AIMC Topic: Wrist

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Efficacy of wrist robot-aided orthopedic rehabilitation: a randomized controlled trial.

Journal of neuroengineering and rehabilitation
BACKGROUND: In recent years, many studies focused on the use of robotic devices for both the assessment and the neuro-motor reeducation of upper limb in subjects after stroke, spinal cord injuries or affected by neurological disorders. Contrarily, it...

Prediction of hand-wrist maturation stages based on cervical vertebrae images using artificial intelligence.

Orthodontics & craniofacial research
OBJECTIVE: To predict the hand-wrist maturation stages based on the cervical vertebrae (CV) images, and to analyse the accuracy of the proposed algorithms.

2D-3D reconstruction of distal forearm bone from actual X-ray images of the wrist using convolutional neural networks.

Scientific reports
The purpose of the study was to develop a deep learning network for estimating and constructing highly accurate 3D bone models directly from actual X-ray images and to verify its accuracy. The data used were 173 computed tomography (CT) images and 10...

Inter-Subject Domain Adaptation for CNN-Based Wrist Kinematics Estimation Using sEMG.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Recently, convolutional neural network (CNN) has been widely investigated to decode human intentions using surface Electromyography (sEMG) signals. However, a pre-trained CNN model usually suffers from severe degradation when testing on a new individ...

Myoelectric analysis of upper-extremity muscles during robot-assisted bilateral wrist flexion-extension in subjects with poststroke hemiplegia.

Clinical biomechanics (Bristol, Avon)
BACKGROUND: Muscle co-contraction during the execution of motor tasks or training is common in poststroke subjects. EMG-derived muscular activation indexes have been used to evaluate muscle co-contractions during movements. In addition, robot-assiste...

Critical evaluation of deep neural networks for wrist fracture detection.

Scientific reports
Wrist Fracture is the most common type of fracture with a high incidence rate. Conventional radiography (i.e. X-ray imaging) is used for wrist fracture detection routinely, but occasionally fracture delineation poses issues and an additional confirma...

A robot-aided visuomotor wrist training induces gains in proprioceptive and movement accuracy in the contralateral wrist.

Scientific reports
Proprioceptive training is a neurorehabilitation approach known to improve proprioceptive acuity and motor performance of a joint/limb system. Here, we examined if such learning transfers to the contralateral joints. Using a robotic exoskeleton, 15 h...

Hand Gesture Recognition Using Single Patchable Six-Axis Inertial Measurement Unit via Recurrent Neural Networks.

Sensors (Basel, Switzerland)
Recording human gestures from a wearable sensor produces valuable information to implement control gestures or in healthcare services. The wearable sensor is required to be small and easily worn. Advances in miniaturized sensor and materials research...

Deep CHORES: Estimating Hallmark Measures of Physical Activity Using Deep Learning.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Wrist accelerometers for assessing hallmark measures of physical activity (PA) are rapidly growing with the advent of smartwatch technology. Given the growing popularity of wrist-worn accelerometers, there needs to be a rigorous evaluation for recogn...

Automated Bone Age Assessment Using Artificial Intelligence: The Future of Bone Age Assessment.

Korean journal of radiology
Bone age assessments are a complicated and lengthy process, which are prone to inter- and intra-observer variabilities. Despite the great demand for fully automated systems, developing an accurate and robust bone age assessment solution has remained ...