List of Publications
There are numbers of autism related research can be found in Malaysia that generally focus on the ASD, learning disorder, communication aids, therapy and many more. The list of publications is provided below:
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2018 |
Hariharan, M; Sindhu, R; Vijean, V; Yazid, H; Nadarajaw, T; Yaacob, S; Polat, K Improved binary dragonfly optimization algorithm and wavelet packet based non-linear features for infant cry classification Journal Article Computer Methods and Programs in Biomedicine, 155 , pp. 39-51, 2018, ISSN: 01692607, (cited By 21). Abstract | Links | BibTeX | Tags: Accidents, Algorithms, Article, Artificial Neural Network, Asphyxia, Binary Dragonfly Optimization Aalgorithm, Classification (of information), Classification Algorithm, Classifier, Coding, Computer-Assisted, Constants and Coefficients, Crying, Database Systems, Databases, Deafness, Diagnosis, Energy, Entropy, Extraction, Extreme Learning Machine, Factual, Factual Database, Feature Extraction, Feature Selection Methods, Fuzzy System, Hearing Impairment, Human, Hunger, Infant, Infant Cry, Infant Cry Classifications, Jaundice, Kernel Method, Learning, Linear Predictive Coding, Machine Learning, Mathematical Transformations, Mel Frequency Cepstral Coefficient, Mel Frequency Cepstral Coefficients, Multi-Class Classification, Neural Networks, Nonlinear Dynamics, Nonlinear System, Optimization, Pain, Pathophysiology, Prematurity, Reproducibility, Reproducibility of Results, Signal Processing, Speech Recognition, Wavelet Analysis, Wavelet Packet, Wavelet Packet Transforms @article{Hariharan201839, title = {Improved binary dragonfly optimization algorithm and wavelet packet based non-linear features for infant cry classification}, author = {M Hariharan and R Sindhu and V Vijean and H Yazid and T Nadarajaw and S Yaacob and K Polat}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85036611215&doi=10.1016%2fj.cmpb.2017.11.021&partnerID=40&md5=1f3b17817b00f07cadad6eb61c0f4bf9}, doi = {10.1016/j.cmpb.2017.11.021}, issn = {01692607}, year = {2018}, date = {2018-01-01}, journal = {Computer Methods and Programs in Biomedicine}, volume = {155}, pages = {39-51}, publisher = {Elsevier Ireland Ltd}, abstract = {Background and objective Infant cry signal carries several levels of information about the reason for crying (hunger, pain, sleepiness and discomfort) or the pathological status (asphyxia, deaf, jaundice, premature condition and autism, etc.) of an infant and therefore suited for early diagnosis. In this work, combination of wavelet packet based features and Improved Binary Dragonfly Optimization based feature selection method was proposed to classify the different types of infant cry signals. Methods Cry signals from 2 different databases were utilized. First database contains 507 cry samples of normal (N), 340 cry samples of asphyxia (A), 879 cry samples of deaf (D), 350 cry samples of hungry (H) and 192 cry samples of pain (P). Second database contains 513 cry samples of jaundice (J), 531 samples of premature (Prem) and 45 samples of normal (N). Wavelet packet transform based energy and non-linear entropies (496 features), Linear Predictive Coding (LPC) based cepstral features (56 features), Mel-frequency Cepstral Coefficients (MFCCs) were extracted (16 features). The combined feature set consists of 568 features. To overcome the curse of dimensionality issue, improved binary dragonfly optimization algorithm (IBDFO) was proposed to select the most salient attributes or features. Finally, Extreme Learning Machine (ELM) kernel classifier was used to classify the different types of infant cry signals using all the features and highly informative features as well. Results Several experiments of two-class and multi-class classification of cry signals were conducted. In binary or two-class experiments, maximum accuracy of 90.18% for H Vs P, 100% for A Vs N, 100% for D Vs N and 97.61% J Vs Prem was achieved using the features selected (only 204 features out of 568) by IBDFO. For the classification of multiple cry signals (multi-class problem), the selected features could differentiate between three classes (N, A & D) with the accuracy of 100% and seven classes with the accuracy of 97.62%. Conclusion The experimental results indicated that the proposed combination of feature extraction and selection method offers suitable classification accuracy and may be employed to detect the subtle changes in the cry signals. © 2017 Elsevier B.V.