Dental Appliance Motion and Surface Classification for User Feedback
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Solution Overview
Problem
Existing grooming and household appliances lack the ability to leverage internal sensor data and image data effectively to enhance user experience and improve operational efficiency.
Innovation Solution
Integration of physical sensors and cameras with grooming/household appliances to derive augmented classifications, allowing for modified operations based on sensor and image data, including position, surface conditions, and user identity, and providing user feedback.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If physical sensors and cameras are integrated with grooming appliances to collect sensor data and image data, then the ability to derive augmented classifications and modify operation is improved, but device complexity increases
Solution Approach 1:
The patent combines multiple sensors (accelerometers, gyroscopes, magnetometers) and cameras into a single integrated system within the grooming appliance handle. This merging allows the device to collect both sensor data and image data simultaneously, enabling augmented classification without requiring separate standalone devices.
Solution Approach 2:
The grooming appliance is designed to perform multiple functions: it provides grooming treatment while simultaneously collecting sensor data, capturing images, processing this data through machine learning classifiers, and providing feedback. This multi-functionality allows a single device to replace what would traditionally require multiple separate systems.
2Measurement precision
If machine learning classifiers are used to classify sensor data and image data, then measurement precision of position and surface conditions is improved, but computing requirements and device complexity increase
Solution Approach 1:
The system pre-processes sensor data and image data through trained machine learning classifiers before final analysis. The classifiers are trained in advance to recognize patterns related to head position, surface conditions, and treatment progress, enabling accurate real-time classification without requiring complex runtime computations.
Solution Approach 2:
The patent introduces an intermediary processing layer that includes a processor and memory system between the sensors/cameras and the feedback mechanism. This intermediary layer handles the computationally intensive tasks of data fusion and classification, allowing the appliance to maintain high measurement precision while managing processing complexity through dedicated hardware resources.
3Productivity
If real-time data processing and feedback are implemented, then user experience and operational efficiency are enhanced, but energy consumption increases
Solution Approach 1:
The system implements periodic feedback provision rather than continuous real-time feedback. The processor analyzes sensor data and image data at intervals, determining when feedback should be provided based on changes in head position, surface conditions, or treatment progress. This periodic approach maintains operational efficiency while reducing overall energy consumption compared to continuous processing.
Solution Approach 2:
The grooming appliance autonomously processes its own sensor data and image data to provide self-feedback about treatment progress and proper usage. The system automatically adjusts operation based on detected conditions without requiring external monitoring or intervention, enabling enhanced operational efficiency while minimizing the energy overhead of external processing systems.
Data Source
AI summary
A method for operating a dental appliance by providing a dental appliance including at least one motion sensor that provides motion data, the motion sensor is one of an orientation sensor, an acceleration sensor, and an inertial sensor. Further, providing at least one camera associated with the dental appliance that provides image data, and segmenting the image data received from the camera to segment a surface condition using a first machine learning neural network to generate a surface condition segmentation. Then classifying the motion data received from the motion sensor and the image data received from the camera to classify motion and position of the dental appliance with respect to a surface of a user's anatomy, using a second machine learning neural network classifier to generate a surface position comprising at least one of a relational motion classification or a relational position classification. Finally, generating user treatment progress condition and position based on the surface condition and surface position; and communicating the treatment progress condition and position to the user.