Most existing fitness training applications offer effective programmes for guiding users in achieving their fitness goals. Some even provide guided workouts led by trainers. However, these applications have limited capability when it comes to assessing posture during exercise. Poor posture can reduce exercise effectiveness and may even lead to injury. RP has developed a solution that combines video/ imagine processing, human pose recognition, and machine learning technologies to advise users on the correct execution of repetitive movement sequences, such as sit-up and push-up.
A software-only solution.
Can be deployed on both Python and JavaScript platforms, offering flexibility for use on a wide range of affordable devices and operating systems.
Can be seamlessly integrated into existing software applications to enhance existing functionality.
Suitable for the fitness (e.g. yoga) and healthcare (rehabilitation) industries.
Applicable in scenarios involving the counting and assessment of movements of human subjects, such as the correct execution of safety drills.
The small footprint solution can serve as the foundation for intelligent coaching functions in applications that promote healthy living.
Cost-saving as it does not require additional equipment, apart from a camera-enabled mobile phone or laptop.
Enables users to monitor their posture at home or in the gym.
Provide real-time feedback.
Allows for remote assessment of exercise without relying on the expertise of a coach.
RP has successfully completed a proof-of-concept and is actively seeking collaborators to enhance and test the technology.
Get in touch with us today for more information and collaboration opportunities! Drop Us a Message