}, note = {cited By 21}, keywords = {Accidents, Algorithms, Article, Artificial Neural Network, Asphyxia, Binary Dragonfly Optimization Aalgorithm, Classification (of information), Classification Algorithm, Classifier, Coding, Computer-Assisted, Constants and Coefficients, Crying, Database Systems, Databases, Deafness, Diagnosis, Energy, Entropy, Extraction, Extreme Learning Machine, Factual, Factual Database, Feature Extraction, Feature Selection Methods, Fuzzy System, Hearing Impairment, Human, Hunger, Infant, Infant Cry, Infant Cry Classifications, Jaundice, Kernel Method, Learning, Linear Predictive Coding, Machine Learning, Mathematical Transformations, Mel Frequency Cepstral Coefficient, Mel Frequency Cepstral Coefficients, Multi-Class Classification, Neural Networks, Nonlinear Dynamics, Nonlinear System, Optimization, Pain, Pathophysiology, Prematurity, Reproducibility, Reproducibility of Results, Signal Processing, Speech Recognition, Wavelet Analysis, Wavelet Packet, Wavelet Packet Transforms}, pubstate = {published}, tppubtype = {article} } Background and objective Infant cry signal carries several levels of information about the reason for crying (hunger, pain, sleepiness and discomfort) or the pathological status (asphyxia, deaf, jaundice, premature condition and autism, etc.) of an infant and therefore suited for early diagnosis. In this work, combination of wavelet packet based features and Improved Binary Dragonfly Optimization based feature selection method was proposed to classify the different types of infant cry signals. Methods Cry signals from 2 different databases were utilized. First database contains 507 cry samples of normal (N), 340 cry samples of asphyxia (A), 879 cry samples of deaf (D), 350 cry samples of hungry (H) and 192 cry samples of pain (P). Second database contains 513 cry samples of jaundice (J), 531 samples of premature (Prem) and 45 samples of normal (N). Wavelet packet transform based energy and non-linear entropies (496 features), Linear Predictive Coding (LPC) based cepstral features (56 features), Mel-frequency Cepstral Coefficients (MFCCs) were extracted (16 features). The combined feature set consists of 568 features. To overcome the curse of dimensionality issue, improved binary dragonfly optimization algorithm (IBDFO) was proposed to select the most salient attributes or features. Finally, Extreme Learning Machine (ELM) kernel classifier was used to classify the different types of infant cry signals using all the features and highly informative features as well. Results Several experiments of two-class and multi-class classification of cry signals were conducted. In binary or two-class experiments, maximum accuracy of 90.18% for H Vs P, 100% for A Vs N, 100% for D Vs N and 97.61% J Vs Prem was achieved using the features selected (only 204 features out of 568) by IBDFO. For the classification of multiple cry signals (multi-class problem), the selected features could differentiate between three classes (N, A & D) with the accuracy of 100% and seven classes with the accuracy of 97.62%. Conclusion The experimental results indicated that the proposed combination of feature extraction and selection method offers suitable classification accuracy and may be employed to detect the subtle changes in the cry signals. © 2017 Elsevier B.V. |
Thu, Ei H; Hussain, Z; Shuid, A N Current Drug Targets, 19 (8), pp. 865-876, 2018, ISSN: 13894501, (cited By 2). Abstract | Links | BibTeX | Tags: Amisulpride, Amitriptyline, Animals, Antipsychotic Agents, Anxiety, Aripiprazole, Autism, Bioavailability, Biological Availability, Bipolar Disorder, Buspirone, Chemistry, Clonazepam, Clozapine, Depression, Diazepam, Drug Delivery System, Drug Delivery Systems, Duloxetine, Half Life Time, Half-Life, Health Care, Human, Iloperidone, In Vitro Study, In Vivo Study, Mental Disease, Mental Disorders, Midazolam, Nanotechnology, Neuroleptic Agent, Olanzapine, Pathophysiology, Permeability, Physical Chemistry, Psychosis, Review, Risperidone, Schizophrenia, Solubility, Sulpiride, Treatment Outcome, Venlafaxine, Ziprasidone @article{EiThu2018865, title = {New insight in improving therapeutic efficacy of antipsychotic agents: An overview of improved in vitro and in vivo performance, efficacy upgradation and future prospects}, author = {H Ei Thu and Z Hussain and A N Shuid}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85048981535&doi=10.2174%2f1389450117666161125174625&partnerID=40&md5=d32e5bc9766ff9d68dd79f082b9ca4bc}, doi = {10.2174/1389450117666161125174625}, issn = {13894501}, year = {2018}, date = {2018-01-01}, journal = {Current Drug Targets}, volume = {19}, number = {8}, pages = {865-876}, publisher = {Bentham Science Publishers B.V.