Physiologic Sound Acquisition System With DSP Noise Filtering
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Solution Overview
Problem
Existing systems for digital acquisition and analysis of physiologic sounds are cumbersome, complex, and lack user-friendly interfaces, making them difficult for healthcare professionals with limited technical expertise to operate and modify. Additionally, these systems often fail to effectively filter out ambient noise and signals from other organs, leading to inaccurate diagnoses.
Innovation Solution
A portable, customizable system that utilizes a sensor to convert analog signals into digital data, processed by a digital signal processor (DSP) with Super Harvard Architecture (SHARC), allowing for real-time noise reduction and analysis of physiologic sounds. The system includes a user-friendly interface that enables clinicians to adjust parameters such as sampling rate, filtering, and Fourier Transformation without requiring computer programming knowledge.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing systems for digital acquisition and analysis of physiologic sounds are used, then diagnostic information can be obtained, but the systems are cumbersome and complex making them difficult for healthcare professionals with limited technical expertise to operate and modify
Solution Approach 1:
The system performs automatic noise filtering and signal processing without requiring manual intervention. The DSP automatically identifies and removes ambient noise and signals from other organs, and the system self-adjusts parameters based on the recorded signal characteristics, eliminating the need for technical expertise in operation.
Solution Approach 2:
The patent replaces complex manual mechanical adjustment systems with automated digital signal processing. Instead of requiring clinicians to manually adjust filtering and analysis parameters, the system uses DSP to automatically process signals, substitute manual mechanical operations with automated electronic processing.
2Measurement precision
If existing systems for digital acquisition and analysis of physiologic sounds are used, then some analysis can be performed, but they fail to effectively filter out ambient noise and signals from other organs leading to inaccurate diagnoses
Solution Approach 1:
The system extracts and removes unwanted components from the recorded signal. The DSP identifies and separates ambient noise and signals from other organs from the target physiologic signal, extracting only the relevant diagnostic information while eliminating interfering elements.
Solution Approach 2:
The system converts the harmful effect of ambient noise and overlapping signals into useful information. By analyzing the frequency and temporal characteristics of all recorded sounds, the DSP identifies patterns that help distinguish target signals from interference, turning noise into diagnostic data.
3Adaptability or versatility
If existing systems are used, then signal acquisition can be performed, but the systems lack user-friendly interfaces and require computer programming knowledge for modification
Solution Approach 1:
The system automatically adapts to different diagnostic needs without requiring manual programming. The DSP self-configures based on the selected organ and recording conditions, and the interface automatically adjusts parameters based on user selections, making the system versatile without increasing operational complexity.
4Measurement precision
If manual filtering and analysis methods are used, then some noise reduction can be achieved, but the process is time-consuming and reduces productivity
Solution Approach 1:
The patent replaces manual mechanical filtering and analysis processes with automated digital signal processing. The DSP performs noise filtering, signal separation, and diagnostic analysis automatically and instantaneously, substituting time-consuming manual operations with rapid electronic processing.
Solution Approach 2:
The system performs continuous real-time signal processing and analysis as data is being collected. The DSP continuously filters and analyzes the physiologic signals without interruption, providing ongoing diagnostic information rather than requiring batch processing or manual intervention between measurements.
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 system provides accurate, real-time analysis of physiologic sounds, effectively filtering out ambient noise and signals from other organs, thus enhancing diagnostic accuracy. Its user-friendly interface allows healthcare professionals with limited technical expertise to easily operate and modify the system, improving its practical application in clinical settings.
Implementation Method 1
A sensor for acoustic energy is used to convert the analogue signal into an electrical output, which is then converted to digital data
Data Source
AI summary
In some embodiments, an apparatus for acquiring, processing and transmitting physiological sounds, which may include acoustic sounds from at least one organ in a biological system, may include a sensor for acquiring physiological sounds. Analogue signals representative of the physiological sounds are converted into an electrical output. The electrical output is converted to digital data. A processing unit processes the digital data in a manner selected by a user. A display device displays the digital data and can be customized by a user.