Abstract:
Neuropsychological test are used to identify the presence of brain injuries or any associated
function deficits. These tests evaluate functioning in a number of areas which include
intelligence, attention, memory and language etc. Psychologists generally conduct these
tests with a single person in an office environment that is free from distractions and
disturbances. Drawing tasks have achieved a central location in neuropsychological
assessment and contains information about the presence of neurological disorders. Drawing
tests have been long used by doctors and researchers for early detection of psychological
and neurological disorders. Mini-Cog test is a combination of the Recall test and Clock
Drawing Test and the combined scoring of these tests identifies whether the person is
demented or not. This test is divided into three different steps. Firstly, the patient is
shown three different words. Furthermore, the patient has to draw digits on a piece of
paper where a clock circle is already drawn. In the last phase, patient is asked to recall
the words which were shown in the first step. This test is currently scored and interpreted
manually which increases the work load of practitioners and also consumes a significant
amount of time. The purpose of the proposed project is to develop an efficient, reliable and
accurate diagnostic tool which will reduce the work load of psychologists by automatically
screening the subjects using the Mini-Cog test. This study proposes the application of
image analysis techniques to automatically score a subset of hand drawn clock images
in the test. The developed system evaluated on a number of hand-drawn clocks realized
promising results.
