Bioacoustic Sensor Noise Classification for Attachment State Feedback
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing bioacoustic sensors attached to body surfaces using double-sided surgical tape face challenges in maintaining accurate analytical data due to noise components from varying attachment states, such as poor adhesion and faulty lead wire connections, which current noise reduction techniques fail to adequately address.
Innovation Solution
A bioacoustic processing apparatus that includes a noise extraction section and a noise type classification section to identify and classify noise components based on different attachment states, outputting information to guide users in improving the attachment state, thereby reducing noise contamination in acoustic signals.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Duration of action of stationary object
If adhesive-type bioacoustic sensors are used for continuous monitoring, then duration of action is improved, but noise components from attachment state degradation worsen measurement precision
Solution Approach 1:
The system performs preliminary classification of noise components to identify attachment state issues before they severely degrade measurement quality. By continuously monitoring and classifying noise types (contact noise, handling noise, adhesion noise), the system can alert users to reattach the sensor before analytical accuracy drops below acceptable thresholds.
Solution Approach 2:
The noise type classification section provides continuous feedback about the attachment state by classifying extracted noise components into distinct categories. This feedback mechanism enables users to understand the current attachment quality and take corrective actions (reattachment, position adjustment) to maintain measurement precision throughout the monitoring duration.
2Object-affected harmful factors
If general noise reduction techniques are applied, then some noise components are reduced, but attachment-state-specific noise components cannot be sufficiently mitigated
Solution Approach 1:
The noise extraction and classification system segments noise components into distinct types based on their characteristics and sources. By dividing noise into categories (contact noise during attachment, handling noise during movement, adhesion noise during monitoring), the system can apply targeted processing strategies for each type, achieving better noise reduction than general techniques.
Solution Approach 2:
The noise type classification section applies different processing approaches tailored to each noise type's characteristics. Instead of using a uniform noise reduction method, the system adapts its processing to the specific local conditions represented by each noise category, thereby more effectively preserving signal quality and analytical accuracy.
3Loss of information
If noise components are extracted and classified, then information about attachment state is obtained, but device complexity increases
Solution Approach 1:
The noise extraction and classification apparatus serves multiple functions: it extracts noise components, classifies them by type, identifies attachment state issues, and provides feedback for maintenance. By consolidating these functions into a single integrated system, the patent reduces the complexity that would result from separate devices for each function.
Solution Approach 2:
The system performs self-diagnosis by automatically analyzing its own operational state through noise classification. The noise type classification section enables the apparatus to independently identify attachment state issues without external intervention, reducing the need for additional monitoring equipment or manual checks.
Data Source
Figure 1
Figure 2
Figure 3~4
AI summary
A bioacoustic processing apparatus capable of outputting information that represents the current state of attachment of a bioacoustic sensor. The bioacoustic processing apparatus (300), which processes acoustic signals from a bioacoustic sensor (200) attached to a body surface, comprises: a noise-extracting unit (320) for extracting the noise component contained in an acoustic signal from the acoustic signal, and a noise type classification unit (340) for classifying the extracted noise component into one of a plurality of noise types that correspond to different respective states of attachment of the bioacoustic sensor (200) and outputting information that corresponds to the results of said classification.