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 …

Sensor-based activity recognition seeks the profound high-level knowledge about human
activities from multitudes of low-level sensor readings. Conventional pattern recognition …

We performed an electronic database search of published works from 2012 to mid-2021 that
focus on human gait studies and apply machine learning techniques. We identified six key …

Real-world deployments of accelerometer-based human activity recognition systems need
to be carefully configured regarding the sampling rate used for measuring acceleration …

Training skillful and competent surgeons is critical to ensure high quality of care and to
minimize disparities in access to effective care. Traditional models to train surgeons are …

By leveraging advances in deep learning, challenging pattern recognition problems have
been solved in computer vision, speech recognition, natural language processing, and …

BackgroundLate-life depression (LLD) is associated with a decline in physical activity.
Typically this is assessed by self-report questionnaires and, more recently, with actigraphy …

Accelerometer-based (and by extension other inertial sensors) research for Human Activity
Recognition (HAR) is a dead-end. This sensor does not offer enough information for us to …

With the pervasive use of smartphones, which contain numerous sensors, data for modeling
human activity is readily available. Human activity recognition is an important area of …

The World Health Organization promotes healthy living through regular physical activities,
such as exercise and sports, as well as access to healthcare and rehabilitation services for …