Better quality of life & lower burden healthcare system
An ICAI Lab is a research collaboration between one or multiple industrial, governmental or not-for-profit partner(s) and one or multiple knowledge institute(s). ICAI Labs always focus on AI technology.
This specific ICAI Lab aims at:
- Increasing the richness and quality of health, dietary and behavioral data by monitoring health using various or novel sensors.
- Developing smart AI algorithms and machine learning techniques to extract more relevant outcomes and knowledge from these data.
- Improving the personalized lifestyle feedback generated from these measurement to coach in the direction of healthier behavior.
By contributing to overall healthier behavior of our population, we can potentially increase the quality of life of people. This will results in lower expected incidence rates of disease and therefore also lower the burden on the healthcare system.
4 work packages
The application domains for the developments are in dietary coaching, preventing cognitive decline, preventing orthostatic hypotension and health promoting chatbots for smoking addiction and sexual health. These areas are covered in 4 work packages. There is an enormous synergy between these work packages on exchanging algorithms, techniques, data, knowledge and expertise.
- WP1: AI for dietary assessment and dietary coaching – The aim of this WP is to develop automatic and semi-automatic measurements of food intake and macronutrient intake, such to be able to use this data to automatically generate personal advice and individualized coaching.
- WP2: Non-invasive markers of cognitive decline and intervention response – The aim of this WP is to develop predictive models of markers for cognitive decline constructed by means of (existing) data from collaborative projects within MOCIA (NWO Crossover).
- WP3: Developing long-term engaging health-promoting chatbots through Natural Language Processing and cognitive modelling – WP3 focuses on the development of health-promoting chatbots in two domains: smoking addiction and sexual health. To achieve this, chatbots need to be able to engage in personalized conversations with users over longer periods of time.
- WP4: Development and application of machine learning algorithms for prevention and detection of Orthostatic Hypotension by wearable sensor technology – This WP aims at development and validation of wearable sensors for measuring blood flow in the brain based on Near Infrared Spectroscopy (NIS).
The ICAI Lab consists out of 7 PhD students and 2 postdocs of excellence working on these challenging AI problems. The lab itself is coordinated by two scientific directors, a lab manager and several work package leaders.