This paper firstly introduces common wearable sensors, smart wearable devices and the key
application areas. Since multi-sensor is defined by the presence of more than one model or …

Mobile and wearable devices have enabled numerous applications, including activity
tracking, wellness monitoring, and human–computer interaction, that measure and improve …

In recent times, deep artificial neural networks have achieved many successes in pattern
recognition. Part of this success can be attributed to the reliance on big data to increase …

Deep learning performs remarkably well on many time series analysis tasks recently. The
superior performance of deep neural networks relies heavily on a large number of training …

To understand human behavior and intrinsically anticipate human intentions, research into
human activity recognition HAR) using sensors in wearable and handheld devices has …

In the last decade, Human Activity Recognition (HAR) has become a vibrant research area,
especially due to the spread of electronic devices such as smartphones, smartwatches and …

In next-generation network architecture, the Cybertwin drove the sixth generation of cellular
networks sixth-generation (6G) to play an active role in many applications, such as …

Advances in deep learning (DL) model design have pushed the boundaries of the areas in
which it can be applied. The fields with an immense availability of complex big data have …

Gait assessment is an essential tool for clinical applications not only to diagnose different
neurological conditions but also to monitor disease progression as it contributes to the …

Photoplethysmography (PPG) is an affordable and straightforward optical technique used to
detect changes in blood volume within tissue microvascular beds. PPG technology has …