Acoustic Sensor Compression Module for Respiratory Monitoring
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Solution Overview
Problem
Existing acoustic respiratory monitoring systems face challenges in accurately capturing a wide range of physiological sounds, including both quiet and loud sounds, due to the limited dynamic range of components in the sensor data path, leading to signal saturation and distortion.
Innovation Solution
The implementation of an acoustic sensor with a compression module that modifies the signal output from the sensing element to prevent saturation in subsequent components, such as preamplifiers, and a noise reduction module that processes signals from multiple sensors to improve the signal-to-noise ratio, allowing for a wider dynamic range and accurate detection of various physiological parameters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the dynamic range of components in the sensor data path is increased to capture a wider range of sound intensities, then the ability to detect both quiet and loud physiological sounds is improved, but the complexity of the system increases due to the need for compression and noise reduction modules
Solution Approach 1:
The compression module performs preliminary action by compressing the output signal from the sensing element before it reaches subsequent components with limited dynamic range. This prevents signal saturation in advance, allowing the system to handle both quiet and loud sounds without distortion. The compression is applied proactively rather than correcting saturation after it occurs.
2Adaptability or versatility
If compression is applied to prevent signal saturation in components with limited dynamic range, then the dynamic range capability is improved, but distortion may be introduced into the signal
Solution Approach 1:
The compression module acts as an intermediary between the sensing element and subsequent components with limited dynamic range. It transforms the signal into a form that can be processed without saturation, and the noise reduction module further processes the signal to remove artifacts. This intermediary processing preserves signal fidelity while enabling wider dynamic range handling.
3Measurement precision
If multiple sensors are used to improve the signal-to-noise ratio through noise reduction processing, then the accuracy of physiological parameter detection is improved, but the device complexity and cost increase
Solution Approach 1:
The noise reduction module merges signals from multiple sensors to improve the signal-to-noise ratio. By combining multiple sensor inputs and processing them together, the system achieves better measurement precision for physiological parameters. This merging approach leverages the redundant information from multiple sensors to filter out noise more effectively.
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
The solution enhances the dynamic range of the acoustic respiratory monitoring system, enabling the accurate capture and processing of a broader range of sound intensities, reducing distortion, and improving the detection of physiological parameters, including respiratory rates and heart sounds, while maintaining resolution for quieter sounds.
Implementation Method 1
The acoustic sensor can include an acoustic sensing element, such as a piezoelectric sensing element, configured to generate an output signal in response to acoustic vibrations from a medical patient.
Data Source
AI summary
An acoustic sensor is provided according to certain aspects for non-invasively detecting physiological acoustic vibrations indicative of one or more physiological parameters of a medical patient. The sensor can include an acoustic sensing element configured to generate a first signal in response to acoustic vibrations from a medical patient. The sensor can also include front-end circuitry configured to receive an input signal that is based at least in part on the first signal and to produce an amplified signal in response to the input signal. In some embodiments, the sensor further includes a compression module in communication with the front-end circuitry and configured to compress portions of at least one of the input signal and the amplified signal according to a first compression scheme, the compressed portions corresponding to portions of the first signal having a magnitude greater than a predetermined threshold level.