Movement Digital Biomarkers for Functional and Cognitive Decline in Dementia

Background Digital biomarkers based on accurate tracking of motor behaviour can provide a cost‐effective, objective, and robust measure for disease progression in dementia, changes in care needs, and the effect of interventions. Most of our brain is involved in the planning and execution of movement. Hence, quantifying and monitoring movement can produce powerful indicators of both motor and cognitive decline. In this project, we develop an intelligent system that computes and tracks movement‐based digital biomarkers of dementia. Methods The project is established in a controlled and ecologically valid mock apartment – the Living Lab – situated in the UK DRI Care Research and Technology Centre. We collected patients’ performance in a set of physical tasks and activities of daily living (ADL) with a depth‐based motion capture system, along with neurocognitive measures using Addenbrooke’s Cognitive Examination III and Cognitron. We first conducted temporal and spatial synchronisations of data collected from six Microsoft Azure Kinect cameras to produce high‐precision three‐dimensional joint coordinates that provide dynamic postural representations. These were then used to compute digital kinematic markers. This was followed by an assessment of the efficacy of the biomarkers in characterising people affected by dementia. We examined the association between the biomarkers with motor and cognitive function and overall efficiency in performing ADL. Results Our preliminary analysis showed that patients and healthy controls can be distinguished by the distribution of extracted features (an example feature – spinal curvature – is shown in Figure 1) in structured tasks and free behaviour. The variance of the distribution was correlated with performance in clinical assessments. Conclusion Our analysis suggests the feasibility of digital biomarkers in characterising functional limitations and cognitive decline. Successfully validated biomarkers can be integrated into remote health monitoring systems at home, care‐homes, and clinics, with the potential to revolutionise prognostic prediction and functional assessment of dementia.