AIMC Topic: Upper Extremity

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LSTM-AE for Domain Shift Quantification in Cross-Day Upper-Limb Motion Estimation Using Surface Electromyography.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Although deep learning (DL) techniques have been extensively researched in upper-limb myoelectric control, system robustness in cross-day applications is still very limited. This is largely caused by non-stable and time-varying properties of surface ...

Development of a program to determine optimal settings for robot-assisted rehabilitation of the post-stroke paretic upper extremity: a simulation study.

Scientific reports
Robot-assisted therapy can effectively treat upper extremity (UE) paralysis in patients who experience a stroke. Presently, UE, as a training item, is selected according to the severity of the paralysis based on a clinician's experience. The possibil...

VLAD: Task-agnostic VAE-based lifelong anomaly detection.

Neural networks : the official journal of the International Neural Network Society
Lifelong learning represents an emerging machine learning paradigm that aims at designing new methods providing accurate analyses in complex and dynamic real-world environments. Although a significant amount of research has been conducted in image cl...

Will Your Next Therapist Be a Robot?-A Review of the Advancements in Robotic Upper Extremity Rehabilitation.

Sensors (Basel, Switzerland)
Several recent studies have indicated that upper extremity injuries are classified as a top common workplace injury. Therefore, upper extremity rehabilitation has become a leading research area in the last few decades. However, this high number of up...

A comparison of point-tracking algorithms in ultrasound videos from the upper limb.

Biomedical engineering online
Tracking points in ultrasound (US) videos can be especially useful to characterize tissues in motion. Tracking algorithms that analyze successive video frames, such as variations of Optical Flow and Lucas-Kanade (LK), exploit frame-to-frame temporal ...

Model-Predictive Control for Omnidirectional Mobile Robots in Logistic Environments Based on Object Detection Using CNNs.

Sensors (Basel, Switzerland)
Object detection is an essential component of autonomous mobile robotic systems, enabling robots to understand and interact with the environment. Object detection and recognition have made significant progress using convolutional neural networks (CNN...

Impairments of the arm and hand are highly correlated during subacute stroke.

Journal of rehabilitation medicine
BACKGROUND: The classical description of poststroke upper limb impairment follows a proximalto-distal impairment gradient. Previous studies are equivocal on whether the hand is more impaired than the arm.

Soft Robotics Enables Neuroprosthetic Hand Design.

ACS nano
Development and implementation of neuroprosthetic hands is a multidisciplinary field at the interface between humans and artificial robotic systems, which aims at replacing the sensorimotor function of the upper-limb amputees as their own. Although p...

A Deep Q-Network based hand gesture recognition system for control of robotic platforms.

Scientific reports
Hand gesture recognition (HGR) based on electromyography signals (EMGs) and inertial measurement unit signals (IMUs) has been investigated for human-machine applications in the last few years. The information obtained from the HGR systems has the pot...

Motor differences in autism during a human-robot imitative gesturing task.

Clinical biomechanics (Bristol, Avon)
BACKGROUND: Difficulty with imitative gesturing is frequently observed as a clinical feature of autism. Current practices for assessment of imitative gesturing ability-behavioral observation and parent report-do not allow precise measurement of speci...