Design and Implementation of Automated Ankle Foot Orthosis for Foot Drop Patients Using Gait Cycle EMG Analysis

TLDR: An automated AFO has been developed and implemented to test the feasibility and effectiveness on patients and shows that the effect of GBS on swing phase can be lessened as the value of correlation coefficient increases.

Abstract: Foot drop is known as gait abnormality in which the dropping of the forefoot happens due to the weakness of Tibialis Anterior Muscle for the damage of the common fibular nerve in the anterior portion of the lower leg. In this research, those patients are considered who have foot drop for Guillain–Barre syndrome (GBS). GBS is a peripheral nerve disorder for which bilateral foot drop happens to the patients. So, the aim of this research is to develop an automated Ankle Foot Orthosis (AFO) which will aid the GBS patients in their gait cycle while walking. For the development of this AFO, an EMG analysis has been conducted on both normal people (20 persons, Male 20-45 years) and GBS patients (10 patients, Male 20-45 years) and compared to find out the deviation of the patient’s one from the normal people. The findings of the EMG study show that the stance phase of the gait cycle is not affected by the GBS as correlation coefficient values are in between 0.95 to 1 where the swing phase very much deviates from the normal pattern as the coefficient values are in between 0.6 to 0.7 as well as short swing phase and no heel strike during walking. Considering these, automated AFO has been developed and implemented to test the feasibility and effectiveness on patients. The experimental results show that the effect of GBS on swing phase can be lessened as the value of correlation coefficient increases to 0.85 to 0.9 with long swing phase and proper heel strike on terminal swing phase.