (BCG) and phonocardiogram (PCG) signals, even in noisy environments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If current systems are used to capture cardiopulmonary signals, then environmental noise and low-frequency motion artifacts are captured, but measurement precision and signal fidelity deteriorate
Solution Approach 1:
The patent segments the cardiopulmonary signals into distinct frequency bands using multiple bandpass filters (e.g., 0.5-20 Hz for mechanical signals, 20-200 Hz for acoustic signals). This segmentation allows selective processing and analysis of different signal components, improving measurement precision by isolating target signals from noise and artifacts in specific frequency ranges.
Solution Approach 2:
The patent introduces high-speed accelerometer data as an intermediary element that captures both mechanical vibrations and acoustic signals simultaneously. This intermediary sensor provides a rich signal source that contains multiple frequency components, enabling the system to extract and separate different signal types through filtering and processing, thereby improving overall signal fidelity.
2Adaptability or versatility
If multiple signal types are captured simultaneously, then comprehensive cardiopulmonary data is obtained, but device complexity increases
Solution Approach 1:
The patent implements a universal signal processing framework that handles multiple signal types (mechanical vibrations, acoustic signals, respiratory movements) through a single integrated system. The high-speed accelerometer serves as a multi-functional sensor that captures diverse physiological signals, and the processing system applies unified filtering and analysis methods across different signal types, achieving versatility without proportionally increasing device complexity.
Solution Approach 2:
The patent changes processing parameters (filter frequencies, analysis windows, detection thresholds) dynamically based on the detected signal type and physiological state. For example, different bandpass filters are applied depending on whether mechanical or acoustic signals are being analyzed, and detection algorithms adjust parameters based on signal characteristics. This parameter adaptation enables comprehensive signal capture while maintaining efficient processing.
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
This approach enables robust measurements of cardiac and respiratory functions, providing accurate identification of cardiac activities without user intervention, across various physical activity conditions, by filtering and processing signals to determine cardiac and respiratory rates.
Implementation Method 1
receiving an accelerometer signal from an accelerometer in a headphone configured to be mounted in a user's ear canal
Implementation Method 2
filtering the accelerometer signal using a bandpass filter to extract the cardiac signal
Data Source
AI summary
A method is provided that includes receiving an accelerometer signal from an accelerometer in a headphone configured to be mounted in a user's ear canal and filtering the accelerometer signal to extract a cardiac signal. The method further includes detecting a plurality of peaks in the cardiac signal and determining a cardiac rate of the user based on the detected plurality of peaks.