Machine Vision Procedural Training With Real-Time CPR Feedback
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Solution Overview
Problem
Modern procedural training, such as CPR, is costly and inefficient.
Innovation Solution
An apparatus and method utilizing a sensor, processor, and machine vision system to capture optical data, identify key positions and parameters of a procedure, compare them to performance thresholds, and provide training feedback.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional procedural training methods are used, then training can be provided, but the training is costly and inefficient
Solution Approach 1:
The patent replaces manual evaluation methods with an automated machine vision system that uses cameras and image processing algorithms to assess CPR performance. The system captures images of the trainer's hand position and compression depth, then automatically analyzes these images against predefined criteria to generate real-time feedback, eliminating the need for expensive manual evaluators while maintaining assessment accuracy
Solution Approach 2:
The training system provides self-assessment capabilities by enabling learners to receive immediate feedback on their own performance through the machine vision system. The system automatically evaluates compression depth, hand position, and other critical parameters, allowing students to self-correct without requiring continuous external evaluation, thereby reducing overall training costs and improving efficiency
2Productivity
If machine vision system is implemented, then real-time feedback is provided improving training efficiency, but device complexity increases
Solution Approach 1:
The patent divides the complex evaluation task into separate, manageable components by analyzing different aspects of CPR performance independently through the machine vision system. Each aspect such as compression depth, hand position, and body angle is evaluated as a separate parameter with its own detection algorithm, making the overall complex system more manageable and easier to implement
Solution Approach 2:
The machine vision system is designed as a multi-functional platform that can evaluate multiple CPR parameters simultaneously using a single camera system. The same hardware infrastructure supports various evaluation modes and can assess different aspects of performance (compression depth, hand placement, recovery position) without requiring separate specialized devices for each measurement, thereby managing complexity through versatility
Data Source
AI summary
In an aspect, an apparatus for procedural training is presented. An apparatus includes a processor and a memory communicatively connected to at least a processor. The memory contains instructions configuring at least a processor to receive optical data from a sensor, wherein a machine vision system is configured to identify at least one object within optical data. At least a processor is configured to determine a procedural performance parameter as a function of optical data wherein determining the procedural performance parameter comprises classifying the at least one object within optical data to an optical data category using an optical data classifier. At least a processor is configured to compare a procedural performance parameter to a procedural performance threshold. At least a processor is configured to display procedural training feedback through a display unit as a function of a comparison.