}, abstract = {Psychotic disorders are recognized as severe mental disorders that rigorously affect pa-tient’s personality, critical thinking, and perceptional ability. High prevalence, global dissemination and limitations of conventional pharmacological approaches compel a significant burden to the patient, medical professionals and the healthcare system. To date, numerous orally administered therapies are available for the management of depressive disorders, schizophrenia, anxiety, bipolar disorders and autism spectrum problems. However, poor water solubility, erratic oral absorption, extensive first-pass metabolism, low oral bioavailability and short half-lives are the major factors which limit the pharmaceutical significance and therapeutic feasibility of these agents. In recent decades, nanotechnology-based delivery systems have gained remarkable attention of the researchers to mitigate the pharmaceutical issues related to the antipsychotic therapies and to optimize their oral drug delivery, therapeutic outcomes, and patient compliance. Therefore, the present review was aimed to summarize the available in vitro and in vivo evidences signifying the pharmaceutical importance of the advanced delivery systems in improving the aqueous solubility, transmembrane permeability, oral bioavailability and therapeutic outcome of the antipsychotic agents. © 2018 Bentham Science Publishers.}, note = {cited By 2}, keywords = {Amisulpride, Amitriptyline, Animals, Antipsychotic Agents, Anxiety, Aripiprazole, Autism, Bioavailability, Biological Availability, Bipolar Disorder, Buspirone, Chemistry, Clonazepam, Clozapine, Depression, Diazepam, Drug Delivery System, Drug Delivery Systems, Duloxetine, Half Life Time, Half-Life, Health Care, Human, Iloperidone, In Vitro Study, In Vivo Study, Mental Disease, Mental Disorders, Midazolam, Nanotechnology, Neuroleptic Agent, Olanzapine, Pathophysiology, Permeability, Physical Chemistry, Psychosis, Review, Risperidone, Schizophrenia, Solubility, Sulpiride, Treatment Outcome, Venlafaxine, Ziprasidone}, pubstate = {published}, tppubtype = {article} } Psychotic disorders are recognized as severe mental disorders that rigorously affect pa-tient’s personality, critical thinking, and perceptional ability. High prevalence, global dissemination and limitations of conventional pharmacological approaches compel a significant burden to the patient, medical professionals and the healthcare system. To date, numerous orally administered therapies are available for the management of depressive disorders, schizophrenia, anxiety, bipolar disorders and autism spectrum problems. However, poor water solubility, erratic oral absorption, extensive first-pass metabolism, low oral bioavailability and short half-lives are the major factors which limit the pharmaceutical significance and therapeutic feasibility of these agents. In recent decades, nanotechnology-based delivery systems have gained remarkable attention of the researchers to mitigate the pharmaceutical issues related to the antipsychotic therapies and to optimize their oral drug delivery, therapeutic outcomes, and patient compliance. Therefore, the present review was aimed to summarize the available in vitro and in vivo evidences signifying the pharmaceutical importance of the advanced delivery systems in improving the aqueous solubility, transmembrane permeability, oral bioavailability and therapeutic outcome of the antipsychotic agents. © 2018 Bentham Science Publishers. |
2017 |
Hasan, C Z C; Jailani, R; Tahir, Md N; Ilias, S The analysis of three-dimensional ground reaction forces during gait in children with autism spectrum disorders Journal Article Research in Developmental Disabilities, 66 , pp. 55-63, 2017, ISSN: 08914222, (cited By 8). Abstract | Links | BibTeX | Tags: Age Distribution, Article, Autism, Autism Spectrum Disorders, Biomechanical Phenomena, Biomechanics, Body Equilibrium, Body Height, Body Mass, Body Weight, Children, Clinical Article, Controlled Study, Disease Assessment, Female, Gait, Gait Analysis, Gait Disorder, Ground Reaction Forces, Human, Imaging, Leg Length, Malaysia, Male, Neurologic Examination, Pathophysiology, Physiology, Postural Balance, Procedures, Psychology, Statistics, Three-Dimensional, Three-Dimensional Imaging, Three-Dimentional Ground Reaction Force, Walking @article{Hasan201755, title = {The analysis of three-dimensional ground reaction forces during gait in children with autism spectrum disorders}, author = {C Z C Hasan and R Jailani and N Md Tahir and S Ilias}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85015640386&doi=10.1016%2fj.ridd.2017.02.015&partnerID=40&md5=d6a9839cda7f62bcce9bdcca33d3d33b}, doi = {10.1016/j.ridd.2017.02.015}, issn = {08914222}, year = {2017}, date = {2017-01-01}, journal = {Research in Developmental Disabilities}, volume = {66}, pages = {55-63}, publisher = {Elsevier Inc.