2015 |
Yussof, H; Salleh, M H; Miskam, M A; Shamsuddin, S; Omar, A R Aplikasi ASKNAO yang menyasarkan pengembangan kemahiran sosial untuk kanak-kanak dengan autisme Persidangan 2015-Oktober , Persatuan Komputer IEEE, 2015, ISSN: 21618070, (dipetik oleh 3). Abstrak | Pautan | BibTeX | Tag: Automasi, Kanak-kanak dengan Autisme, Kemahiran komunikasi, Penyakit, Pendidikan, Kemahiran sosial @ persidangan{Yussof2015973, tajuk = {Aplikasi ASKNAO yang menyasarkan pengembangan kemahiran sosial untuk kanak-kanak dengan autisme}, pengarang = {H Yussof dan M H Salleh dan M A Miskam dan S Shamsuddin dan A R Omar}, url = {https://www.scopus.com/inward/record.uri?eid = 2-s2.0-84952770737&doi = 10.1109% 2fCoASE.2015.7294225&rakan kongsi = 40&md5 = bb2d8f8a5d54a457dec4137e1a55514a}, doi = {10.1109/KESELURUHAN.2015.7294225}, terbitan = {21618070}, tahun = {2015}, tarikh = {2015-01-01}, jurnal = {Persidangan Antarabangsa IEEE mengenai Sains dan Kejuruteraan Automasi}, isi padu = {2015-Oktober}, halaman = {973-978}, penerbit = {Persatuan Komputer IEEE}, abstrak = {Makalah ini bertujuan untuk mengkaji aplikasi ASKNAO yang menyasarkan kemahiran sosial kanak-kanak dengan autisme. Aplikasi ASKNAO adalah sistem yang direka untuk mengajar kanak-kanak autisme kemahiran asas yang secara semula jadi dipelajari oleh kanak-kanak biasa. Oleh kerana aplikasi ASKNAO adalah sistem berasaskan komersial, kandungannya belum dikategorikan secara teknikal dan khusus mengikut tiga kriteria autisme iaitu kemahiran sosial, kemahiran komunikasi dan tingkah laku berulang. Dengan mengambil langkah pertama dalam mengenal pasti kesesuaian Aplikasi yang memfokuskan pada kemahiran sosial, kajian lanjutan mengenai aplikasi dan penilaian ASKNAO dapat dilakukan untuk mengajar anak mengikut kehendak pengguna. © 2015 IEEE.}, nota = {dipetik oleh 3}, kata kunci = {Automasi, Kanak-kanak dengan Autisme, Kemahiran komunikasi, Penyakit, Pendidikan, Kemahiran sosial}, pubstate = {diterbitkan}, tppubtype = {persidangan} } Makalah ini bertujuan untuk mengkaji aplikasi ASKNAO yang menyasarkan kemahiran sosial kanak-kanak dengan autisme. Aplikasi ASKNAO adalah sistem yang direka untuk mengajar kanak-kanak autisme kemahiran asas yang secara semula jadi dipelajari oleh kanak-kanak biasa. Oleh kerana aplikasi ASKNAO adalah sistem berasaskan komersial, kandungannya belum dikategorikan secara teknikal dan khusus mengikut tiga kriteria autisme iaitu kemahiran sosial, kemahiran komunikasi dan tingkah laku berulang. Dengan mengambil langkah pertama dalam mengenal pasti kesesuaian Aplikasi yang memfokuskan pada kemahiran sosial, kajian lanjutan mengenai aplikasi dan penilaian ASKNAO dapat dilakukan untuk mengajar anak mengikut kehendak pengguna. © 2015 IEEE. |
2014 |
Batt, S; Acharya, U R; Adeli, H; Tenusu, G M; Adeli, A Automated diagnosis of autism: In search of a mathematical marker Artikel Jurnal Reviews in the Neurosciences, 25 (6), hlm. 851-861, 2014, ISSN: 03341763, (dipetik oleh 34). Abstrak | Pautan | BibTeX | Tag: Algoritma, Artikel, Autisme, Gangguan Spektrum Autisme, Automasi, Biological Model, Otak, Chaos Theory, Correlation Analysis, Detrended Fluctuation Analysis, Disease Marker, Electrode, Elektroencephalogram, Elektroensefalografi, Entropy, Fourier Transformation, Fractal Analysis, Frequency Domain Analysis, Manusia, Mathematical Analysis, Mathematical Marker, Mathematical Parameters, Models, Neurologic Disease, Neurological, Nonlinear Dynamics, Nonlinear System, Patofisiologi, Jurnal Keutamaan, Prosedur, Pemprosesan isyarat, Model Statistik, Masa, Time Frequency Analysis, Wavelet Analysis @artikel{Bhat2014851, tajuk = {Automated diagnosis of autism: In search of a mathematical marker}, pengarang = {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&rakan kongsi = 40&md5=04858a5c9860e9027e3113835ca2e11f}, doi = {10.1515/revneuro-2014-0036}, terbitan = {03341763}, tahun = {2014}, tarikh = {2014-01-01}, jurnal = {Reviews in the Neurosciences}, isi padu = {25}, nombor = {6}, halaman = {851-861}, penerbit = {Walter de Gruyter GmbH}, abstrak = {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 (LIHAT). 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.}, nota = {dipetik oleh 34}, kata kunci = {Algoritma, Artikel, Autisme, Gangguan Spektrum Autisme, Automasi, Biological Model, Otak, Chaos Theory, Correlation Analysis, Detrended Fluctuation Analysis, Disease Marker, Electrode, Elektroencephalogram, Elektroensefalografi, Entropy, Fourier Transformation, Fractal Analysis, Frequency Domain Analysis, Manusia, Mathematical Analysis, Mathematical Marker, Mathematical Parameters, Models, Neurologic Disease, Neurological, Nonlinear Dynamics, Nonlinear System, Patofisiologi, Jurnal Keutamaan, Prosedur, Pemprosesan isyarat, Model Statistik, Masa, Time Frequency Analysis, Wavelet Analysis}, pubstate = {diterbitkan}, tppubtype = {artikel} } 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 (LIHAT). 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. |
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2015 |
Aplikasi ASKNAO yang menyasarkan pengembangan kemahiran sosial untuk kanak-kanak dengan autisme Persidangan 2015-Oktober , Persatuan Komputer IEEE, 2015, ISSN: 21618070, (dipetik oleh 3). |
2014 |
Automated diagnosis of autism: In search of a mathematical marker Artikel Jurnal Reviews in the Neurosciences, 25 (6), hlm. 851-861, 2014, ISSN: 03341763, (dipetik oleh 34). |