Human-robot teams collaborating to achieve tasks under various conditions, especially in
unstructured, dynamic environments will require robots to adapt autonomously to a human …

Human-robot teams operate in uncertain environments to accomplish a wide range of tasks.
A dynamic under-standing of the human's workload can enable fluid interactions between …

Wearable sensor-based human activity recognition (HAR) methods hold considerable
promise for upper-level control in exoskeleton systems. However, such methods tend to …

Hand gesture recognition (HGR) has gained significant attention due to the increasing use
of AI-powered human–computer interfaces (HCIs) that can interpret the deep spatiotemporal …

Human-robot teams involve humans and robots collaborating to achieve tasks under various
environmental conditions. Successful teaming requires robots to adapt autonomously in real …

Recent advances in Biological Signal Processing (BSP) and Machine Learning (ML), in
particular, Deep Neural Networks (DNNs), have paved the way for development of …

Today, electromyography (EMG) and inertial measurement unit (IMU) readings collected
from wearable sensors see a wide variety of applications in robotic systems. These include …

This work presents a system to recognize key pinch and tripod hand grips using surface
electromyography. This system made use of sEMG signals collected from 8 subjects for …