AIMC Journal:
Medical & biological engineering & computing

Showing 321 to 330 of 330 articles

An automatic method for arterial pulse waveform recognition using KNN and SVM classifiers.

Medical & biological engineering & computing
The measurement and analysis of the arterial pulse waveform (APW) are the means for cardiovascular risk assessment. Optical sensors represent an attractive instrumental solution to APW assessment due to their truly non-contact nature that makes the m...

Hierarchical multi-class SVM with ELM kernel for epileptic EEG signal classification.

Medical & biological engineering & computing
In this paper, a novel hierarchical multi-class SVM (H-MSVM) with extreme learning machine (ELM) as kernel is proposed to classify electroencephalogram (EEG) signals for epileptic seizure detection. A clinical EEG benchmark dataset having five classe...

Identifying relevant group of miRNAs in cancer using fuzzy mutual information.

Medical & biological engineering & computing
MicroRNAs (miRNAs) act as a major biomarker of cancer. All miRNAs in human body are not equally important for cancer identification. We propose a methodology, called FMIMS, which automatically selects the most relevant miRNAs for a particular type of...

Classification of diabetes maculopathy images using data-adaptive neuro-fuzzy inference classifier.

Medical & biological engineering & computing
Prolonged diabetes retinopathy leads to diabetes maculopathy, which causes gradual and irreversible loss of vision. It is important for physicians to have a decision system that detects the early symptoms of the disease. This can be achieved by build...

RAIRS2 a new expert system for diagnosing tuberculosis with real-world tournament selection mechanism inside artificial immune recognition system.

Medical & biological engineering & computing
Tuberculosis is a major global health problem that has been ranked as the second leading cause of death from an infectious disease worldwide, after the human immunodeficiency virus. Diagnosis based on cultured specimens is the reference standard; how...

Comparative assessment of glucose prediction models for patients with type 1 diabetes mellitus applying sensors for glucose and physical activity monitoring.

Medical & biological engineering & computing
The present work presents the comparative assessment of four glucose prediction models for patients with type 1 diabetes mellitus (T1DM) using data from sensors monitoring blood glucose concentration. The four models are based on a feedforward neural...

Prediction of drug-induced eosinophilia adverse effect by using SVM and naïve Bayesian approaches.

Medical & biological engineering & computing
Drug-induced eosinophilia is a potentially life-threatening adverse effect; clinical manifestations, eosinophilia-myalgia syndrome, mainly include severe skin eruption, fever, hematologic abnormalities, and organ system dysfunction. Using experimenta...

Upper-limb kinematic reconstruction during stroke robot-aided therapy.

Medical & biological engineering & computing
The paper proposes a novel method for an accurate and unobtrusive reconstruction of the upper-limb kinematics of stroke patients during robot-aided rehabilitation tasks with end-effector machines. The method is based on a robust analytic procedure fo...

Support vector machine and fuzzy C-mean clustering-based comparative evaluation of changes in motor cortex electroencephalogram under chronic alcoholism.

Medical & biological engineering & computing
In this study, the magnitude and spatial distribution of frequency spectrum in the resting electroencephalogram (EEG) were examined to address the problem of detecting alcoholism in the cerebral motor cortex. The EEG signals were recorded from chroni...

A robust method for online heart sound localization in respiratory sound based on temporal fuzzy c-means.

Medical & biological engineering & computing
This work presents a detailed framework to detect the location of heart sound within the respiratory sound based on temporal fuzzy c-means (TFCM) algorithm. In the proposed method, respiratory sound is first divided into frames and for each frame, th...