Cognitive Gaming Platforms
May 1, 2013, Neuro-Gaming Conference, San Francisco—Closing the loop from monitoring to feedback can be used to track, understand, and boost attention and cognitive performance of players. A panel moderated by Zack Lynch from the Neurotech Industry Organization looked at opening up new avenues for experience development. The panel members were Mike Oxley form Foc.us, Amy Kruse from Intific, Joe Hardy from Lumos Lab, and Chris Berka from Advanced Brain Monitoring.
Technology is emerging from research. One of the challenges relative to the state of functions versus game penetration?
Oxley is focused on product development, so he doesn’t know of other markets.
Kruse identified a need for gathering all the people in a space. Game development is an iterative process that needs a team. New interfaces create more opportunities, but integration is a challenge.
Hardy is interested in training and increasing cognitive functions. The market is shifting to lighter, interactive games and the existing engines are moving to a more casual format on more platforms.
Berka noted that existing technology and platforms can use new I/O devices that there is no integration. This creates new areas for applications, which is a disconnect with the researchers and game developers. Developers need APIs and looks for interfaces at the operating system level. Scientists need help with graphics and game design to accelerate learning.
Integrating sensor information into gaming?
Hardy considered that this integration is not too advanced yet, and still mostly in research. Everyone is still developing baseline data, and products need refinement. The stimulation side may also be good for improving cognitive growth.
Latency versus frequency for fidelity?
Berka responded that closed loop parameters require a millisecond basis. They have to synchronize to visual stimulation, so most sensors are too slow. Galvanic skin responses area slow and heart rate change, although faster, cannot meet this latency requirement. They can capture up to 128 channels of data in real time, but the processing algorithms have to be done off-line, or slowly in situ.
EEG and neural feedback for cognitive exercises?
Hardy commented that this is traditional biofeedback. Integration into games is unknown at this time. Their primary focus is to measure up outputs and responses, so they don’t know enough yet. Any additional data can be useful to change game parameters.
Inputs and outputs from other stimulation? Realistic technology in next 20 years?
Hardy suggested that cognitive training will become ubiquitous some time in the next 5-20 years. Everyone seems to understand the need for brain training.
Changes in non-brain training games?
Hardy offered lots of ways to go, with lots of available technologies. The education market is a large one for games and neuro-games.
Kruse added that this situation echoes the short term focus on fitness and data acquisition.
Cognitive and physics are moving together in areas like education. We will see more wearable sensors that align with educational goals. In 20 years, we will get to the trans-human with implantable sensors. We need to think of gaming in other views, such as aging people increasing adoption rates.
Oxley mentioned that standards will make more sensors and actuators widely accessible and easy to use. A lot will depend upon cloud-based compute for the underlying functions. People will change. So far, the studies for their devices are following the products.
Berka offered close to ubiquitous EEG for education and training and disability mitigation. In 20 years, we will have much greater human-machine interfaces like exo-skeletons, prosthetics, etc. Group optimizations from 2 to thousands in the same process will result in social, neural games.
