Monitoring and fuzzy warning system for risk prevention of Guyon’s canal syndrome

Abstract

Guyon’s canal is a very small tunnel in the wrist where the ulnar nerve and ulnar artery are passing through. As it goes down from the canal, the ulnar nerve runs through the last two fingers and provides sensory innervation of the fifth and half of the fourth fingers. When it is trapped in Guyon’s canal, due to continual compression or pressure, some symptoms could emerge, like feeling of pins and needles, numbness and decreased sensation. One of the characteristic reasons of Guyon’s canal syndrome (GCS) is habitual misuse of computer keyboards that may cause constant pressure to the ulnar nerve. Therefore, in this paper, we present a novel methodology of monitoring and identification supported by a fuzzy warning system that warns the users to prevent from wrong wrist posture and to reduce the risks of GCS. From the images taken by a camera mounted on a laptop monitor, hands of the user are segmented for location of the exact wrist region. Afterwards, the angle of the wrist is estimated and subsequently a fuzzy-based warning system is triggered by the angle and the duration data. The results are greatly encouraging that the hands on the keyboards and wrist angles are perfectly identified; and depending on the duration and the angles of wrists, the warning system is generated correct signals to warn the users for changing their wrist posture. As an outstanding instance of artificial intelligence-based systems in ergonomic research, the monitoring system would help the users with the bad posture habit to reposition their wrist for wrist health.