  Parkinson's disease ranks as the second most prevalent neurodegenerative
disorder globally. This research aims to develop a system leveraging Mixed
Reality capabilities for tracking and assessing eye movements. In this paper,
we present a medical scenario and outline the development of an application
designed to capture eye-tracking signals through Mixed Reality technology for
the evaluation of neurodegenerative diseases. Additionally, we introduce a
pipeline for extracting clinically relevant features from eye-gaze analysis,
describing the capabilities of the proposed system from a medical perspective.
The study involved a cohort of healthy control individuals and patients
suffering from Parkinson's disease, showcasing the feasibility and potential of
the proposed technology for non-intrusive monitoring of eye movement patterns
for the diagnosis of neurodegenerative diseases.
  Clinical relevance - Developing a non-invasive biomarker for Parkinson's
disease is urgently needed to accurately detect the disease's onset. This would
allow for the timely introduction of neuroprotective treatment at the earliest
stage and enable the continuous monitoring of intervention outcomes. The
ability to detect subtle changes in eye movements allows for early diagnosis,
offering a critical window for intervention before more pronounced symptoms
emerge. Eye tracking provides objective and quantifiable biomarkers, ensuring
reliable assessments of disease progression and cognitive function. The eye
gaze analysis using Mixed Reality glasses is wireless, facilitating convenient
assessments in both home and hospital settings. The approach offers the
advantage of utilizing hardware that requires no additional specialized
attachments, enabling examinations through personal eyewear.
