Therapeutic Smile Detection via Facial Segmentation
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Solution Overview
Problem
Conventional facial recognition systems are unable to detect genuine smiles, which have therapeutic benefits, and lack features to train individuals in executing genuine smiles with appropriate frequency, duration, or in response to physiological triggers.
Innovation Solution
A system comprising a facial expression detection device and a system processor that acquires and processes facial data to identify and encourage genuine smiles by setting target criteria, prompting users to exhibit such smiles, and tracking their execution over time, potentially linked to health metrics and feedback displays.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional facial recognition systems are used, then general facial expressions can be detected, but genuine smiles with therapeutic benefits cannot be detected
Solution Approach 1:
The patent segments the smile detection process into distinct components: detecting mouth curvature, detecting eye muscle activation (orbicularis oculi), and combining these indicators to determine genuine versus fake smiles. This segmentation allows the system to achieve high precision in detecting therapeutic genuine smiles while maintaining the ability to recognize other facial expressions through the same modular detection framework.
2Ease of operation
If conventional facial recognition systems are used, then basic expression detection is available, but training features for executing genuine smiles are missing
Solution Approach 1:
The system incorporates feedback mechanisms that provide users with real-time information about their smiling technique and frequency. The processor analyzes detected genuine smiles and provides feedback through the user interface, guiding users on how to execute therapeutic smiles properly. This feedback loop enables training functionality without requiring complex additional hardware, as the feedback is generated from the existing detection capabilities.
3Productivity
If conventional facial recognition systems are used, then expression detection is available, but features to encourage genuine smiles with specific frequency and duration are absent
Solution Approach 1:
The system implements periodic action by setting target criteria for smile frequency and duration, then monitoring and encouraging users to meet these targets over time. The processor compares actual smile occurrences against predefined targets and provides periodic encouragement or alerts to help users achieve therapeutic smile goals. This structured periodic approach increases productivity in executing therapeutic smiles without requiring complex intervention systems.
Data Source
AI summary
Systems for detecting when a person exhibits a smile with therapeutic benefits including a facial expression detection device and a system processor. The facial expression detection device is configured to acquire facial expression data. The system processor is in data communication with the facial expression detection device and is configured to execute stored computer executable system instructions. The computer executable system instructions include the steps of receiving facial expression parameter data establishing target facial expression criteria, receiving current facial expression data from the facial expression detection device, comparing the current facial expression data to the target facial expression criteria of the facial expression parameter data, and identifying whether the current facial expression data satisfies the target facial expression criteria. The target facial expression criteria define a smile with therapeutic benefits.