String Grammar Unsupervised Possibilistic Fuzzy C-Medians for Gait Pattern Classification in Patients with Neurodegenerative Diseases.

Abstract:

:Neurodegenerative diseases that affect serious gait abnormalities include Parkinson's disease (PD), amyotrophic lateral sclerosis (ALS), and Huntington disease (HD). These diseases lead to gait rhythm distortion that can be determined by stride time interval of footfall contact times. In this paper, we present a new method for gait classification of neurodegenerative diseases. In particular, we utilize a symbolic aggregate approximation algorithm to convert left-foot stride-stride interval into a sequence of symbols using a symbolic aggregate approximation. We then find string prototypes of each class using the newly proposed string grammar unsupervised possibilistic fuzzy C-medians. Then in the testing process the fuzzy k-nearest neighbor is used. We implement the system on three 2-class problems, i.e., the classification of ALS against healthy patients, that of HD against healthy patients , and that of PD against healthy patients. The system is also implemented on one 4-class problem (the classification of ALS, HD, PD, and healthy patients altogether) called NDDs versus healthy. We found that our system yields a very good detection result. The average correct classification for ALS versus healthy is 96.88%, and that for HD versus healthy is 97.22%, whereas that for PD versus healthy is 96.43%. When the system is implemented on 4-class problem, the average accuracy is approximately 98.44%. It can provide prototypes of gait signals that are more understandable to human.

journal_name

Comput Intell Neurosci

authors

Klomsae A,Auephanwiriyakul S,Theera-Umpon N

doi

10.1155/2018/1869565

subject

Has Abstract

pub_date

2018-06-13 00:00:00

pages

1869565

eissn

1687-5265

issn

1687-5273

journal_volume

2018

pub_type

杂志文章
  • Layered Concept Lattice Model and Its Application to Build Rapidly Concept Lattice.

    abstract::When some attributes of a formal context can be decomposed into some subattributes a model of layered concept lattice to improve the efficiency of building concept lattice with complex structure attribute data is studied, the relationship between concept lattice and layered concept is discussed. Two algorithms are pro...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2020/5784209

    authors: Wu X,Zhang J,Zhong J

    更新日期:2020-06-11 00:00:00

  • Multiswarm Particle Swarm Optimization with Transfer of the Best Particle.

    abstract::We propose an improved algorithm, for a multiswarm particle swarm optimization with transfer of the best particle called BMPSO. In the proposed algorithm, we introduce parasitism into the standard particle swarm algorithm (PSO) in order to balance exploration and exploitation, as well as enhancing the capacity for glo...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2015/904713

    authors: Wei XP,Zhang JX,Zhou DS,Zhang Q

    更新日期:2015-01-01 00:00:00

  • Augmenting weak semantic cognitive maps with an "abstractness" dimension.

    abstract::The emergent consensus on dimensional models of sentiment, appraisal, emotions, and values is on the semantics of the principal dimensions, typically interpreted as valence, arousal, and dominance. The notion of weak semantic maps was introduced recently as distribution of representations in abstract spaces that are n...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2013/308176

    authors: Samsonovich AV,Ascoli GA

    更新日期:2013-01-01 00:00:00

  • SGB-ELM: An Advanced Stochastic Gradient Boosting-Based Ensemble Scheme for Extreme Learning Machine.

    abstract::A novel ensemble scheme for extreme learning machine (ELM), named Stochastic Gradient Boosting-based Extreme Learning Machine (SGB-ELM), is proposed in this paper. Instead of incorporating the stochastic gradient boosting method into ELM ensemble procedure primitively, SGB-ELM constructs a sequence of weak ELMs where ...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2018/4058403

    authors: Guo H,Wang J,Ao W,He Y

    更新日期:2018-06-26 00:00:00

  • Adaptive State Observer Design for Dynamic Links in Complex Dynamical Networks.

    abstract::The state observer for dynamic links in complex dynamical networks (CDNs) is investigated by using the adaptive method whether the networks are undirected or directed. In this paper, a complete network model is proposed, which is composed of two coupled subsystems called nodes subsystem and links subsystem, respective...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2020/8846438

    authors: Gao Z,Xiong J,Zhong J,Liu F,Liu Q

    更新日期:2020-10-21 00:00:00

  • Energy Consumption Forecasting Using Semantic-Based Genetic Programming with Local Search Optimizer.

