Wearable sensors and systems have become increasingly popular in recent years. Two
prominent wearable technologies for human activity monitoring are smart textile systems …

Most post-stroke patients experience varying degrees of impairment in upper limb function
and fine motor skills. Occupational therapy (OT) with other rehabilitation trainings is …

To obtain accurate position information, herein, a one-assistant method involving the fusion
of extreme learning machine (ELM)/finite impulse response (FIR) filters and vision data is …

In this letter, we propose a new approach for human motion reconstruction based on
Gaussian Mixture Probability Hypothesis Density (GM-PHD) Filter applied to human joint …

Human activity detection has evolved due to the advances and developments of machine
learning techniques, which have enabled solutions to new challenges without ignoring …

Multi-person motion prediction is a challenging task, especially for real-world scenarios of
highly interacted persons. Most previous works have been devoted to studying the case of …

Robots traditionally have a wide array of sensors that allow them to react to the environment
and make appropriate decisions. These sensors can give incorrect or imprecise data due to …

Robots have to be able to function in a multitude of different situations and environments. To
help them achieve this, they are usually equipped with a large set of sensors whose data will …

Abstract Activities of Daily Living (ADL's) are the activities that people perform every day in
their home as part of their typical routine. The in-home, automated monitoring of ADL's has …

Many Human Activity Recognition (HAR) research works have been engineered, however,
only a few studies combine Kinect and the smartphone. Also, most findings are geared …