Neuropsychology & Cognitive Science
“Alzheimer’s desease is the sixth leading cause of death for all ages and the fifth leading cause of death for those 65 years of age and older in the U.S. This disorder affects approximately 5% of people 65 to 74 years of age and almost 50% of people older than 85 years of age, at an annual cost of approximately $148 billion in the U.S. alone. The problem will become much greater as baby-boomers age. An estimated 5.3 million persons in the U.S. have AD. This figure is projected to grow to 13.2 million by 2050.”
Source: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2873716/
Alzheimer’s disease is already a huge issue and with the ageing population it is becoming massive. The established treatments aren’t revolutionary and there is so far no cure for the disease, but it is vastly preferable to be diagnosed and treated than to suffer without a diagnosis.
Given this, it is unfortunate that 50-65% of dementia cases go unnoticed (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5293981/). Earlier diagnosis improves the chances for effective treatment, and this is the area in which we see major potential for quick improvement.
We are currently researching:
- Which cognitive functions are being used while interacting with various forms of brain training tools,
- How to better detect the first symptoms of brain degeneration, using digitalized versions of pen&paper cognitive tests,
- The most advanced non-invasive tracking methods of physiological states such as alertness, restedness and stress-levels,
- Which data-analysis models are best suited for the detection of first cognitive decline symptoms, using as raw material the user’s input and physiological data,
- Would special, dedicated equipment, tightly integrated with the operating software, help with detecting early stages of cognitive decline.
Our goal is to develop a non-invasive process of cognitive performance monitoring that will detect the first signs of illness-induced cognitive decline.
If this sounds like a goal worth achieving to you, feel free to contact us and share your views on the topic.
Puzzle Generation Algorithms
Puzzle generation algorithms offer a broad field of research. Our main focus so far has been content generation speed and accuracy. Our current goal is to develop a one-click content production process for a complete puzzle magazine. We are experimenting with massive multi-threading (using GPU-based rigs as computing centers), which allows us to run tons of concurrent tasks. Effectively making the one-click concept much closer to reality. And to recreate the quality of a human compiler, we are using clever templating methods and smart backtracking.
There are two other directions in which our attention is shifting. The first one is increasingly gamified and novel puzzle content. This includes new approaches to the solving experience such as multiplayer and gamification features, but also innovative technologies such as AR and MR to form unique, stimulating ways of interaction.
This brings us to the second focus, which is to design in-game functionalities that serve out-game goals. One example is an AR-based 3D puzzle solving experience that facilitates physical activity. Physical activity is an important factor in maintaining cognitive health. Merging puzzle content-based games, sports tracking and cognitive health monitoring, we aim to uncover ways to make the entertainment that we produce increasingly engaging and meaningful.
Interested in hearing more about innovative puzzle types and ways to interact with them? Contact us and we will share our vision with you.
Virtual Remote Collaboration Spaces
A further field of our research includes technologies functioning as the basis for virtual collaboration spaces. These spaces can be 2D shared whiteboards like Miro or 3D joint AR/MR spaces like Spatial.
As Spatial’s demo illustrates, AR/MR technology is far advanced. Yet, it is obvious that it is still to some degree clumsy. One of the bottlenecks of the currently used bi-directional AR-goggle based technology is that it generates a gargantuan amount of input data, leading to a substantial transfer lag. It seems unlikely that this can be surpassed by minor technical tweaks, which is why we are researching a completely new approach to the underlying technical structure.
Want to join our research or hear more about it? Contact us and we can explore collaboration possibilities.