Sports Medicine

Prediction of HIV sensitivity to monoclonal antibodies using aminoacid sequences and deep learning.

MOTIVATION: Knowing the sensitivity of a viral strain versus a monoclonal antibody is of interest for HIV vaccine development and therapy. The HIV strains vary in their resistance to antibodies, and the accurate prediction of virus-antibody sensitivity can be used to find potent antibody combinations that broadly neutralize multiple and diverse HIV strains. Sensitivity prediction can be combined w...

Machine Learning for Acute Kidney Injury Prediction in the Intensive Care Unit.

Machine learning is the field of artificial intelligence in which computers are trained to make predictions or to identify patterns in data through complex mathematical algorithms. It has great potential in critical care to predict outcomes, such as acute kidney injury, and can be used for prognosis and to suggest management strategies. Machine learning can also be used as a research tool to advan...

Comparative analysis of machine learning algorithms on the microbial strain-specific AMP prediction.

The evolution of drug-resistant pathogenic microbial species is a major global health concern. Naturally occurring, antimicrobial peptides (AMPs) are ...

Special issue: informatics & data-driven medicine-2021.

Modern medical diagnosis, treatment, or rehabilitation problems of the patient reach completely different levels due to the rapid development of artif...

An ISB-consistent Denavit-Hartenberg model of the human upper limb for joint kinematics optimization: validation on synthetic and robot data during a typical rehabilitation gesture.

Several biomedical contexts such as diagnosis, rehabilitation, and ergonomics require an accurate estimate of human upper limbs kinematics. Wearable i...

A Lymphatic Drainage Robot for Lymphedema Rehabilitation.

Lymphedema is a medical condition that results in swelling and discomfort in human arms or legs. Caused due to the build-up of lymph fluid in the tiss...

A Pruned Deep Learning Approach for Classification of Motor Imagery Electroencephalography Signals.

The Deep Learning (DL) approach has been gaining much popularity in recent years in the development of electroencephalogram (EEG) based Motor Imagery ...

Design of a 6-DoF Cost-effective Differential-drive based Robotic system for Upper-Limb Stroke Rehabilitation.

This paper discusses the design, construction, and characteristics of a six degree of freedom (6-DoF) robotic upper limb stroke rehabilitation device....

Classification of Tonic Pain Experience based on Phase Connectivity in the Alpha Frequency Band of the Electroencephalogram using Convolutional Neural Networks.

The complexity of brain activity involved in the generation of the experience of pain makes it hard to identify neural markers able to predict pain st...

Design and development of a social assistive robot for music and game activities: a case study in a residential facility for disabled people.

Cognitive disability strongly reduces people's autonomy in performing desired as well as daily activities. The use of Social Assistive Robots (SARs) f...

Prediction of lower limb kinematics from vision-based system using deep learning approaches.

The joint angular velocity during daily life exercises is an important clinical outcome for injury risk index, rehabilitation progress monitoring and ...

Cross-Validation of Machine Learning Models for the Functional Outcome Prediction after Post-Stroke Robot-Assisted Rehabilitation.

The state of the art is still lacking an extensive analysis of which clinical characteristics are leading to better outcomes after robot-assisted reha...

Estimating Echocardiographic Myocardial Strain of Left Ventricle with Deep Learning.

The global longitudinal strain of the myocardial tissue has been shown to be a better indicator of cardiac pathologies in the subclinical stage than o...

Automatic and Personalized Adaptation of Therapy Parameters for Unsupervised Robot-Assisted Rehabilitation: a Pilot Evaluation.

Growing evidence shows that increasing the dose of upper limb therapy after stroke might improve functional outcomes and unsupervised robot-assisted t...

Mirror-Based Robotic Therapy for Ankle Recovery with a Serious Game: A Case Study with a Neurological Patient.

Neuromuscular disorders, such as foot drop, severely affect the locomotor function and walking independence after a brain injury event. Mirror-based r...

AGREE: an upper-limb robotic platform for personalized rehabilitation, concept and clinical study design.

Rehabilitation exoskeletons can supplement therapist-based training allowing post-stroke patients to perform functional, high-dosage, repetitive exerc...

Comparison of Machine Learning Techniques for Activities of Daily Living Classification with Electromyographic Data.

Advances in data science and wearable robotic devices present an opportunity to improve rehabilitation outcomes. Some of these devices incorporate ele...

Learning Dynamic Patient-Robot Task Assignment and Scheduling for A Robotic Rehabilitation Gym.

A robotic rehabilitation gym is a setup that allows multiple patients to exercise together using multiple robots. The effectiveness of training in suc...

Testing the Limit Range of Motion Safety Function of Upper Limb Rehabilitation Robots with an Anthropometrically Adjustable and Sensorized Dummy Limb.

Arm type or exoskeleton type rehabilitation robots move the patient's upper limb through one or more, either free or restrained connection points. The...

Measuring Torque Production with a Robotic Exoskeleton during Cervical Transcutaneous Spinal Stimulation.

Spinal cord injury (SCI) affects a large number of individuals in the United States. Unfortunately, traditional neurorehabilitation therapy leaves out...