The design of an effective bio-inspired deep learning multimodal technique for identifying gait components from real-time video samples is presented in this paper. For robust modelling of temporal dependencies in gait components, the suggested method combines two well-known Recurrent Neural Network (RNN) models, Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU).