Bench Press Detection Computer Vision Project

Thomas Bardhi

Updated a year ago

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Classes (8)
barbell
benchpressHeel
benchpressaboveshoulder
benchpresschest
benchpressshoulder
elbow
hand head

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Description

Here are a few use cases for this project:

  1. Personal Fitness Apps: The "Bench Press Detection" model can be integrated into fitness apps. It can provide real-time feedback on the user's form during the exercise, ensuring safety and effectiveness. The use of multiple identifiers like 'elbow', 'hand', 'head', etc., allows the system to monitor joint angles and barbell height ensuring proper execution.

  2. Physical Therapy & Rehabilitation: In physical therapy centers the system can be used to monitor patients recovering from injuries. It can ensure that exercises are being performed correctly, reduce the risk of re-injury, and provide valuable data to therapists.

  3. Gym Equipment Manufacturers: Companies manufacturing gym equipment like smart benches can integrate this model into their products to provide an interactive and personalized experience to users with automatic detection and feedback on their form.

  4. Fitness Trainers & Coaches: The model could be a valuable tool for trainers and coaches, enabling them to monitor and correct their athlete's form in real time or through a review of recorded sessions. The system can act as a second eye, detecting potential issues that may be missed.

  5. Research & Sports Science: Researchers in sports science can use the "Bench Press Detection" model to study more about the biomechanics of the exercise, effectiveness of different techniques or impacts on specific muscle groups. The detailed class detection can provide granular data for in-depth analysis.

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Cite This Project

LICENSE
CC BY 4.0

If you use this dataset in a research paper, please cite it using the following BibTeX:

                        @misc{
                            bench-press-detection_dataset,
                            title = { Bench Press Detection Dataset },
                            type = { Open Source Dataset },
                            author = { Thomas Bardhi },
                            howpublished = { \url{ https://universe.roboflow.com/thomas-bardhi-d9m1v/bench-press-detection } },
                            url = { https://universe.roboflow.com/thomas-bardhi-d9m1v/bench-press-detection },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { jun },
                            note = { visited on 2024-09-27 },
                            }