Ambient Assisted Training
The AmI system behind this demonstrator has to optimise the training of a group of racing cyclists.
There is group of 2 to 30 racing cyclists. Each cyclist has his own performance profile and training plan. Cyclists and bikes are equipped with a multiplicity of sensors (speed, pulse, pedal force, power, wind, etc.). The bikes are connected to each other and to a coach unit that executes the application, via an ad-hoc, wireless network. The task of the AmI system is to optimise training for the entire group. The training ride has to be planned and controlled in such a way that each cyclist meets his training plan as far as possible.
In an additional scenario, the AmI system also has to support the overall competition, that is, the race situation of the bicycle group as well. Using the same technology, the task now is to win a race; that is, a given point from A to B must be passed in minimal time by one member of the group. The bicycle group is controlled using the stored performance data as well as the actual sensor data, and the condition of the cyclists.
Of course, the training of an individual cyclist can also be supported with such an AmI system.
The advantages of an AmI system in a training situation will now be summarised using two examples, individual training and group training.
The AmI system gives an online optimisation for training stress based on an individual's performance profile and training plan. Here, the control values of "power" and "heart rate" will be adapted in order to process their dynamics. The values will be modified depending on the individual's physique and individual strength as well as environmental and track conditions (wind, track profile, etc). The system thereby enables online expertise and intervention by the coach during the training, as well as training documentation and analysis after training.
Two suggested scenarios could be as follows:
This scenario also concerns the optimisation of the training load of each individual cyclist, however, the cyclist is riding in a group. The AmI system must consider the restrictions of the group, so that the optimisation of the overall performance of the group remains the focus. The formation and speed of the group as given by the system depends on:
The AmI system is now used to monitor the training parameters of the individual cyclists to optimise the group's speed, position changes, and formation/structure.
For the group training, two possible scenarios are presented:
Although the scenarios described above look like toy scenarios without any serious background, this is not true. Many trainers are very interested in having such a training aid. Whilst the whole system is far beyond state of the art, several aspects are already available for top teams, who can afford current, expensive solutions. Of broader interest would be an "AmI solution" for the whole scenario that is cheap and light weight, comprises unobtrusive hardware, and that controls and adapts to an actual situation. For that, the objectives have to be elaborated.
For our AmI research center, the main advantage of this scenario is that it covers many different research questions, which are typical for AmI:
Today, the tasks of the AmI system, which have been described, are done more or less optimally by a coach. The coach generally knows the quality of the cyclists. However, he does not know the exact, current situation regarding training or running. "However, the Aml system could further improve the situation dramatically," confirms Mr Mühlfriedel, head of the racing cycle department at the "Heinrich-Heine-Gymnasium", an elite sport school not far from our university.
In addition to their own research questions, the scenarios relate to other domains so that solutions for these scenarios will fit others, too. Examples for general AmI research questions include:
In mid-2004, our AmI Research Centre began to develop a demonstrator for the bicycle scenario. The demonstrator covers four racing bikes, which are equipped with different sensors and a wireless network (see below). The demonstrator is designed in such a way that in the medium-term, we can perform experiments with competitive cyclists in cooperation with the Heinrich-Heine-Gymnasiums.
Furthermore, it is hoped, that the demonstrator can be used both outdoor ("outdoor" or "real life" demonstrator) and indoor ("indoor" or "VR" demonstrator). For the latter, the four bicycles, mounted on wheel stands or ergometers (ref. indoor cycling training) are attached to a simulator. This simulator, in combination with a screen and the braking force of the wheel stands, replaces the environment of the real-life demonstrator. By adapting the braking force for each bike individually, cyclists with totally different physiques can use the demonstrator together.
We currently work on following tasks:
With the currently available prototypes we already performed first experiments, successfully:
Finally, we want to list several visions in the context of the assisted training demonstrator: