Indications of Neural Disorder through Automated Assessment of the Box and Block Test

Abstract

The needs of an ever growing global aging population are a cause of world wide concern. The consequent ageing of the human nervous system is a major risk factor for stroke and many other neurological disorders. These pathological conditions affect the activities of daily living and impose a support and resource burden on society. Rehabilitation is long term and resource intensive and even so, it can be subjective and inconsistent in execution. We propose a novel system to indicate the level of neurological disorder by electronically scoring a widely used rehabilitative assessment for the upper limb. This is done by embedding widely available sensors into the objects used in this assessment. We enhance this with a two new features derived from these sensors and process one of them using a data driven approachA set of pilot trials were conducted to demonstrate the effectiveness of our approach with promising results.