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Variable Admittance Control Based on Human-Robot Collaboration Observer Using Frequency Analysis for Sensitive and Safe Interaction.

Sensors (Basel, Switzerland)
A collaborative robot should be sensitive to the user intention while maintaining safe interaction during tasks such as hand guiding. Observers based on the discrete Fourier transform have been studied to distinguish between the low-frequency motion ...

A Machine Learning Processing Pipeline for Reliable Hand Gesture Classification of FMG Signals with Stochastic Variance.

Sensors (Basel, Switzerland)
ForceMyography (FMG) is an emerging competitor to surface ElectroMyography (sEMG) for hand gesture recognition. Most of the state-of-the-art research in this area explores different machine learning algorithms or feature engineering to improve hand g...

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...

Robot-assisted rehabilitation of hand function after stroke: Development of prediction models for reference to therapy.

Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology
BACKGROUND: Recovery of hand function after stroke represents the hardest target for clinicians. Robot-assisted therapy has been proved to be effective for hand recovery. Nevertheless, studies aimed to refer patients to the best therapy are missing.

EMG-Based 3D Hand Motor Intention Prediction for Information Transfer from Human to Robot.

Sensors (Basel, Switzerland)
(1) Background: Three-dimensional (3-D) hand position is one of the kinematic parameters that can be inferred from Electromyography (EMG) signals. The inferred parameter is used as a communication channel in human-robot collaboration applications. Al...

User training for machine learning controlled upper limb prostheses: a serious game approach.

Journal of neuroengineering and rehabilitation
BACKGROUND: Upper limb prosthetics with multiple degrees of freedom (DoFs) are still mostly operated through the clinical standard Direct Control scheme. Machine learning control, on the other hand, allows controlling multiple DoFs although it requir...

Performance of an artificial intelligence system for bone age assessment in Tibet.

The British journal of radiology
OBJECTIVE: To investigate whether bone age (BA) of children living in Tibet Highland could be accurately assessed using a fully automated artificial intelligence (AI) system.

Simultaneous Hand-Eye and Intrinsic Calibration of a Laser Profilometer Mounted on a Robot Arm.

Sensors (Basel, Switzerland)
A method for simultaneous laser profilometer and hand-eye calibration in relation to an industrial robot as well as its implementation is presented. In contrast to other methods, the new calibration procedure requires the measurement of only one refe...

Evaluation for Parkinsonian Bradykinesia by deep learning modeling of kinematic parameters.

Journal of neural transmission (Vienna, Austria : 1996)
A wearable sensor system is available for monitoring of bradykinesia in patients with Parkinson's disease (PD), however, it remains unclear whether kinematic parameters would reflect clinical severity of PD, or would help clinical diagnosis of physic...

A Novel Point-in-Polygon-Based sEMG Classifier for Hand Exoskeleton Systems.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
In the early 2000s, data from the latest World Health Organization estimates paint a picture where one-seventh of the world population needs at least one assistive device. Fortunately, these years are also characterized by a marked technological driv...