AIMC Topic: Motor Activity

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Activity-aware essential tremor evaluation using deep learning method based on acceleration data.

Parkinsonism & related disorders
BACKGROUND: Essential tremor (ET), one of the most common neurological disorders is typically evaluated with validated rating scales which only provide a subjective assessment during a clinical visit, underestimating the fluctuations tremor during di...

Self-Efficacy, Poststroke Depression, and Rehabilitation Outcomes: Is There a Correlation?

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
BACKGROUND: The sudden live changes of stroke survivors may lead to negative psychological and behavioral outcomes, including anxiety and depressive mood, which may compromise the rehabilitation process. Some personality features, such as self-effica...

Predicting Motor and Cognitive Improvement Through Machine Learning Algorithm in Human Subject that Underwent a Rehabilitation Treatment in the Early Stage of Stroke.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
BACKGROUND: The objective of this study was to investigate, in subject with stroke, the exact role as prognostic factor of common inflammatory biomarkers and other markers in predicting motor and/or cognitive improvement after rehabilitation treatmen...

Reliability, validity and discriminant ability of the instrumental indices provided by a novel planar robotic device for upper limb rehabilitation.

Journal of neuroengineering and rehabilitation
BACKGROUND: In the last few years, there has been an increasing interest in the use of robotic devices to objectively quantify motor performance of patients after brain damage. Although these robot-derived measures can potentially add meaningful info...

A fresh look at functional link neural network for motor imagery-based brain-computer interface.

Journal of neuroscience methods
BACKGROUND: Artificial neural networks (ANNs) are one of the widely used classifiers in the brain-computer interface (BCI) systems-based on noninvasive electroencephalography (EEG) signals. Among the different ANN architectures, the most commonly app...

Resting-state functional connectivity predicts the ability to adapt arm reaching in a robot-mediated force field.

NeuroImage
Motor deficits are common outcomes of neurological conditions such as stroke. In order to design personalised motor rehabilitation programmes such as robot-assisted therapy, it would be advantageous to predict how a patient might respond to such trea...

Using echo state networks for classification: A case study in Parkinson's disease diagnosis.

Artificial intelligence in medicine
Despite having notable advantages over established machine learning methods for time series analysis, reservoir computing methods, such as echo state networks (ESNs), have yet to be widely used for practical data mining applications. In this paper, w...

Sustained sensorimotor control as intermittent decisions about prediction errors: computational framework and application to ground vehicle steering.

Biological cybernetics
A conceptual and computational framework is proposed for modelling of human sensorimotor control and is exemplified for the sensorimotor task of steering a car. The framework emphasises control intermittency and extends on existing models by suggesti...

Real-Time Human Detection for Aerial Captured Video Sequences via Deep Models.

Computational intelligence and neuroscience
Human detection in videos plays an important role in various real life applications. Most of traditional approaches depend on utilizing handcrafted features which are problem-dependent and optimal for specific tasks. Moreover, they are highly suscept...

Effect of a robotic seal on the motor activity and sleep patterns of older people with dementia, as measured by wearable technology: A cluster-randomised controlled trial.

Maturitas
OBJECTIVES: The robotic seal, PARO, has been used as an alternative to animal-assisted therapies with residents with dementia in long-term care, yet understanding of its efficacy is limited by a paucity of research. We explored the effects of PARO on...