}, abstract = {Minimal information is known about the three-dimensional (3D) ground reaction forces (GRF) on the gait patterns of individuals with autism spectrum disorders (ASD). The purpose of this study was to investigate whether the 3D GRF components differ significantly between children with ASD and the peer controls. 15 children with ASD and 25 typically developing (TD) children had participated in the study. Two force plates were used to measure the 3D GRF data during walking. Time-series parameterization techniques were employed to extract 17 discrete features from the 3D GRF waveforms. By using independent t-test and Mann-Whitney U test, significant differences (p < 0.05) between the ASD and TD groups were found for four GRF features. Children with ASD demonstrated higher maximum braking force, lower relative time to maximum braking force, and lower relative time to zero force during mid-stance. Children with ASD were also found to have reduced the second peak of vertical GRF in the terminal stance. These major findings suggest that children with ASD experience significant difficulties in supporting their body weight and endure gait instability during the stance phase. The findings of this research are useful to both clinicians and parents who wish to provide these children with appropriate treatments and rehabilitation programs. © 2017 Elsevier Ltd}, note = {cited By 8}, keywords = {Age Distribution, Article, Autism, Autism Spectrum Disorders, Biomechanical Phenomena, Biomechanics, Body Equilibrium, Body Height, Body Mass, Body Weight, Children, Clinical Article, Controlled Study, Disease Assessment, Female, Gait, Gait Analysis, Gait Disorder, Ground Reaction Forces, Human, Imaging, Leg Length, Malaysia, Male, Neurologic Examination, Pathophysiology, Physiology, Postural Balance, Procedures, Psychology, Statistics, Three-Dimensional, Three-Dimensional Imaging, Three-Dimentional Ground Reaction Force, Walking}, pubstate = {published}, tppubtype = {article} } Minimal information is known about the three-dimensional (3D) ground reaction forces (GRF) on the gait patterns of individuals with autism spectrum disorders (ASD). The purpose of this study was to investigate whether the 3D GRF components differ significantly between children with ASD and the peer controls. 15 children with ASD and 25 typically developing (TD) children had participated in the study. Two force plates were used to measure the 3D GRF data during walking. Time-series parameterization techniques were employed to extract 17 discrete features from the 3D GRF waveforms. By using independent t-test and Mann-Whitney U test, significant differences (p < 0.05) between the ASD and TD groups were found for four GRF features. Children with ASD demonstrated higher maximum braking force, lower relative time to maximum braking force, and lower relative time to zero force during mid-stance. Children with ASD were also found to have reduced the second peak of vertical GRF in the terminal stance. These major findings suggest that children with ASD experience significant difficulties in supporting their body weight and endure gait instability during the stance phase. The findings of this research are useful to both clinicians and parents who wish to provide these children with appropriate treatments and rehabilitation programs. © 2017 Elsevier Ltd |
2016 |
Sheppard, E; Pillai, D; Wong, G T -L; Ropar, D; Mitchell, P How Easy is it to Read the Minds of People with Autism Spectrum Disorder? Journal Article Journal of Autism and Developmental Disorders, 46 (4), pp. 1247-1254, 2016, ISSN: 01623257, (cited By 37). Abstract | Links | BibTeX | Tags: Adolescent, Adult, Article, Autism, Autism Spectrum Disorders, Decision Making, Emotion, Facial Expression, Female, Human, Male, Mental Health, Nonverbal Communication, Pathophysiology, Priority Journal, Psychology, Video Recording, Young Adult @article{Sheppard20161247, title = {How Easy is it to Read the Minds of People with Autism Spectrum Disorder?