We developed a method based on machine learning that can create a model of user behaviour. Different types of behaviour can be modelled, but at the moment we model physical activity, sleep patterns and mental state, as obtained from sensors and questionnaires. This model can then predict likely future behaviour (e.g., increased or decreased physical activity) as well as detect anomalies in the current one (e.g., unusually low physical activity). Such predictions can in turn be used for monitoring the users’ progress, encouraging them or giving them personalised advice.
Addressing target audiences and expressing needs
- Grants and Subsidies
- Business partners – SMEs, Entrepreneurs, Large Corporations
- Technology Transfer Expertise
We are interested in further development of our result in research/development projects. We seek to increase accuracy, extend scope and similar.
Alternatively, we are interested in making this result more mature and better adapted to commercially relevant applications. This could be done to satisfy the needs of a specific customer (who would fund the adaptation), or for general commercialisation in partnership with a company.
- Public or private funding institutions
- Other Actors who can help us fulfil our market potential
- Private Investors
R&D, Technology and Innovation aspects
Our software has been integrated in the WellCo virtual coach prototype. It works well in this context. Next steps can be in several directions: (1) make minor refinements to incorporate in a commercial version of the WellCo system. (2) Identify commercial applications in need of such software, and adapt it to them. (3) Identify datasets to which the developed method can be applied, and refine it in research context. Several of these steps can be done in parallel.
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