AIMC Topic: Upper Extremity

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Dataset with Tactile and Kinesthetic Information from a Human Forearm and Its Application to Deep Learning.

Sensors (Basel, Switzerland)
There are physical Human-Robot Interaction (pHRI) applications where the robot has to grab the human body, such as rescue or assistive robotics. Being able to precisely estimate the grasping location when grabbing a human limb is crucial to perform a...

Patient-Specific Exercises with the Development of an End-Effector Type Upper Limb Rehabilitation Robot.

Journal of healthcare engineering
End-effector type upper limb rehabilitation robots (ULRRs) are connected to patients at one distal point, making them have simple structures and less complex control algorithms, and they can avoid abnormal motion and posture of the target anatomical ...

A Mixed-Reality Tele-Operation Method for High-Level Control of a Legged-Manipulator Robot.

Sensors (Basel, Switzerland)
In recent years, legged (quadruped) robots have been subject of technological study and continuous development. These robots have a leading role in applications that require high mobility skills in complex terrain, as is the case of Search and Rescue...

Automatic extraction of upper-limb kinematic activity using deep learning-based markerless tracking during deep brain stimulation implantation for Parkinson's disease: A proof of concept study.

PloS one
Optimal placement of deep brain stimulation (DBS) therapy for treating movement disorders routinely relies on intraoperative motor testing for target determination. However, in current practice, motor testing relies on subjective interpretation and c...

Review of Learning-Based Robotic Manipulation in Cluttered Environments.

Sensors (Basel, Switzerland)
Robotic manipulation refers to how robots intelligently interact with the objects in their surroundings, such as grasping and carrying an object from one place to another. Dexterous manipulating skills enable robots to assist humans in accomplishing ...

Data-Driven Predictive Control of Exoskeleton for Hand Rehabilitation with Subspace Identification.

Sensors (Basel, Switzerland)
This study proposed a control method, a data-driven predictive control (DDPC), for the hand exoskeleton used for active, passive, and resistive rehabilitation. DDPC is a model-free approach based on past system data. One of the strengths of DDPC is t...

Detecting upper extremity native joint dislocations using deep learning: A multicenter study.

Clinical imaging
OBJECTIVE: Joint dislocations are orthopedic emergencies that require prompt intervention. Automatic identification of these injuries could help improve timely patient care because diagnostic delays increase the difficulty of reduction. In this study...

Experiences of patients who had a stroke and rehabilitation professionals with upper limb rehabilitation robots: a qualitative systematic review protocol.

BMJ open
INTRODUCTION: Emerging evidence suggests that robotic devices for upper limb rehabilitation after a stroke may improve upper limb function. For robotic upper limb rehabilitation in stroke to be successful, patients' experiences and those of the rehab...

Internet of Things (IoT) Enables Robot-Assisted Therapy as a Home Program for Training Upper Limb Functions in Chronic Stroke: A Randomized Control Crossover Study.

Archives of physical medicine and rehabilitation
OBJECTIVE: To compare the effects of using an Internet of things (IoT)-assisted tenodesis-induced-grip exoskeleton robot (TIGER) and task-specific motor training (TSMT) as home programs for the upper-limb (UL) functions of patients with chronic strok...

Human Arm Motion Prediction for Collision Avoidance in a Shared Workspace.

Sensors (Basel, Switzerland)
Industry 4.0 transforms classical industrial systems into more human-centric and digitized systems. Close human-robot collaboration is becoming more frequent, which means security and efficiency issues need to be carefully considered. In this paper, ...