This article describes the use of neural networks to develop a system for recognizing human activities, such as walking, climbing stairs, descending stairs, among others, using data captured by smartphone sensors such as gyroscopes and accelerometers. Various neural networks were implemented and compared to evaluate their effectiveness. The results indicate good performance across all neural networks, with the LSTM network achieving an accuracy of nearly 95%. This demonstrates the ability of neural networks to predict human movements.