    abstract::Energy consumption forecasting (ECF) is an important policy issue in today's economies. An accurate ECF has great benefits for electric utilities and both negative and positive errors lead to increased operating costs. The paper proposes a semantic based genetic programming framework to address the ECF problem. In par...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2015/971908

    authors: Castelli M,Trujillo L,Vanneschi L

    更新日期:2015-01-01 00:00:00

  • Neural Basis of Intrinsic Motivation: Evidence from Event-Related Potentials.

    abstract::Human intrinsic motivation is of great importance in human behavior. However, although researchers have focused on this topic for decades, its neural basis was still unclear. The current study employed event-related potentials to investigate the neural disparity between an interesting stop-watch (SW) task and a boring...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2015/698725

    authors: Jin J,Yu L,Ma Q

    更新日期:2015-01-01 00:00:00

  • Assessment of Multivariate Neural Time Series by Phase Synchrony Clustering in a Time-Frequency-Topography Representation.

    abstract::Most EEG phase synchrony measures are of bivariate nature. Those that are multivariate focus on producing global indices of the synchronization state of the system. Thus, better descriptions of spatial and temporal local interactions are still in demand. A framework for characterization of phase synchrony relationship...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2018/2406909

    authors: Porta-Garcia MA,Valdes-Cristerna R,Yanez-Suarez O

    更新日期:2018-03-21 00:00:00

  • Ensemble Framework of Deep CNNs for Diabetic Retinopathy Detection.

    abstract::Diabetic retinopathy (DR) is an eye disease that damages the blood vessels of the eye. DR causes blurred vision or it may lead to blindness if it is not detected in early stages. DR has five stages, i.e., 0 normal, 1 mild, 2 moderate, 3 severe, and 4 PDR. Conventionally, many hand-on projects of computer vision have b...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2020/8864698

    authors: Jinfeng G,Qummar S,Junming Z,Ruxian Y,Khan FG

    更新日期:2020-12-09 00:00:00

  • GA-Based Membrane Evolutionary Algorithm for Ensemble Clustering.

    abstract::Ensemble clustering can improve the generalization ability of a single clustering algorithm and generate a more robust clustering result by integrating multiple base clusterings, so it becomes the focus of current clustering research. Ensemble clustering aims at finding a consensus partition which agrees as much as po...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2017/4367342

    authors: Wang Y,Liu X,Xiang L

    更新日期:2017-01-01 00:00:00

  • Prognostics of Lithium-Ion Batteries Based on Wavelet Denoising and DE-RVM.

    abstract::Lithium-ion batteries are widely used in many electronic systems. Therefore, it is significantly important to estimate the lithium-ion battery's remaining useful life (RUL), yet very difficult. One important reason is that the measured battery capacity data are often subject to the different levels of noise pollution....

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2015/918305

    authors: Zhang C,He Y,Yuan L,Xiang S,Wang J

    更新日期:2015-01-01 00:00:00

  • Double-Criteria Active Learning for Multiclass Brain-Computer Interfaces.

    abstract::Recent technological advances have enabled researchers to collect large amounts of electroencephalography (EEG) signals in labeled and unlabeled datasets. It is expensive and time consuming to collect labeled EEG data for use in brain-computer interface (BCI) systems, however. In this paper, a novel active learning me...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2020/3287589

    authors: She Q,Chen K,Luo Z,Nguyen T,Potter T,Zhang Y

    更新日期:2020-03-10 00:00:00

  • Cloud Model-Based Artificial Immune Network for Complex Optimization Problem.

    abstract::This paper proposes an artificial immune network based on cloud model (AINet-CM) for complex function optimization problems. Three key immune operators-cloning, mutation, and suppression-are redesigned with the help of the cloud model. To be specific, an increasing half cloud-based cloning operator is used to adjust t...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2017/5901258

    authors: Wang M,Feng S,Li J,Li Z,Xue Y,Guo D

    更新日期:2017-01-01 00:00:00

  • Context Attention Heterogeneous Network Embedding.

