Human activity recognition (HAR) has multifaceted applications due to its worldly usage of
acquisition devices such as smartphones, video cameras, and its ability to capture human …

Human Activity Recognition (HAR) is a field that infers human activities from raw time-series
signals acquired through embedded sensors of smartphones and wearable devices. It has …

Computing devices that can recognize various human activities or movements can be used
to assist people in healthcare, sports, or human–robot interaction. Readily available data for …

Motion or inertial sensors such as gyroscope and accelerometer commonly found in
smartwatches and smartphones can measure characteristics such as acceleration and …

Decoding human activity accurately from wearable sensors can aid in applications related to
healthcare and context awareness. The present approaches in this domain use recurrent …

Smartphones as ubiquitous gadgets are rapidly becoming more intelligent and context-
aware as sensing, networking, and processing capabilities advance. These devices provide …

Sensor-based human activity recognition (S-HAR) has become an important and high-
impact topic of research within human-centered computing. In the last decade, successful …

Smart mobile devices are being widely used to identify and track human behaviors in simple
and complex daily activities. The evolution of wearable sensing technologies pertaining to …

Wearable technology has advanced significantly and is now used in various entertainment
and business contexts. Authentication methods could be trustworthy, transparent, and non …

Gait analysis has traditionally relied on laborious and lab-based methods. Data from
wearable sensors, such as Inertial Measurement Units (IMU), can be analyzed with machine …