Exercise Guidance Training Data Synthesis with Movable Camera Feedback
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Solution Overview
Problem
Existing exercise machines with embedded cameras are limited by obsolescence, field of view, and computational capabilities, leading to inefficient and potentially unsafe strength training due to incorrect form recognition and lack of advanced feedback.
Innovation Solution
Integrating a movable external camera device with a cable-based exercise machine to distribute computation and enhance feedback capabilities, using computer vision to provide real-time form feedback and combine with cable-based measurements for improved guidance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If an embedded camera is used in the exercise machine, then the device structure is simplified and cost is reduced, but the field of view is limited and the camera becomes obsolete quickly
Solution Approach 1:
The system separates the camera function from the exercise machine by using an external camera device that can be independently positioned and configured. This segmentation allows the camera to have an unrestricted field of view while the machine maintains its simplified structure.
Solution Approach 2:
A communication interface acts as an intermediary between the external camera device and the exercise machine, enabling data transfer without physical integration. This mediator allows the system to benefit from both the simplicity of separate components and the functionality of integrated operation.
2Device complexity
If an embedded camera is used in the exercise machine, then the device structure is simplified, but the computational capabilities are limited
Solution Approach 1:
The computational workload is segmented between the external camera device and the exercise machine. The camera device performs initial image processing and form analysis using its own computational resources, while the machine handles workout programming and performance tracking, thus overcoming the limited computational capability of embedded systems.
Solution Approach 2:
The communication interface serves as a mediator that transfers processed data from the camera device to the machine, allowing the system to leverage the computational power of external devices without requiring the machine itself to have high computational capabilities.
3Reliability
If real-time form feedback is implemented using camera data, then exercise safety and efficacy are improved, but communication overhead and CPU utilization increase
Solution Approach 1:
The system performs preliminary processing of camera data to extract only the essential form feedback information needed for safety monitoring. By pre-processing the data and identifying key performance indicators before transmission, the system reduces the amount of data that needs to be communicated in real-time, thereby reducing communication overhead while maintaining exercise safety.
Data Source
AI summary
A first video of a first individual performing an exercise movement is received, wherein the first video is associated with a first guidance label. A modified version of a video is generated at least in part by passing the first video to a pose data change model. The modified version of the video is associated with a second guidance label. A guidance classifier model is trained using the modified version of the video.