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Discriminant Analysis

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[A TrAdaBoost-based method for detecting multiple subjects' P300 potentials].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
Individual differences of P300 potentials lead to that a large amount of training data must be collected to construct pattern recognition models in P300-based brain-computer interface system, which may cause subjects' fatigue and degrade the system p...

Classification of Elastic and Collagen Fibers in H&E Stained Hyperspectral Images.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
This study investigates the classification performance of elastic and collagen fibers using H&E stained hyperspectral images. As many as 1200 sample pixels were trained by using Linear discriminant analysis (LDA) and support vector machine (SVM) meth...

Comparison of Classifiers for the Transfer Learning of Affective Auditory P300-Based BCIs.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
The auditory P300-based BCI was improved by changing stimuli. However, the current method needed time for recording training data. The time can be saved by the subject-to-subject transfer learning. However, the suitable classifier for the learning re...

Tensor Discriminant Analysis for MI-EEG Signal Classification Using Convolutional Neural Network.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Motor Imagery (MI) is a typical paradigm for Brain-Computer Interface (BCI) system. In this paper, we propose a new framework by introducing a tensor-based feature representation of the data and also utilizing a convolutional neural network (CNN) arc...

Optimizing Machine Learning Methods to Improve Predictive Models of Alzheimer's Disease.

Journal of Alzheimer's disease : JAD
BACKGROUND: Predicting clinical course of cognitive decline can boost clinical trials' power and improve our clinical decision-making. Machine learning (ML) algorithms are specifically designed for the purpose of prediction; however. identifying opti...

Ensemble learning based on overlapping clusters of subjects to predict microsleep states from EEG.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Microsleeps are brief and involuntary instances of complete loss of sleep-related consciousness. We present a novel approach of creating overlapping clusters of subjects and training of an ensemble classifier to enhance the prediction of microsleep s...

A Two Stage Approach for the Automatic Detection of Insomnia.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Chronic insomnia can significantly impair an individual's quality of life leading to a high societal cost. Unfortunately, limited automated tools exist that can assist clinicians in the timely detection of insomnia. In this paper, we propose a two st...

Enhancing predictive accuracy and reproducibility in clinical evaluation research: Commentary on the special section of the Journal of Evaluation in Clinical Practice.

Journal of evaluation in clinical practice
This paper introduces a special section of the current issue of the Journal of Evaluation in Clinical Practice that includes a set of 6 empirical articles showcasing a versatile, new machine-learning statistical method, known as optimal data (or disc...

An approach to predict Sudden Cardiac Death (SCD) using time domain and bispectrum features from HRV signal.

Bio-medical materials and engineering
In this paper we present a method to predict Sudden Cardiac Arrest (SCA) with higher order spectral (HOS) and linear (Time) features extracted from heart rate variability (HRV) signal. Predicting the occurrence of SCA is important in order to avoid t...

User intent prediction with a scaled conjugate gradient trained artificial neural network for lower limb amputees using a powered prosthesis.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Powered lower limb prostheses have the ability to provide greater mobility for amputee patients. Such prostheses often have pre-programmed modes which can allow activities such as climbing stairs and descending ramps, something which many amputees st...