AIMC Topic: Movement
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EMG-Based 3D Hand Motor Intention Prediction for Information Transfer from Human to Robot.
Sensors (Basel, Switzerland)
Feb 12, 2021
(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...
GroupRegNet: a groupwise one-shot deep learning-based 4D image registration method.
Physics in medicine and biology
Feb 12, 2021
Accurate deformable four-dimensional (4D) (three-dimensional in space and time) medical images registration is essential in a variety of medical applications. Deep learning-based methods have recently gained popularity in this area for the significan...
Application of machine learning to the identification of joint degrees of freedom involved in abnormal movement during upper limb prosthesis use.
PloS one
Feb 11, 2021
To evaluate movement quality of upper limb (UL) prosthesis users, performance-based outcome measures have been developed that examine the normalcy of movement as compared to a person with a sound, intact hand. However, the broad definition of "normal...
Multitask Non-Autoregressive Model for Human Motion Prediction.
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Feb 5, 2021
Human motion prediction, which aims at predicting future human skeletons given the past ones, is a typical sequence-to-sequence problem. Therefore, extensive efforts have been devoted to exploring different RNN-based encoder-decoder architectures. Ho...
Deep Representation-Based Domain Adaptation for Nonstationary EEG Classification.
IEEE transactions on neural networks and learning systems
Feb 4, 2021
In the context of motor imagery, electroencephalography (EEG) data vary from subject to subject such that the performance of a classifier trained on data of multiple subjects from a specific domain typically degrades when applied to a different subje...
Head motion classification using thread-based sensor and machine learning algorithm.
Scientific reports
Jan 29, 2021
Human machine interfaces that can track head motion will result in advances in physical rehabilitation, improved augmented reality/virtual reality systems, and aid in the study of human behavior. This paper presents a head position monitoring and cla...
Accurate prediction of clinical stroke scales and improved biomarkers of motor impairment from robotic measurements.
PloS one
Jan 29, 2021
OBJECTIVE: One of the greatest challenges in clinical trial design is dealing with the subjectivity and variability introduced by human raters when measuring clinical end-points. We hypothesized that robotic measures that capture the kinematics of hu...
Evaluation for Parkinsonian Bradykinesia by deep learning modeling of kinematic parameters.
Journal of neural transmission (Vienna, Austria : 1996)
Jan 28, 2021
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...
Body Temperature-Triggered Mechanical Instabilities for High-Speed Soft Robots.
Soft robotics
Jan 27, 2021
Nature offers bionic inspirations for elegant applications of mechanical principles such as the concept of snap buckling, which occurs in several plants. Exploiting mechanical instabilities is the key to fast movement here. We use the snap-through an...
The accuracy and predictability of micro Doppler radar signature projection algorithm measuring functional movement in NCAA athletes.
Gait & posture
Jan 26, 2021
BACKGROUND: Development of accessible cost-effective technology to objectively, reliably, and accurately predict musculoskeletal injury risk could aid the effort to prevent chronic pain and disability. Recent work on micro-Doppler radar suggests it m...
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