A real-time detection algorithm for freezing of gait in Parkinson's disease
Freezing of gait (FOG) is a symptom of Parkinson's disease (PD). In this paper, we develop a real-time FOG detection algorithm. To achieve the goal of real time, we adopt the generalized spectrogram with asymmetric windows and the asymmetric smooth filter. Furthermore, instead of using only the frequency domain information, we apply the features in both the time domain and the frequency domain. Simulations show that the proposed FOG detection algorithm has higher accuracy than other methods. Moreover, the time delay of the proposed algorithm is only 1 second, which is 2.25-3.75 times less than that of existing methods.