  The ability to use digitally recorded and quantified neurological exam
information is important to help healthcare systems deliver better care,
in-person and via telehealth, as they compensate for a growing shortage of
neurologists. Current neurological digital biomarker pipelines, however, are
narrowed down to a specific neurological exam component or applied for
assessing specific conditions. In this paper, we propose an accessible
vision-based exam and documentation solution called Digitized Neurological
Examination (DNE) to expand exam biomarker recording options and clinical
applications using a smartphone/tablet. Through our DNE software, healthcare
providers in clinical settings and people at home are enabled to video capture
an examination while performing instructed neurological tests, including finger
tapping, finger to finger, forearm roll, and stand-up and walk. Our modular
design of the DNE software supports integrations of additional tests. The DNE
extracts from the recorded examinations the 2D/3D human-body pose and
quantifies kinematic and spatio-temporal features. The features are clinically
relevant and allow clinicians to document and observe the quantified movements
and the changes of these metrics over time. A web server and a user interface
for recordings viewing and feature visualizations are available. DNE was
evaluated on a collected dataset of 21 subjects containing normal and
simulated-impaired movements. The overall accuracy of DNE is demonstrated by
classifying the recorded movements using various machine learning models. Our
tests show an accuracy beyond 90% for upper-limb tests and 80% for the stand-up
and walk tests.