}, author = {E Sheppard and D Pillai and G T -L Wong and D Ropar and P Mitchell}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84961215349&doi=10.1007%2fs10803-015-2662-8&partnerID=40&md5=d39b6bdebe3c2f33e304eb4d4c09b6fd}, doi = {10.1007/s10803-015-2662-8}, issn = {01623257}, year = {2016}, date = {2016-01-01}, journal = {Journal of Autism and Developmental Disorders}, volume = {46}, number = {4}, pages = {1247-1254}, publisher = {Springer New York LLC}, abstract = {How well can neurotypical adults’ interpret mental states in people with ASD? ‘Targets’ (ASD and neurotypical) reactions to four events were video-recorded then shown to neurotypical participants whose task was to identify which event the target had experienced. In study 1 participants were more successful for neurotypical than ASD targets. In study 2, participants rated ASD targets equally expressive as neurotypical targets for three of the events, while in study 3 participants gave different verbal descriptions of the reactions of ASD and neurotypical targets. It thus seems people with ASD react differently but not less expressively to events. Because neurotypicals are ineffective in interpreting the behaviour of those with ASD, this could contribute to the social difficulties in ASD. © 2015, Springer Science+Business Media New York.}, note = {cited By 37}, keywords = {Adolescent, Adult, Article, Autism, Autism Spectrum Disorders, Decision Making, Emotion, Facial Expression, Female, Human, Male, Mental Health, Nonverbal Communication, Pathophysiology, Priority Journal, Psychology, Video Recording, Young Adult}, pubstate = {published}, tppubtype = {article} } How well can neurotypical adults’ interpret mental states in people with ASD? ‘Targets’ (ASD and neurotypical) reactions to four events were video-recorded then shown to neurotypical participants whose task was to identify which event the target had experienced. In study 1 participants were more successful for neurotypical than ASD targets. In study 2, participants rated ASD targets equally expressive as neurotypical targets for three of the events, while in study 3 participants gave different verbal descriptions of the reactions of ASD and neurotypical targets. It thus seems people with ASD react differently but not less expressively to events. Because neurotypicals are ineffective in interpreting the behaviour of those with ASD, this could contribute to the social difficulties in ASD. © 2015, Springer Science+Business Media New York. |
2014 |
Karim, S; Mirza, Z; Kamal, M A; Abuzenadah, A M; Azhar, E I; Al-Qahtani, M H; Damanhouri, G A; Ahmad, F; Gan, S H; Sohrab, S S The role of viruses in neurodegenerative and neurobehavioral diseases Journal Article CNS and Neurological Disorders - Drug Targets, 13 (7), pp. 1213-1223, 2014, ISSN: 18715273, (cited By 12). Abstract | Links | BibTeX | Tags: Alzheimer Disease, Amyotrophic Lateral Sclerosis, Animals, Article, Autism, Beta Interferon, Borna Disease Virus, Cytomegalovirus, Degenerative Disease, Disease Association, Enterovirus, Epstein Barr virus, Hepatitis Virus, Herpes Simplex Virus, HIV Associated Dementia, Human, Immune System, Inflammation, Influenza Virus, Influenza Virus A H5N1, Mental Disease, Mental Disorders, Multiple Sclerosis, Nerve Cell Degeneration, Neurodegenerative Diseases, Nonhuman, Parkinson Disease, Pathophysiology, Picornavirus, Roseolovirus, Varicella Zoster Virus, Virology, Virus Infection, Virus Pathogenesis, Virus Transmission, West Nile Flavivirus @article{Karim20141213, title = {The role of viruses in neurodegenerative and neurobehavioral diseases}, author = {S Karim and Z Mirza and M A Kamal and A M Abuzenadah and E I Azhar and M H Al-Qahtani and G A Damanhouri and F Ahmad and S H Gan and S S Sohrab}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84911396470&doi=10.2174%2f187152731307141015122638&partnerID=40&md5=7564c64b2fe5d0737f83e65e1fdff60a}, doi = {10.2174/187152731307141015122638}, issn = {18715273}, year = {2014}, date = {2014-01-01}, journal = {CNS and Neurological Disorders - Drug Targets}, volume = {13}, number = {7}, pages = {1213-1223}, publisher = {Bentham Science Publishers B.V.