Overview / Usage

The human skeleton is designed to support body weight by adapting to repeated stress. Repetitive weight-bearing exercises help to increase and maintain bone density as the load places stress on the bone, stimulating the growth of new bone tissue and slowing bone loss. Bone being a connective tissue is sensitive to changes in weight-bearing and mechanical forces. Resistance/weight training may influence bone mass, area, width, and density. The essential components of mechanical loading influence the rate of adaptations that include Intensity, Speed, and Direction of forces as well as the volume of loading. As bone density starts to decrease in people over 30 years old, weight-bearing exercise becomes increasingly important. Remember that Bone is living tissue and as such adapts to the way used just as muscle adapts to the way it is used. Fitness training balances the key elements of good health including strength training, core exercises, balance training, and flexibility and stretching. Training Programs mantra “use it or lose it” need to emphasize skeletal imagery in order to visualize the quantum of load it can endure.

Methodology / Approach

We propose an effective, affordable, real-time Deep Learning Fast R-CNN based algorithm equipped with voice assistance/alert which by means of skeletal imagery features monitors the load the skeletal system endures during workouts/training. The Entire system is built with the OpenVINO Toolkit! The system with its observation cautions/guides in real-time over the voice assistant/alert to ensure the exercise/training is being carried out properly. This can pave way for improvising the training effectiveness and also aids in visualizing the decreased bone density a condition known as Osteoporosis, or weak bones, a disease that causes bones to become brittle and more likely to fracture. This will help a long way in undergoing precautionary diagnosis/treatment in case of any abnormalities noticed. We also offer historical data about the details for any further analysis.

Technologies Used

OpenVINO

AI