18064519. HUMAN POSTURE DETECTION simplified abstract (Intel Corporation)
Contents
- 1 HUMAN POSTURE DETECTION
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 HUMAN POSTURE DETECTION - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Key Features and Innovation
- 1.6 Potential Applications
- 1.7 Problems Solved
- 1.8 Benefits
- 1.9 Commercial Applications
- 1.10 Prior Art
- 1.11 Frequently Updated Research
- 1.12 Questions about Posture Monitoring Technology
- 1.13 Original Abstract Submitted
HUMAN POSTURE DETECTION
Organization Name
Inventor(s)
David Pearce of El Dorado Hills CA (US)
David Stanhill of Hoshaya (IL)
HUMAN POSTURE DETECTION - A simplified explanation of the abstract
This abstract first appeared for US patent application 18064519 titled 'HUMAN POSTURE DETECTION
Simplified Explanation
The patent application describes a user computing device that uses both a camera sensor and a depth sensor to analyze a user's posture. The camera captures an image of the user, which is used by a machine learning model to determine the user's posture. The depth sensor provides additional data to refine the analysis and provide feedback to the user.
- Image data from the camera sensor is used to capture an image of the user.
- A first machine learning model analyzes the image data to determine the user's posture.
- Depth data from the depth sensor is used along with the first feature set to generate a second feature set.
- A second machine learning model refines the analysis based on the depth data and the first feature set.
- The user's posture is determined from the second feature set to provide feedback to the user.
Key Features and Innovation
- Integration of camera sensor and depth sensor for analyzing user posture.
- Utilization of machine learning models to determine posture from image and depth data.
- Providing real-time feedback to the user based on posture analysis.
Potential Applications
This technology can be applied in:
- Fitness and wellness applications for monitoring posture during exercises.
- Rehabilitation programs for tracking progress and ensuring correct posture.
- Virtual reality and gaming for enhancing user experience based on posture.
Problems Solved
- Accurately determining user posture using multiple sensors.
- Providing real-time feedback to improve posture and prevent injuries.
- Enhancing user experience in various applications through posture analysis.
Benefits
- Improved posture monitoring and feedback for users.
- Enhanced user experience in fitness, rehabilitation, and entertainment applications.
- Potential for preventing injuries and promoting better health through correct posture.
Commercial Applications
Posture Monitoring Technology for Fitness and Rehabilitation Applications
This technology can be utilized in fitness and rehabilitation centers to monitor and improve user posture during exercises and therapy sessions. By providing real-time feedback, it can enhance the effectiveness of training programs and help prevent injuries.
Prior Art
Prior research in the field of computer vision and machine learning has explored similar applications of analyzing user posture using image and depth data. Researchers have developed various algorithms and models to track and analyze human movements for different purposes.
Frequently Updated Research
Ongoing research in the field of human-computer interaction and computer vision continues to explore innovative ways to analyze and interpret user posture using sensor data. Researchers are focusing on improving the accuracy and efficiency of posture detection algorithms for a wide range of applications.
Questions about Posture Monitoring Technology
How does this technology benefit users in fitness and rehabilitation settings?
This technology benefits users by providing real-time feedback on their posture during exercises and therapy sessions, helping them maintain correct form and prevent injuries.
What are the potential applications of posture monitoring technology beyond fitness and rehabilitation?
Posture monitoring technology can also be applied in virtual reality, gaming, and ergonomic settings to enhance user experience and promote better posture habits.
Original Abstract Submitted
A user computing device includes a camera sensor and a depth sensor. Image data generated by the camera captures an image of a user of the user computing device and is provided as an input to a first machine learning model trained to determine a feature set associated with posture of the user from the image data. Depth data generated by the depth sensor contemporaneously with generation of the image data is provided as input to a second machine learning model along with the first feature set to generate a second feature set as an output of the second machine learning model based on the depth data and the first feature set. The posture of the user is determined from the second feature set to provide feedback to the user.
