Feature extraction and feature selection in smartphone-based activity recognition

Nowadays, smartphones are gradually being integrated in our daily lives, and they can be considered powerful tools for monitoring human activities. However, due to the limitations of processing capability and energy consumption of smartphones compared to standard machines, a trade-off between performance and computational complexity must be considered when developing smartphone-based systems. In this paper, we shed light on the importance of feature selection and its impact on simplifying the activity classification process which enhances the computational complexity of the system. Through an in-depth survey on the features that are widely used in state-of-the-art studies, we selected the most common features for sensor-based activity classification, namely conventional features. Then, in an experimental study with 10 participants and using 2 different smartphones, we investigated how to reduce system complexity while maintaining classification performance by replacing the conventional feature set with an optimal set. For this reason, in the considered scenario, the users were instructed to perform different static and dynamic activities, while freely holding a smartphone in their hands. In our comparison to the state-of-the-art approaches, we implemented and evaluated major classification algorithms, including the decision tree and Bayesian network. We demonstrated that replacing the conventional feature set with an optimal set can significantly reduce the complexity of the activity recognition system with only a negligible impact on the overall system performance

An IMU and RFID-based navigation system providing vibrotactile feedback for visually impaired people

This paper presents the DOVI (Device for Orientation of the Visually Impaired) system, a new inertial and RFID-based wearable navigation device for indoor environments providing vibrotactile feedback to visually impaired people for reaching a target place. The DOVI system is based on sensor fusion techniques, allowing a precise and global localization of the pedestrian thanks to inertial measurements from accelerometers and gyroscope and passive RFID tags. The pedestrian is provided a haptic feedback through a vibrotactile bracelet, that can guide him/her through the correct path toward the target. The DOVI system is complementary to both those systems allowing the detection of mobile obstacles along the path and to other aids, such as the white cane or the guide dog