Personal and ubiquitous sensing technologies such as smartphones have allowed the
continuous collection of data in an unobtrusive manner. Machine learning methods have …

Emotions play an important role in the learning process. Considering the learner's emotions
is essential for electronic learning (e-learning) systems. Some researchers have proposed …

We introduce hand movement, orientation, and grasp (HMOG), a set of behavioral features
to continuously authenticate smartphone users. HMOG features unobtrusively capture subtle …

Deep learning greatly empowers Inertial Measurement Unit (IMU) sensors for various mobile
sensing applications, including human activity recognition, human-computer interaction …

Every person is unique, with individual behavioural characteristics: how one moves,
coordinates, and uses their body. In this paper we investigate body motion as behavioural …

The increasing use of smartphones as personal computing platforms to access personal
information has stressed the demand for secure and usable authentication techniques, and …

Mobile devices have brought a great convenience to us these years, which allow the users
to enjoy the anytime and anywhere various applications such as the online shop** …

Currently, ECG-based authentication is considered highly promising in terms of user
identification for smart healthcare systems because of its inimitability, suitability, accessibility …

We present a large-scale study exploring the capability of temporal deep neural networks to
interpret natural human kinematics and introduce the first method for active biometric …

The growing popularity of wearable devices is leading to new ways to interact with the
environment, with other smart devices, and with other people. Wearables equipped with an …