Wearable computing of Freezing of Gait in Parkinson's disease: A survey

Abstract Freezing of Gait (FoG) is defined as a sudden and short event in which a patient loses the ability to step forward. Advanced Parkinson's Disease (PD) patients frequently experience these events. When FoG occurs, falling is possible and this has a severe influence on patients' quality of lives. Recently, the research on detecting and predicting FoG and falls in PD has increased rapidly. However, there has not been a recent systematic survey in this area to conclude the efficacy of wearable devices in both detection and prediction in different environments (clinical, laboratory, home). Thus, this survey summarizes the previous research on FoG computing in sensor selection, feature extraction, algorithms and performance, which provides sufficient background knowledge on the state-of-the-art research. In this paper, we discuss a series of FoG challenges and integral future research trends, which will allow for the advancement of further research.