Assessing the transparency of a visualisation platform displaying the activity of individuals with dementia who are experiencing circadian lighting

The integration of sensing and actuating technologies to deliver
responsive frameworks for solving user needs has been a huge support to multiple
industries. Of particular importance is the heavily burdened and highly understaffed
healthcare industry. However, the ability to provide such solutions is dependent on
the accurate understanding, manipulation and visualisation of the domain-specific
data. A significant part of this involves studying the human-computer interaction of
these technologies and their applications in order to increase their value. Therefore,
this work divulges on the relationship between lighting and related human activity
metrics, with an emphasis on assessing the clarity of the information provided on the
visualisation platform. The context of this work is outlined in the following.
For hundreds of thousands of years, the natural ‘alarm clock’ of the human body has
been determined by the seasonal timing of the rising and setting sun. These light-
dark intervals inform the body of their sleep/wake schedule, activity levels, energetic
state and mood, by controlling the release of the melatonin hormone. Therefore, the
variability in these body processes for any individual are the result of their
synchronisation with these light-dark cycles, through a system known as the human
circadian rhythm.
Measuring an individual’s circadian rhythm therefore requires aggregating data
surrounding the general activity of an individual, in varying degrees of granularity
aligning with the 24 hour light-dark cycle. In this work, a daylight-simulating luminaire
has been developed, which encourages alignment of the human circadian rhythm to
the approximate 24 hour cycle. This is paired with a sensing device which can
unobtrusively track an individual’s position at a high resolution. In this way, the
research objective to determine the impact of the lighting on circadian rhythms can
be achieved.
A simultaneous objective is to assess how useful the collection and presentation of
this data is for those using making use of the system. In this work, the focus is on
observing individuals with dementia, since their diagnosis and typical age
demographic lends itself to a stronger de-synchronisation of the circadian rhythm.
Therefore, informal workshops were held with care staff in a local care home in
Belfast to assess the human-computer interaction with the visualisation dashboard
presenting these activity metrics. We have designed several simulations of resident-
typical activity which the sensor is capable of tracking. The metrics are stored within a database and presented on a plug-in dashboard. An assessment of the
transparency of these metrics is achieved by utilising feedback from care staff. The
results will then be used to inform future versioning of the visualisation platform. The
end goal is to optimally address the care staff need in alignment with the scope of
the technology used in the framework.