    abstract::Network embedding (NE), which maps nodes into a low-dimensional latent Euclidean space to represent effective features of each node in the network, has obtained considerable attention in recent years. Many popular NE methods, such as DeepWalk, Node2vec, and LINE, are capable of handling homogeneous networks. However, ...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2019/8106073

    authors: Zhuo W,Zhan Q,Liu Y,Xie Z,Lu J

    更新日期:2019-08-21 00:00:00

  • Channel selection and feature projection for cognitive load estimation using ambulatory EEG.

    abstract::We present an ambulatory cognitive state classification system to assess the subject's mental load based on EEG measurements. The ambulatory cognitive state estimator is utilized in the context of a real-time augmented cognition (AugCog) system that aims to enhance the cognitive performance of a human user through com...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2007/74895

    authors: Lan T,Erdogmus D,Adami A,Mathan S,Pavel M

    更新日期:2007-01-01 00:00:00

  • Intelligence Is beyond Learning: A Context-Aware Artificial Intelligent System for Video Understanding.

    abstract::Understanding video files is a challenging task. While the current video understanding techniques rely on deep learning, the obtained results suffer from a lack of real trustful meaning. Deep learning recognizes patterns from big data, leading to deep feature abstraction, not deep understanding. Deep learning tries to...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2020/8813089

    authors: Ghozia A,Attiya G,Adly E,El-Fishawy N

    更新日期:2020-12-23 00:00:00

  • Annealing Ant Colony Optimization with Mutation Operator for Solving TSP.

    abstract::Ant Colony Optimization (ACO) has been successfully applied to solve a wide range of combinatorial optimization problems such as minimum spanning tree, traveling salesman problem, and quadratic assignment problem. Basic ACO has drawbacks of trapping into local minimum and low convergence rate. Simulated annealing (SA)...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2016/8932896

    authors: Mohsen AM

    更新日期:2016-01-01 00:00:00

  • A novel single neuron perceptron with universal approximation and XOR computation properties.

    abstract::We propose a biologically motivated brain-inspired single neuron perceptron (SNP) with universal approximation and XOR computation properties. This computational model extends the input pattern and is based on the excitatory and inhibitory learning rules inspired from neural connections in the human brain's nervous sy...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2014/746376

    authors: Lotfi E,Akbarzadeh-T MR

    更新日期:2014-01-01 00:00:00

  • Two Different Points of View through Artificial Intelligence and Vector Autoregressive Models for Ex Post and Ex Ante Forecasting.

    abstract::The ANN method has been applied by means of multilayered feedforward neural networks (MLFNs) by using different macroeconomic variables such as the exchange rate of USD/TRY, gold prices, and the Borsa Istanbul (BIST) 100 index based on monthly data over the period of January 2000 and September 2014 for Turkey. Vector ...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2015/409361

    authors: Aydin AD,Caliskan Cavdar S

    更新日期:2015-01-01 00:00:00

  • Saliency Mapping Enhanced by Structure Tensor.

    abstract::We propose a novel efficient algorithm for computing visual saliency, which is based on the computation architecture of Itti model. As one of well-known bottom-up visual saliency models, Itti method evaluates three low-level features, color, intensity, and orientation, and then generates multiscale activation maps. Fi...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2015/875735

    authors: He Z,Chen X,Sun L

    更新日期:2015-01-01 00:00:00

  • Characterization of Visual Scanning Patterns in Air Traffic Control.

    abstract::Characterization of air traffic controllers' (ATCs') visual scanning strategies is a challenging issue due to the dynamic movement of multiple aircraft and increasing complexity of scanpaths (order of eye fixations and saccades) over time. Additionally, terminologies and methods are lacking to accurately characterize ...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2016/8343842

    authors: McClung SN,Kang Z

    更新日期:2016-01-01 00:00:00

  • HDEC: A Heterogeneous Dynamic Ensemble Classifier for Binary Datasets.

