AIMC Topic: Posture

Clear Filters Showing 191 to 200 of 270 articles

Robotic finger perturbation training improves finger postural steadiness and hand dexterity.

Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology
The purpose of the study was to understand the effect of robotic finger perturbation training on steadiness in finger posture and hand dexterity in healthy young adults. A mobile robotic finger training system was designed to have the functions of hi...

High-accuracy automatic classification of Parkinsonian tremor severity using machine learning method.

Physiological measurement
MOTIVATION: Although clinical aspirations for new technology to accurately measure and diagnose Parkinsonian tremors exist, automatic scoring of tremor severity using machine learning approaches has not yet been employed.

Developmental Approach for Behavior Learning Using Primitive Motion Skills.

International journal of neural systems
Imitation learning through self-exploration is essential in developing sensorimotor skills. Most developmental theories emphasize that social interactions, especially understanding of observed actions, could be first achieved through imitation, yet t...

Iterative Learning Impedance for Lower Limb Rehabilitation Robot.

Journal of healthcare engineering
This paper discusses the problem of squatting training of stroke patients. The main idea is to correct the patient's training trajectory through an iterative learning control (ILC) method. To obtain better rehabilitation effect, a patient will typica...

Assessment of pose repeatability and specimen repositioning of a robotic joint testing platform.

Medical engineering & physics
This paper describes the quantitative assessment of a robotic testing platform, consisting of an industrial robot and a universal force-moment sensor, via the design of fixtures used to hold the tibia and femur of cadaveric knees. This platform was u...

Limb Position Tolerant Pattern Recognition for Myoelectric Prosthesis Control with Adaptive Sparse Representations From Extreme Learning.

IEEE transactions on bio-medical engineering
UNLABELLED: Myoelectric signals can be used to predict the intended movements of an amputee for prosthesis control. However, untrained effects like limb position changes influence myoelectric signal characteristics, hindering the ability of pattern r...

Modifying upper-limb inter-joint coordination in healthy subjects by training with a robotic exoskeleton.

Journal of neuroengineering and rehabilitation
BACKGROUND: The possibility to modify the usually pathological patterns of coordination of the upper-limb in stroke survivors remains a central issue and an open question for neurorehabilitation. Despite robot-led physical training could potentially ...

Hemorrhagic versus ischemic stroke: Who can best benefit from blended conventional physiotherapy with robotic-assisted gait therapy?

PloS one
BACKGROUND: Contrary to common belief of clinicians that hemorrhagic stroke survivors have better functional prognoses than ischemic, recent studies show that ischemic survivors could experience similar or even better functional improvements. However...

Machine-learning-based calving prediction from activity, lying, and ruminating behaviors in dairy cattle.

Journal of dairy science
The objective of this study was to use automated activity, lying, and rumination monitors to characterize prepartum behavior and predict calving in dairy cattle. Data were collected from 20 primiparous and 33 multiparous Holstein dairy cattle from Se...

Experimental evaluation of a novel robotic hospital bed mover with omni-directional mobility.

Applied ergonomics
Bed pushing during patient transfer is one of the most physically demanding and yet common tasks in the hospital setting. Powered bed movers have been increasingly introduced to hospitals to reduce physiological strains on the users. This study intro...