Hand posture detection of smartphone users using LSTM networks

Abstract

Automatic hand posture detection of smartphone users is important for adaptive user interface design, context aware application development, and activity analysis. This paper presents a method for hand posture and phone placement detection from data produced by accelerometer, magnetometer and gyroscope of a smartphone using LSTM networks. Real-time testing results indicated that LSTM network is effective in hand posture and phone placement prediction, and the proposed method outperformed existing methods by significant margins.