Myasthenia Gravis Disease Diagnosis System

The article presents the design and implementation of an information system to support the diagnosis and follow-up of symptoms resulting from Myasthenia Gravis (MG) disease. MG belongs to a group of rare diseases, the diagnosis of which requires a special approach. The presented system makes it possible to examine the patient, and then using various algorithms analyzes the collected data. The innovative, proprietary algorithm is a procedure for detecting the symptom of drooping eyelid (ptosis), which uses automatic detection of the patient's face, and then analyzes eyelid movements. Another test is the assessment of arm muscle performance. Based on the video recorded during a patient examination, system automatically recognized drooping of the arms. The system is being tested at the Clinic of Neurology in Poznan, Poland and at a hospital in Bydgoszcz, Poland.