Development of gait assist method for parkinson's disease patients with FOG in walking

Parkinson's disease (PD) is progressive degenerative neurological disorder by dopamine depletion. Many PD patients have Freezing of Gait (FOG). During FOG, they have difficulty to start to take a step in several seconds to over ten seconds. FOG leads to fall, and lower Quality of life due to get injured and psychological influence by anxious and fear of falling. For symptomatic relief of FOG in daily life, it is necessary to predict automatically FOG and physical intervention by wearable system without environment arrangement and human assistance. The purpose of this study is to develop a wearable gait assist system that predicts FOG episode and performs physical assistance, and to confirm the feasibility of the system through an experiment. Subjects of the system have enough muscle to walk alone in this study. For this reason, the system is single leg mechanism of exoskeleton type and a power unit is installed in a knee joint. Prediction method for FOG episode is to detect reduction of gait cycle (GC) based on peak-to-peak of toe floor reaction force. For the experiment with an able-bodied participant, the participant performed normal gait and walking with short steps. As a result, the developed system detected all of GC reduction and performed the assistance, and participant's knee joint was flexed. Therefore, we confirmed the feasibility of the developed system with the prediction method through the experiment.