}, abstract = {Neurodegenerative and neurobehavioral diseases may be caused by chronic and neuropathic viral infections and may result in a loss of neurons and axons in the central nervous system that increases with age. To date, there is evidence of systemic viral infections that occur with some neurodegenerative conditions such as Alzheimer’s disease, Parkinson’s disease, amyotrophic lateral sclerosis, multiple sclerosis, autism spectrum disorders, and HIV-associated neurocognitive disorders. With increasing lifespan, the incidence of neurodegenerative diseases increases consistently. Neurodegenerative diseases affect approximately 37 million people worldwide and are an important cause of mortality. In addition to established non-viral-induced reasons for neurodegenerative diseases, neuropathic infections and viruses associated with neurodegenerative diseases have been proposed. Neuronal degeneration can be either directly or indirectly affected by viral infection. Viruses that attack the human immune system can also affect the nervous system and interfere with classical pathways of neurodegenerative diseases. Viruses can enter the central nervous system, but the exact mechanism cannot be understood well. Various studies have supported viral- and non-viral-mediated neurodegeneration at the cellular, molecular, genomic and proteomic levels. The main focus of this review is to illustrate the association between viral infections and both neurodegenerative and neurobehavioral diseases, so that the possible mechanism and pathway of neurodegenerative diseases can be better explained. This information will strengthen new concepts and ideas for neurodegenerative and neurobehavioral disease treatment. © 2014 Bentham Science Publishers.}, note = {cited By 12}, keywords = {Alzheimer Disease, Amyotrophic Lateral Sclerosis, Animals, Article, Autism, Beta Interferon, Borna Disease Virus, Cytomegalovirus, Degenerative Disease, Disease Association, Enterovirus, Epstein Barr virus, Hepatitis Virus, Herpes Simplex Virus, HIV Associated Dementia, Human, Immune System, Inflammation, Influenza Virus, Influenza Virus A H5N1, Mental Disease, Mental Disorders, Multiple Sclerosis, Nerve Cell Degeneration, Neurodegenerative Diseases, Nonhuman, Parkinson Disease, Pathophysiology, Picornavirus, Roseolovirus, Varicella Zoster Virus, Virology, Virus Infection, Virus Pathogenesis, Virus Transmission, West Nile Flavivirus}, pubstate = {published}, tppubtype = {article} } Neurodegenerative and neurobehavioral diseases may be caused by chronic and neuropathic viral infections and may result in a loss of neurons and axons in the central nervous system that increases with age. To date, there is evidence of systemic viral infections that occur with some neurodegenerative conditions such as Alzheimer’s disease, Parkinson’s disease, amyotrophic lateral sclerosis, multiple sclerosis, autism spectrum disorders, and HIV-associated neurocognitive disorders. With increasing lifespan, the incidence of neurodegenerative diseases increases consistently. Neurodegenerative diseases affect approximately 37 million people worldwide and are an important cause of mortality. In addition to established non-viral-induced reasons for neurodegenerative diseases, neuropathic infections and viruses associated with neurodegenerative diseases have been proposed. Neuronal degeneration can be either directly or indirectly affected by viral infection. Viruses that attack the human immune system can also affect the nervous system and interfere with classical pathways of neurodegenerative diseases. Viruses can enter the central nervous system, but the exact mechanism cannot be understood well. Various studies have supported viral- and non-viral-mediated neurodegeneration at the cellular, molecular, genomic and proteomic levels. The main focus of this review is to illustrate the association between viral infections and both neurodegenerative and neurobehavioral diseases, so that the possible mechanism and pathway of neurodegenerative diseases can be better explained. This information will strengthen new concepts and ideas for neurodegenerative and neurobehavioral disease treatment. © 2014 Bentham Science Publishers. |
Bhat, S; Acharya, U R; Adeli, H; Bairy, G M; Adeli, A Automated diagnosis of autism: In search of a mathematical marker Journal Article Reviews in the Neurosciences, 25 (6), pp. 851-861, 2014, ISSN: 03341763, (cited By 34). Abstract | Links | BibTeX | Tags: Algorithms, Article, Autism, Autism Spectrum Disorders, Automation, Biological Model, Brain, Chaos Theory, Correlation Analysis, Detrended Fluctuation Analysis, Disease Marker, Electrode, Electroencephalogram, Electroencephalography, Entropy, Fourier Transformation, Fractal Analysis, Frequency Domain Analysis, Human, Mathematical Analysis, Mathematical Marker, Mathematical Parameters, Models, Neurologic Disease, Neurological, Nonlinear Dynamics, Nonlinear System, Pathophysiology, Priority Journal, Procedures, Signal Processing, Statistical Model, Time, Time Frequency Analysis, Wavelet Analysis @article{Bhat2014851, title = {Automated diagnosis of autism: