AIMC Topic: Adult

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Adaptive hybrid robotic system for rehabilitation of reaching movement after a brain injury: a usability study.

Journal of neuroengineering and rehabilitation
BACKGROUND: Brain injury survivors often present upper-limb motor impairment affecting the execution of functional activities such as reaching. A currently active research line seeking to maximize upper-limb motor recovery after a brain injury, deals...

Development of A Machine Learning Algorithm to Classify Drugs Of Unknown Fetal Effect.

Scientific reports
Many drugs commonly prescribed during pregnancy lack a fetal safety recommendation - called FDA 'category C' drugs. This study aims to classify these drugs into harmful and safe categories using knowledge gained from chemoinformatics (i.e., pharmacol...

Early hospital mortality prediction of intensive care unit patients using an ensemble learning approach.

International journal of medical informatics
BACKGROUND: Mortality prediction of hospitalized patients is an important problem. Over the past few decades, several severity scoring systems and machine learning mortality prediction models have been developed for predicting hospital mortality. By ...

The effectiveness of robotic training depends on motor task characteristics.

Experimental brain research
Previous research suggests that the effectiveness of robotic training depends on the motor task to be learned. However, it is still an open question which specific task's characteristics influence the efficacy of error-modulating training strategies....

Tele-Manipulation with Two Asymmetric Slaves: Two Operators Perform Better Than One.

IEEE transactions on haptics
Certain tele-manipulation tasks require manipulation by two asymmetric slaves, for example, a crane for hoisting and a dexterous robotic arm for fine manipulation. It is unclear how to best design human-in-the-loop control over two asymmetric slaves....

Using Temporal Sensitivity to Predict Performance Under Latency in Teleoperation.

Human factors
Objective This article establishes a relationship between temporal sensitivity and task performance under one-way latency between input and response. Background As the latency between human input and telerobot response increases, performance (e.g., s...

Real-Time Non-Invasive Detection and Classification of Diabetes Using Modified Convolution Neural Network.

IEEE journal of biomedical and health informatics
Non-invasive diabetes prediction has been gaining prominence over the last decade. Among many human serums evaluated, human breath emerges as a promising option with acetone levels in breath exhibiting a good correlation to blood glucose levels. Such...

Diffusion parameter mapping with the combined intravoxel incoherent motion and kurtosis model using artificial neural networks at 3 T.

NMR in biomedicine
Artificial neural networks (ANNs) were used for voxel-wise parameter estimation with the combined intravoxel incoherent motion (IVIM) and kurtosis model facilitating robust diffusion parameter mapping in the human brain. The proposed ANN approach was...

A finite element-based machine learning approach for modeling the mechanical behavior of the breast tissues under compression in real-time.

Computers in biology and medicine
This work presents a data-driven method to simulate, in real-time, the biomechanical behavior of the breast tissues in some image-guided interventions such as biopsies or radiotherapy dose delivery as well as to speed up multimodal registration algor...

Hand Passive Mobilization Performed with Robotic Assistance: Acute Effects on Upper Limb Perfusion and Spasticity in Stroke Survivors.

BioMed research international
This single arm pre-post study aimed at evaluating the acute effects induced by a single session of robot-assisted passive hand mobilization on local perfusion and upper limb (UL) function in poststroke hemiparetic participants. Twenty-three patients...