    abstract::In recent years, ensemble classification methods have been widely investigated in both industry and literature in the field of machine learning and artificial intelligence. The main advantage of this approach is to benefit from a set of classifiers instead of using a single classifier with the aim of improving the pre...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2020/8826914

    authors: Ostvar N,Eftekhari Moghadam AM

    更新日期:2020-12-14 00:00:00

  • Extracting rhythmic brain activity for brain-computer interfacing through constrained independent component analysis.

    abstract::We propose a technique based on independent component analysis (ICA) with constraints, applied to the rhythmic electroencephalographic (EEG) data recorded from a brain-computer interfacing (BCI) system. ICA is a technique that can decompose the recorded EEG into its underlying independent components and in BCI involvi...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2007/41468

    authors: Wang S,James CJ

    更新日期:2007-01-01 00:00:00

  • List-Based Simulated Annealing Algorithm for Traveling Salesman Problem.

    abstract::Simulated annealing (SA) algorithm is a popular intelligent optimization algorithm which has been successfully applied in many fields. Parameters' setting is a key factor for its performance, but it is also a tedious work. To simplify parameters setting, we present a list-based simulated annealing (LBSA) algorithm to ...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2016/1712630

    authors: Zhan SH,Lin J,Zhang ZJ,Zhong YW

    更新日期:2016-01-01 00:00:00

  • Modified Mahalanobis Taguchi System for Imbalance Data Classification.

    abstract::The Mahalanobis Taguchi System (MTS) is considered one of the most promising binary classification algorithms to handle imbalance data. Unfortunately, MTS lacks a method for determining an efficient threshold for the binary classification. In this paper, a nonlinear optimization model is formulated based on minimizing...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2017/5874896

    authors: El-Banna M

    更新日期:2017-01-01 00:00:00

  • Music composition from the brain signal: representing the mental state by music.

    abstract::This paper proposes a method to translate human EEG into music, so as to represent mental state by music. The arousal levels of the brain mental state and music emotion are implicitly used as the bridge between the mind world and the music. The arousal level of the brain is based on the EEG features extracted mainly b...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2010/267671

    authors: Wu D,Li C,Yin Y,Zhou C,Yao D

    更新日期:2010-01-01 00:00:00

  • Multiclass Posterior Probability Twin SVM for Motor Imagery EEG Classification.

    abstract::Motor imagery electroencephalography is widely used in the brain-computer interface systems. Due to inherent characteristics of electroencephalography signals, accurate and real-time multiclass classification is always challenging. In order to solve this problem, a multiclass posterior probability solution for twin SV...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2015/251945

    authors: She Q,Ma Y,Meng M,Luo Z

    更新日期:2015-01-01 00:00:00

  • Study of the bus dynamic coscheduling optimization method under urban rail transit line emergency.

    abstract::As one of the most important urban commuter transportation modes, urban rail transit (URT) has been acting as a key solution for supporting mobility needs in high-density urban areas. However, in recent years, high frequency of unexpected events has caused serious service disruptions in URT system, greatly harming pas...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2014/174369

    authors: Wang Y,Yan X,Zhou Y,Wang J,Chen S

    更新日期:2014-01-01 00:00:00

  • Designs and Algorithms to Map Eye Tracking Data with Dynamic Multielement Moving Objects.

    abstract::Design concepts and algorithms were developed to address the eye tracking analysis issues that arise when (1) participants interrogate dynamic multielement objects that can overlap on the display and (2) visual angle error of the eye trackers is incapable of providing exact eye fixation coordinates. These issues were ...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2016/9354760

    authors: Kang Z,Mandal S,Crutchfield J,Millan A,McClung SN

    更新日期:2016-01-01 00:00:00

  • Deep Learning for Plant Identification in Natural Environment.

    abstract::Plant image identification has become an interdisciplinary focus in both botanical taxonomy and computer vision. The first plant image dataset collected by mobile phone in natural scene is presented, which contains 10,000 images of 100 ornamental plant species in Beijing Forestry University campus. A 26-layer deep lea...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2017/7361042

    authors: Sun Y,Liu Y,Wang G,Zhang H

    更新日期:2017-01-01 00:00:00