Trampolines really seem to get people moving and the added jump height and reduced impact makes gymnastics training accessible to new target groups. The prices have dropped and there seems to be a trampoline in every backyard in the Finnish suburbs. Furthermore, a computer vision based trampoline system can improve safety by monitoring that there's only a single player bouncing at a time, something that indoor activity parks like Hoplop and Huimala require but don't have enough personnel to enforce. In this study, 74% of trampoline injuries were from situations where there was more than two people on the trampoline.
We aim to develop games and feedback tools to help in
learning motor skills, and investigate the user experience, e.g., effect on
skill acquisition and perceived competence. The importance of feedback in
learning is well known, but the possibilities of novel technologies such as
depth cameras (Kinect) are still relatively unexplored. So far, we have made a
feasibility study, creating two simple Kinect games played on a trampoline. We
have found that there's no fundamental obstacles for such systems - the safety
net and elastic bed of the trampoline don't interfere too much with the
tracking, the latency is not disturbing except for very low jumps (high jumping
frequency), and it is possible for the user to watch a screen or screens while
jumping. Demo video:
In our research, we try to explore the
following mechanisms:
- Increasing body awareness with audiovisual feedback. Beginners often have no clue what their body is doing when they end up in unusual positions (hand stand, flipping in the air...). Displaying video and relevant measurements on a screen, either concurrently or with appropriate delay, can help in realizing what needs to be improved. The challenge is to keep the information visualization simple and focused and to find the best ways to control the system without interfering with training, e.g., using gestures or voice commands. See my previous post for examples of feedback systems.
- Manipulating the learning curve to help the user stay in the flow channel. For example, in gymnastics, the learning curve may actually be in the form of a staircase with high steps - you learn a skill, after which there may be little or no perceived progress until learning the next new skill, which may seem far. A good coach comes up with appropriate intermediate challenges and supporting exercises to keep the student motivated. Using a computer system, we can do the same but using quantitative measurements. For example, the first trampolining skill to learn is to jump high while staying in the middle of the trampoline. Using a Kinect, we can measure where the student lands and give a prize for executing 10 consecutive jumps that reach higher than 1 meter while staying inside a circle with radius of 50cm. As a more advanced example, after learning a single flip on a trampoline, a virtual on-screen obstacle can be added over which the student tries to do the flip higher and higher until reaching a height suitable for attempting a double flip.
- Manipulating perceived competence through the player's on-screen representation (avatar). The importance of perceived competence in staying motivated in sports training is well established in the literature. There's some recent studies showing that augmented feedback can improve perceived competence. We hypothesize that perceived competence can be increased by finding an optimal balance of developing real and virtual skills and attributes of the player. Some form of character development/upgrading is used in many games. In a physically interactive fighting game, the player may earn both real martial arts skills and abilities (kicking technique, flexibility, strength) and virtual ones (various armors to improve resistance to damage, improved jump height or kick strength to leap over or destroy obstacles, flaming hands that cause more damage, the ability to fly, posing to trigger spells...). Because the player identifies with the avatar, perceived competence is probably affected by the avatar's abilities. There's some anecdotal evidence to support the hypothesis, but we need to run comparative studies using different game versions and a standardized perceived competence questionnaire.
- Improving training safety by gamifying low risk exercises - in case of trampolining this would mean avoiding somersaults and flips to prevent neck injuries, and instead focus on basic jumping, landings (seat, front, back) and twisting around the vertical axis. The basic jumping games in the video above seem to motivate jumping by giving concrete goals and feedback, but we still need to come up with more examples and confirm the effects using suitable metrics, such as the Game Engagement Questionnaire.
Edit 4.9.: formatting, added the bullet about training safety
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