Parafunctional Activity Detection Using Acoustic Signal Filtering
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Solution Overview
Problem
Existing devices for detecting parafunctional activities, such as bruxism and jaw clenching, are not accurately functional during waking periods due to frequent and random facial mimic activities associated with speech, leading to false positives when relying solely on electromyographic signal analysis.
Innovation Solution
A device equipped with sensing means to detect muscular activity and a processor that incorporates a sound detecting device, like a microphone, to differentiate vocal sounds from parafunctional activities, categorizing false positives and accurately identifying parafunctional activities through signal analysis and voice recognition.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If electromyographic signal analysis is used to detect parafunctional activities, then detection capability is provided, but measurement precision deteriorates due to false positives from facial mimic activities during speech
Solution Approach 1:
The patent combines electromyographic signal analysis with sound detection capabilities to create a multi-parameter detection system. The processor integrates signals from both the electromyographic sensor and sound detector, using pattern recognition to distinguish between parafunctional activities and normal speech-related facial movements, thereby improving measurement precision while maintaining detection capability.
Solution Approach 2:
The sound detecting device acts as an intermediary element that provides additional information about the user's state. By detecting sound patterns associated with speech, the system can differentiate between voluntary facial movements during speech and involuntary parafunctional activities, serving as a mediator that resolves the false positive problem.
2Device complexity
If only electromyographic sensors are used, then device complexity is reduced, but reliability deteriorates due to inability to distinguish speech-related activity from parafunctional activity
Solution Approach 1:
The device achieves multi-functionality by integrating both electromyographic detection and sound detection capabilities into a single system. This universal approach allows the device to monitor parafunctional activities while simultaneously detecting speech patterns, improving reliability without requiring multiple separate devices.
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 device effectively monitors and distinguishes parafunctional activities during both waking and sleeping hours, reducing false positives by integrating voice recognition, thereby providing reliable detection and alerting the user to parafunctional activities without discomfort.
Implementation Method 1
sensing means (3, 103) configured to detect a muscular activity and a processor (110) programmed for recognizing a parafunctional activity by means of an analysis of the electromyographic signal detected by said sensing means
Implementation Method 2
a sound detecting device (150, C) is further comprised, cooperating with the processor in such a manner as to distinguish a potential vocal sound emitted in use by the user
Data Source
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AI summary
The present invention concerns a device (1) for detecting a parafunctional activity and comprising at least a sensor (3, 103) configured to detect a muscular activity and a processor (110) programmed to recognize a parafunctional activity by means of an analysis of the electromyographic signal detected by the sensor. According to the invention, a device for detecting sounds (150, C) is further comprised, configured to recognize a voice emitted by the user and cooperating with the processor.