Age related cognitive diseases are becoming a growing problem in Sweden. With the fast ageing population and lowered mortality rate comes the spread of cognitive diseases related to dementia. In order to accommodate this growing target group in transport and the built environment, it is important to understand the mobility and travel behaviour of patients suffering from these diseases. One subset of this target group is travellers suffering from age induced illnesses related with dementia, which most often have fluctuating symptoms that are affecting the cognitive skills of the traveller. This makes it hard to use standardized forms and survey-based information that would require the traveller to actively respond retroactively, either in oral or written form, since the traveller might have forgotten or mixed up their past experiences, among other things, it becomes very hard to gain confidence in the results as it might be hard to tell in which condition the patient is during the collection.

We propose an automated collection of biometric data such as heart rate in combination with position. Since the validity of the information collected in this manner is directly related to the quality of the sensors used it means that the precision and accuracy of the results could be virtually endlessly improved by upgrading the hardware and optimizing the software. To take a first step towards a solution like this we have started developing a smart watch application which is utilizing PPG technology to collect heart rate and combine it with positions collected through GPS technology.

Early testing has shown the possibility to correlate the heart rate of a traveller to their specific location. The implications of this must be validated through data labelling as we wish to utilize machine learning algorithms to analyse the data collected.