AIMC Topic: Signal Processing, Computer-Assisted

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Improved Transductive Support Vector Machine for a Small Labelled Set in Motor Imagery-Based Brain-Computer Interface.

Computational intelligence and neuroscience Nov 25, 2019
Long and tedious calibration time hinders the development of motor imagery- (MI-) based brain-computer interface (BCI). To tackle this problem, we use a limited labelled set and a relatively large unlabelled set from the same subject for training bas...
Foot Models, Theoretical Hand Support Vector Machine Motor Activity Tongue Electroencephalography Imagination Calibration Signal Processing, Computer-Assisted Brain-Computer Interfaces Humans Brain Time Factors
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Non-Invasive Estimation of Hemoglobin Using a Multi-Model Stacking Regressor.

IEEE journal of biomedical and health informatics Nov 20, 2019
OBJECTIVE: We describe a novel machine-learning based method to estimate total Hemoglobin (Hb) using photoplethysmograms (PPGs) acquired non-invasively.
Adolescent India Photoplethysmography Equipment Design Signal Processing, Computer-Assisted Hemoglobins Machine Learning Female Algorithms Young Adult Pregnancy Adult Middle Aged Humans
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Artificial Intelligence Techniques for Automated Diagnosis of Neurological Disorders.

European neurology Nov 19, 2019
BACKGROUND: Authors have been advocating the research ideology that a computer-aided diagnosis (CAD) system trained using lots of patient data and physiological signals and images based on adroit integration of advanced signal processing and artifici...
Artificial Intelligence Diagnosis, Computer-Assisted Signal Processing, Computer-Assisted Central Nervous System Diseases Humans
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An incremental learning system for atrial fibrillation detection based on transfer learning and active learning.

Computer methods and programs in biomedicine Nov 14, 2019
BACKGROUND AND OBJECTIVE: Atrial fibrillation (AF) is a type of arrhythmia with high incidence. Automatic AF detection methods have been studied in previous works. However, a model cannot be used all the time without any improvement. And updating mod...
Algorithms Databases, Factual Diagnosis, Computer-Assisted Electrocardiography Signal Processing, Computer-Assisted Humans Atrial Fibrillation Neural Networks, Computer Cardiology Machine Learning Software
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Signal identification system for developing rehabilitative device using deep learning algorithms.

Artificial intelligence in medicine Nov 8, 2019
Paralyzed patients were increasing day by day. Some of the neurodegenerative diseases like amyotrophic lateral sclerosis, Brainstem Leison, Stupor and Muscular dystrophy affect the muscle movements in the body. The affected persons were unable to mig...
Male Aging Deep Learning Eye Movements Equipment Design Signal Processing, Computer-Assisted Female Brain-Computer Interfaces Electrodes Reproducibility of Results Humans Electrooculography Healthy Volunteers Young Adult Self-Help Devices Algorithms Adult Rehabilitation
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Feasibility of a Sensor-Based Gait Event Detection Algorithm for Triggering Functional Electrical Stimulation during Robot-Assisted Gait Training.

Sensors (Basel, Switzerland) Nov 5, 2019
Technologies such as robot-assisted gait trainers or functional electrical stimulation can improve the rehabilitation process of people affected with gait disorders due to stroke or other neurological defects. By combining both technologies, the pote...
Humans Algorithms Adult Male Robotics Electrodes Signal Processing, Computer-Assisted Acceleration Gait Foot Feasibility Studies Electric Stimulation
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Predicting individual decision-making responses based on single-trial EEG.

NeuroImage Nov 4, 2019
Decision-making plays an essential role in the interpersonal interactions and cognitive processing of individuals. There has been increasing interest in being able to predict an individual's decision-making response (i.e., acceptance or rejection). W...
Signal Processing, Computer-Assisted Brain Supervised Machine Learning Female Neural Pathways Humans Young Adult Male Evoked Potentials Adult Decision Making Discriminant Analysis Electroencephalography
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Machine learning to predict 30-day quality-adjusted survival in critically ill patients with cancer.

Journal of critical care Nov 2, 2019
PURPOSE: To develop and compare the predictive performance of machine-learning algorithms to estimate the risk of quality-adjusted life year (QALY) lower than or equal to 30 days (30-day QALY).
Intensive Care Units Female Hospitalization Aged Algorithms Prospective Studies Prognosis Critical Illness Brazil Neoplasms Quality of Life ROC Curve Adult Sensitivity and Specificity Male Middle Aged Humans Machine Learning Pattern Recognition, Automated Decision Trees False Positive Reactions Area Under Curve Hospitals, Public Signal Processing, Computer-Assisted Probability
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A Multi-Column CNN Model for Emotion Recognition from EEG Signals.

Sensors (Basel, Switzerland) Oct 31, 2019
We present a multi-column CNN-based model for emotion recognition from EEG signals. Recently, a deep neural network is widely employed for extracting features and recognizing emotions from various biosignals including EEG signals. A decision from a s...
Electroencephalography Signal Processing, Computer-Assisted Arousal Facial Recognition Humans Neural Networks, Computer Algorithms Emotions
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Special Issue "Advanced Signal Processing in Intelligent Systems for Health Monitoring".

Sensors (Basel, Switzerland) Oct 31, 2019
Recently, significant developments have been achieved in the field of artificial intelligence, in particular the introduction of deep learning technology that has improved the learning and prediction accuracy to unpresented levels, especially when de...
Artificial Intelligence Algorithms Deep Learning Monitoring, Physiologic Signal Processing, Computer-Assisted
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