In search of a mathematical marker}, author = {S Bhat and U R Acharya and H Adeli and G M Bairy and A Adeli}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84925286949&doi=10.1515%2frevneuro-2014-0036&partnerID=40&md5=04858a5c9860e9027e3113835ca2e11f}, doi = {10.1515/revneuro-2014-0036}, issn = {03341763}, year = {2014}, date = {2014-01-01}, journal = {Reviews in the Neurosciences}, volume = {25}, number = {6}, pages = {851-861}, publisher = {Walter de Gruyter GmbH}, abstract = {Autism is a type of neurodevelopmental disorder affecting the memory, behavior, emotion, learning ability, and communication of an individual. An early detection of the abnormality, due to irregular processing in the brain, can be achieved using electroencephalograms (EEG). The variations in the EEG signals cannot be deciphered by mere visual inspection. Computer-aided diagnostic tools can be used to recognize the subtle and invisible information present in the irregular EEG pattern and diagnose autism. This paper presents a state-of-theart review of automated EEG-based diagnosis of autism. Various time domain, frequency domain, time-frequency domain, and nonlinear dynamics for the analysis of autistic EEG signals are described briefly. A focus of the review is the use of nonlinear dynamics and chaos theory to discover the mathematical biomarkers for the diagnosis of the autism analogous to biological markers. A combination of the time-frequency and nonlinear dynamic analysis is the most effective approach to characterize the nonstationary and chaotic physiological signals for the automated EEGbased diagnosis of autism spectrum disorder (ASD). The features extracted using these nonlinear methods can be used as mathematical markers to detect the early stage of autism and aid the clinicians in their diagnosis. This will expedite the administration of appropriate therapies to treat the disorder. © 2014 Walter de Gruyter GmbH.}, note = {cited By 34}, keywords = {Algorithms, Article, Autism, Autism Spectrum Disorders, Automation, Biological Model, Brain, Chaos Theory, Correlation Analysis, Detrended Fluctuation Analysis, Disease Marker, Electrode, Electroencephalogram, Electroencephalography, Entropy, Fourier Transformation, Fractal Analysis, Frequency Domain Analysis, Human, Mathematical Analysis, Mathematical Marker, Mathematical Parameters, Models, Neurologic Disease, Neurological, Nonlinear Dynamics, Nonlinear System, Pathophysiology, Priority Journal, Procedures, Signal Processing, Statistical Model, Time, Time Frequency Analysis, Wavelet Analysis}, pubstate = {published}, tppubtype = {article} } Autism is a type of neurodevelopmental disorder affecting the memory, behavior, emotion, learning ability, and communication of an individual. An early detection of the abnormality, due to irregular processing in the brain, can be achieved using electroencephalograms (EEG). The variations in the EEG signals cannot be deciphered by mere visual inspection. Computer-aided diagnostic tools can be used to recognize the subtle and invisible information present in the irregular EEG pattern and diagnose autism. This paper presents a state-of-theart review of automated EEG-based diagnosis of autism. Various time domain, frequency domain, time-frequency domain, and nonlinear dynamics for the analysis of autistic EEG signals are described briefly. A focus of the review is the use of nonlinear dynamics and chaos theory to discover the mathematical biomarkers for the diagnosis of the autism analogous to biological markers. A combination of the time-frequency and nonlinear dynamic analysis is the most effective approach to characterize the nonstationary and chaotic physiological signals for the automated EEGbased diagnosis of autism spectrum disorder (ASD). The features extracted using these nonlinear methods can be used as mathematical markers to detect the early stage of autism and aid the clinicians in their diagnosis. This will expedite the administration of appropriate therapies to treat the disorder. © 2014 Walter de Gruyter GmbH. |
