Personal Digital Twin: AI meets physical exercise
Room 2.95, 05/12/2018 (11:30-12:15)
Connected fitness is “digitalizing” the fitness club environment. And enabling that anything is talking to everything, like that the air condition will be automatically increasing the fan intensity level if more than three trainees are exercising for more than 3 min in a common space. And all around making the environment more functional and more comfortable for the training.
What about a connected user and the digitalization of the physical exercise?
What about the possibility that a fitness device “knows” that the trainee was performing weaker (then usually) on the previous two devices.
Or that the device is simple “feeling” that the current user is tired.
Or even that the device can “predict”, after 10 sec trainee’s exercising, the optimal intensity plan for that 90sec unit. And the bonus: device is monitoring in the real-time the progress and alarming the user if the performances are unexpectedly degrading
What about connected people in the fitness club, who will be collaborating in doing a physical exercise, combining gamification and “painful” exercising?
The objective is to analyse the implementation of such scenarios through the usage of AI techniques, esp. big data analytics and deep learning, based on the models from the exercise physiology (e.g. mathematical model that describes the human physiological regulation mechanisms, like human heart rate response during exercising) and applied on the data obtained in nonintrusive way using wearables (like smartwatches)
Organised by: Nenad STOJANOVIC (Nissatech, Serbia)
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