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Kreowanie przestrzeni dedykowanej osobom dorosłym z zaburzeniami ze spektrum autyzmu

Bielak-Zasadzka Maria, Pachnik Anna

Builder

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2024

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R.28, nr 1

42--49

PL

Przedmiotem artykułu jest próba odpowiedzi na pytanie – jak należycie kształtować przestrzeń przeznaczoną dla osób dorosłych z zaburzeniami ze spektrum autyzmu? Głównym celem opracowania jest stworzenie wytycznych projektowych związanych z kształtowaniem środowiska zbudowanego, jakim jest przestrzeń ośrodka terapeutycznego dla dorosłych osób w spektrum autyzmu, przy jednoczesnym uwzględnieniu wpływu architektury oraz środowiska na wymagającego użytkowników. Wszystkie wskazówki i dane prowadzące do budowy programu funkcjonalno-powierzchniowego ośrodka powstały na bazie wykonanych badań i analiz przedprojektowych. W celu uzyskania zróżnicowanych danych zgromadzono wiedzę pochodzącą z literatury fachowej, stworzono zestawienie obiektów referencyjnych oraz przeprowadzono wywiady ze specjalistami z dziedziny autyzmu. Efektem końcowym, będącym odpowiedzią na postawione we wstępie pytanie, jest projekt koncepcyjny ośrodka terapeutycznego dla dorosłych osób w spektrum autyzmu z zagospodarowaniem terenów przyległych, zlokalizowany w Sosnowcu. Zasadniczym kryterium przy tworzeniu budynków ośrodka terapeutycznego było stworzenie przestrzeni specjalistycznych i uniwersalnych, ze szczególnym uwzględnieniem potrzeb i oczekiwań osób dorosłych dotkniętych zaburzeniami autystycznymi.

EN

The subject of the article is an attempt to answer the question - how to properly shape the space intended for adults with autism spectrum disorders? The main purpose of the study is to create design guidelines related to shaping the built environment, which is the space of the Therapeutic Center for Adults on the Autism Spectrum, while taking into account the impact of architecture and the environment on demanding users. All guidelines and data leading to the construction of the functional and surface program of the center were created on the basis of pre-design research and analyses. In order to obtain diverse data, knowledge from the professional literature was collected, a list of reference objects was compiled, and autism specialists were interviewed. The final result, which is the answer to the question posed in the introduction, is the conceptual design of the Therapeutic Center for Adults on the Autism Spectrum with the development of the adjacent areas, located in Sosnowiec. The main criterion when creating the buildings of the therapeutic center was to create specialized and universal spaces, with particular emphasis on the needs and expectations of adults affected by autistic disorders.

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An intelligent multimodal framework for identifying children with autism spectrum disorder

Chen Jingying, Liao Mengyi, Wang Guangshuai, Chen Chang

International Journal of Applied Mathematics and Computer Science

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2020

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Vol. 30, no. 3

435--448

EN

Early identification can significantly improve the prognosis of children with autism spectrum disorder (ASD). Yet existing identification methods are costly, time consuming, and dependent on the manual judgment of specialists. In this study, we present a multimodal framework that fuses data on a child’s eye fixation, facial expression, and cognitive level to automatically identify children with ASD, to improve the identification efficiency and reduce costs. The proposed methodology uses an optimized random forest (RF) algorithm to improve classification accuracy and then applies a hybrid fusion method based on the data source and time synchronization to ensure the reliability of the classification results. The classification accuracy of the framework was 91%, which is higher than that of the RF, support vector machine, and discriminant analysis methods. The results suggest that data on a child’s eye fixation, facial expression, and cognitive level are useful for identifying children with ASD. Because the proposed framework can separate ASD children from typically developing (TD) children, it can facilitate the early identification of ASD and may improve intervention programs for children with ASD.

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A robust method for early diagnosis of autism spectrum disorder from EEG signals based on feature selection and DBSCAN method

Abdolzadegan Donya, Moattar Mohammad Hossein, Ghoshuni Majid

Biocybernetics and Biomedical Engineering

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2020

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Vol. 40, no. 1

482--493

EN

Electroencephalogram (EEG) is one of the most important signals for diagnosis of Autism Spectrum Disorder (ASD). There are different challenges such as feature selection and the existence of artifacts in EEG signals. This article aims to present a robust method for early diagnosis of ASD from EEG signal. The study population consists of 34 children with ASD between 3–12 years and 11 healthy children in the same ranges of age. The proposed approach uses linear and nonlinear features such as Power Spectrum, Wavelet Transform, Fast Fourier Transform (FFT), Fractal Dimension, Correlation Dimension, Lyapunov Exponent, Entropy, Detrended Fluctuation Analysis and Synchronization Likelihood for describing the EEG signal. In addition Density Based Clustering is utilized for artifact removal and robustness. Besides, features selection is applied based on different criterions such as Mutual Information (MI), Information Gain (IG), Minimum-Redundancy Maximum-Relevancy (mRmR) and Genetic Algorithm (GA). Finally, the K-Nearest-Neighbor (KNN) and Support Vector Machines (SVM) classifiers are used for final decision. As a result, the investigation indicates that the classification accuracy of the approach using SVM is 90.57% while for KNN it is 72.77%. Moreover, the sensitivity of the proposed method is 99.91% for SVM and 91.96% for KNN. Also, experiments show that DFA, LE, Entropy and SL features have considerable influence in promoting the classification accuracy.