Pillai, D; Sheppard, E; Ropar, D; Marsh, L; Pearson, A; Mitchell, P Using other minds as a window onto the world: Guessing what happened from clues in behaviour Journal Article Journal of Autism and Developmental Disorders, 44 (10), pp. 2430-2439, 2014, ISSN: 01623257, (cited By 17). Abstract | Links | BibTeX | Tags: Adolescent, Adult, Article, Autism, Child Development Disorders, Children, Clinical Article, Cognition, Controlled Study, Eye Movement, Eye Tracking, Facial Expression, Gaze, Human, Intelligence Quotient, Male, Measurement Accuracy, Mouth, Pathophysiology, Pervasive, Physiology, Psychological Aspect, Psychology, Retrodiction, Task Performance, Theory of Mind, Verbal Communication, Video Recording, Videotape Recording, Young Adult @article{Pillai20142430, title = {Using other minds as a window onto the world: Guessing what happened from clues in behaviour}, author = {D Pillai and E Sheppard and D Ropar and L Marsh and A Pearson and P Mitchell}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84912053354&doi=10.1007%2fs10803-014-2106-x&partnerID=40&md5=c3396f6f468e37e253c657f998993859}, doi = {10.1007/s10803-014-2106-x}, issn = {01623257}, year = {2014}, date = {2014-01-01}, journal = {Journal of Autism and Developmental Disorders}, volume = {44}, number = {10}, pages = {2430-2439}, publisher = {Springer New York LLC}, abstract = {It has been proposed that mentalising involves retrodicting as well as predicting behaviour, by inferring previous mental states of a target. This study investigated whether retrodiction is impaired in individuals with autism spectrum disorders (ASD). Participants watched videos of real people reacting to the researcher behaving in one of four possible ways. Their task was to decide which of these four ‘‘scenarios’’ each person responded to. Participants’ eye movements were recorded. Participants with ASD were poorer than comparison participants at identifying the scenario to which people in the videos were responding. There were no group differences in time spent looking at the eyes or mouth. The findings imply those with ASD are impaired in using mentalising skills for retrodiction. © Springer Science+Business Media New York 2014.}, note = {cited By 17}, keywords = {Adolescent, Adult, Article, Autism, Child Development Disorders, Children, Clinical Article, Cognition, Controlled Study, Eye Movement, Eye Tracking, Facial Expression, Gaze, Human, Intelligence Quotient, Male, Measurement Accuracy, Mouth, Pathophysiology, Pervasive, Physiology, Psychological Aspect, Psychology, Retrodiction, Task Performance, Theory of Mind, Verbal Communication, Video Recording, Videotape Recording, Young Adult}, pubstate = {published}, tppubtype = {article} } It has been proposed that mentalising involves retrodicting as well as predicting behaviour, by inferring previous mental states of a target. This study investigated whether retrodiction is impaired in individuals with autism spectrum disorders (ASD). Participants watched videos of real people reacting to the researcher behaving in one of four possible ways. Their task was to decide which of these four ‘‘scenarios’’ each person responded to. Participants’ eye movements were recorded. Participants with ASD were poorer than comparison participants at identifying the scenario to which people in the videos were responding. There were no group differences in time spent looking at the eyes or mouth. The findings imply those with ASD are impaired in using mentalising skills for retrodiction. © Springer Science+Business Media New York 2014. |
2013 |
Mousavizadeh, K; Askari, M; Arian, H; Gorjipour, F; Nikpour, A R; Tavafjadid, M; Aryani, O; Kamalidehghan, B; Maroof, H R; Houshmand, M Association of human mtDNA mutations with autism in Iranian patients Journal Article Journal of Research in Medical Sciences, 18 (10), pp. 926, 2013, ISSN: 17351995, (cited By 2). Links | BibTeX | Tags: Autism, Clinical Article, Controlled Study, Gene, Gene Frequency, Gene Mutation, Gene Sequence, Genetic Association, Genetic Risk, Human, Letter, Mitochondrial DNA, Molecular Phylogeny, Pathophysiology, Point Mutation, Polymerase Chain Reaction @article{Mousavizadeh2013926, title = {Association of human mtDNA mutations with autism in Iranian patients}, author = {K Mousavizadeh and M Askari and H Arian and F Gorjipour and A R Nikpour and M Tavafjadid and O Aryani and B Kamalidehghan and H R Maroof and M Houshmand}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84887270916&partnerID=40&md5=3922601b0364489a2b76d620316cc150}, issn = {17351995}, year = {2013}, date = {2013-01-01}, journal = {Journal of Research in Medical Sciences}, volume = {18}, number = {10}, pages = {926}, publisher = {Isfahan University of Medical Sciences(IUMS)}, note = {cited By 2}, keywords = {Autism, Clinical Article, Controlled Study, Gene, Gene Frequency, Gene Mutation, Gene Sequence, Genetic Association, Genetic Risk, Human, Letter, Mitochondrial DNA, Molecular Phylogeny, Pathophysiology, Point Mutation, Polymerase Chain Reaction}, pubstate = {published}, tppubtype = {article} } |