Medication Pill Tracking via Video Sequence Analysis
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Solution Overview
Problem
Existing methods for confirming the identity of medication pills through image analysis face challenges with single image limitations, such as bad lighting conditions and occlusions, making continued identity confirmation difficult.
Innovation Solution
A method and apparatus using a video sequence of images for initial robust confirmation and subsequent less robust confirmation, employing multi-scale image recognition and reduced processing power to overcome occlusions and lighting issues, allowing for accurate determination and tracking of medication pills.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a single still image is used for pill identification, then the device complexity is reduced, but the measurement precision and reliability of identification deteriorate due to bad lighting conditions, occlusions, and inability to capture all necessary attributes
Solution Approach 1:
The identification process is segmented into two distinct phases: initial robust confirmation using full video sequence analysis with multiple attributes, and subsequent tracking using reduced attribute sets. This segmentation allows the system to achieve high identification accuracy while reducing processing complexity during the tracking phase.
Solution Approach 2:
The system performs preliminary robust identification using comprehensive video analysis and multiple attributes before transitioning to simpler tracking. This preliminary action establishes a reliable baseline that enables subsequent simplified monitoring without sacrificing overall identification accuracy.
2Measurement precision
If robust full-attribute analysis is performed continuously, then the identification accuracy is improved, but the processing power requirements and energy consumption increase significantly
Solution Approach 1:
The system dynamically adjusts the level of analysis based on the operational phase. During initial identification, full robust analysis with all attributes is performed. During subsequent tracking, the system transitions to a less robust mode using reduced attribute sets, thereby reducing processing power consumption while maintaining sufficient accuracy for continuous monitoring.
Solution Approach 2:
The system applies partial action by using only the necessary subset of attributes for each phase. Full attribute analysis is applied only when needed for initial confirmation, while subsequent tracking uses a partial set of attributes, reducing overall processing requirements while maintaining adequate monitoring capability.
3Reliability
If multiple video frames are processed for composite image generation, then the identification reliability is improved by overcoming occlusions and lighting issues, but the processing time and computational requirements increase
Solution Approach 1:
The video processing is segmented into initial frame analysis for robust confirmation and subsequent frame analysis for tracking. This segmentation allows the system to invest more processing time and computational resources in the critical initial identification phase, while using reduced processing for subsequent tracking frames, thereby improving overall reliability without excessive time loss.
4Productivity
If continuous tracking with reduced robustness is implemented, then the processing efficiency is improved, but the ability to detect identity changes deteriorates
Solution Approach 1:
The system implements feedback mechanisms where tracking results are continuously compared against the initial robust identification. This feedback loop allows the simplified tracking to detect potential identity changes by referencing the established baseline, maintaining reliability while preserving processing efficiency.
Data Source
AI summary
A method and apparatus for tracking a medication to be administered by a user. The method includes the steps of determining the identity of a medication to be administered by a user, identifying one or more characteristics associated with the medication that are to be used to continue to track the medication, the one or more characteristics including less than a total number of characteristics associated with the medication to be administered, and tracking the medication to be administered in accordance with the identified one or more characteristics through one or more future video images.


