BACKGROUND: Complex clinical gait analysis results can be expressed as single number gait deviations by applying multivariate processing methods. The original Movement Deviation Profile (MDP) quantifies the deviation of abnormal gait using the most t...
IEEE transactions on bio-medical engineering
Feb 18, 2019
The assessment of Parkinson's disease (PD) poses a significant challenge, as it is influenced by various factors that lead to a complex and fluctuating symptom manifestation. Thus, a frequent and objective PD assessment is highly valuable for effecti...
IEEE transactions on bio-medical engineering
Feb 18, 2019
In this paper, we present a deep learning framework "Rehab-Net" for effectively classifying three upper limb movements of the human arm, involving extension, flexion, and rotation of the forearm, which, over the time, could provide a measure of rehab...
The goal of this study was to develop and validate a non-invasive approach to estimate scapular kinematics in individual patients. We hypothesized that machine learning algorithms could be developed using motion capture data to accurately estimate dy...
Head motion (HM) during fMRI acquisition can significantly affect measures of brain activity or connectivity even after correction with preprocessing methods. Moreover, any systematic relationship between HM and variables of interest can introduce sy...
Currently, effective crowd management based on the information provided by crowd monitoring systems is difficult as this information comes in at the moment adverse crowd movements are already occurring. Up to this moment, very little forecasting tech...
Journal of neuroengineering and rehabilitation
Jan 16, 2019
BACKGROUND: Pattern recognition technology allows for more intuitive control of myoelectric prostheses. However, the need to collect electromyographic data to initially train the pattern recognition system, and to re-train it during prosthesis use, a...
Realization of navigation in virtual environments remains a challenge as it involves complex operating conditions. Decomposition of such complexity is attainable by fusion of sensors and machine learning techniques. Identifying the right combination ...
Non-invasive, electroencephalography (EEG)-based brain-computer interfaces (BCIs) on motor imagery movements translate the subject's motor intention into control signals through classifying the EEG patterns caused by different imagination tasks, e.g....