This paper presents a systematic review of relevant primary studies on the use of augmented reality (AR) to improve various skills of children and adolescents diagnosed with autism spectrum disorder (ASD) from years 2005 to 2018 inclusive in eight bibliographic databases. This systematic review attempts to address eleven specific research questions related to the learing skills, participants, AR technology, research design, data collection methods, settings, evaluation parameters, intervention outcomes, generalization, and maintenance. The social communication skill was the highly targeted skill, and individuals with ASD were part of all the studies. Computer, smartphone, and smartglass are more frequently used technologies. The commonly used research design was pre-test and post-test. Almost all the studies used observation as a data collection method, and classroom environment or controlled research environment were used as a setting of evaluation. Most of the evaluation parameters were human-assisted. The results of the studies show that AR benefited children with ASD in learning skills. The generalization test was conducted in one study only, but the results were not reported. The results of maintenance tests conducted in five studies during a short-term period following the withdrawal of intervention were positive. Although the effect of using AR towards the learning of individuals was positive, given the wide variety of skills targeted in the studies, and the heterogeneity of the participants, a summative conclusion regarding the effectiveness of AR for teaching or learning of skills related to ASD based on the existing literature is not possible. The review also proposes the research taxonomy for ASD. Future research addressing the effectiveness of AR among more participants, different technologies supporting AR for the intervention, generalization, and maintenance of learning skills, and the evaluation in the inslusive classroom environment and other settings is warranted.

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Augmented Reality for Learning of Children and Adolescents With Autism Spectrum Disorder (ASD): A Systematic Review

Rapidly increasing number of web pages or documents leads to topic specific filtering in order to find web pages or documents efficiently. This is a preliminary research that uses cosine similarity to implement text relevance in order to find topic specific document. This research is divided into three parts. The first part is text-preprocessing. In this part, the punctuation in a document will be removed, then convert the document to lower case, implement stop word removal and then extracting the root word by using Porter Stemming algorithm. The second part is keywords weighting. Keyword weighting will be used by the next part, the text relevance calculation. Text relevance calculation will result the value between 0 and 1. The closer value to 1, then both documents are more related, vice versa.

https://iopscience.iop.org/article/10.1088/1742-6596/978/1/012120/pdf

The Implementation of Cosine Similarity to Calculate Text Relevance between Two Documents

Real-time online attendance method is helpful for workers who do a lot of activities outside the office or workers with multi-schedule. The attendance system using online biometric fingerprint system will reduce the problems caused by manual system usage such as lags in data management. The purpose of the research is to constructs an online presence system that combines fingerprint modules and GPS. The ZFM-20 fingerprint module is used as the system's main input as well as a security tool as an entrance to get access to the entire system. GPS module is applied to determine the user's location and sends it to the smartphone. Arduino module in the system will send a text message to the parties concerned about the user's location data automatically. Each module works well and testing the entire system showed the system work reliable according to the initial scenario. The User can access the report using SMS, website, and application on the Android smartphone. The fingerprint sensor can determine the fingerprint stored in the database with an average response time of 1.39 seconds, and GPS can determine latitude and longitude with an average error of 0.007352% and 0.0003% respectively.

Real-Time Online Attendance System Based on Fingerprint and GPS in the Smartphone

For people with Autism Spectrum Disorder (ASD), using technological tools, such as augmented reality (AR) and serious games remain a new and unexplored option. To attract people with ASD who have communicative, social, emotional and attention deficit disorders to behavioral treatments, an attractive environment is needed that ensures continuity during treatment. The aim of the current work is to efficiently examine systematic reviews and relevant primary studies on ASD solutions from 2015 to 2020, particularly those using the traditional Picture Exchange Communication System (PECS), the application of augmented reality and those that propose serious games, thereby providing an overview of existing evidence and to identify strategies for future research. Five databases were searched for keywords that may be included within the broad Autism Spectrum Disorder ‘ASD’ umbrella term, alongside ‘augmented reality’, ‘serious games’ and ‘PECS’. We screened 1799 titles and abstracts, read, and retained 12 reviews and 43 studies. The studies scrutinized in our systematic review were examined to answer four primary and four sub-research questions, which we formulated to better understand general trends in the use of approaches for attracting people with ASD to behavioral therapies. Additionally, our systematic review also presents ongoing issues in this area of research and suggests promising future research directions. Our review is useful to researchers in this field as it facilitates the comparison of existing studies with work currently being conducted, based on the availability of a wide range of studies in three different areas (AR, SG and PECS).

/pdf/augmented-reality-serious-games-and-picture-exchange-3158ec92.pdf

Augmented Reality, Serious Games and Picture Exchange Communication System for People with ASD: Systematic Literature Review and Future Directions

This paper presents a systematic review of the literature on the modalities used in computer-based interventions (CBIs) and the impact of using these interventions in the learning, generalisation, and maintenance of language comprehension and decoding skills for children with autism spectrum disorder (ASD), ending with an appraisal of the certainty of evidence. Despite the importance of both skills in the reading comprehension and overall learning, a limited number of studies have been found. These include seven studies on language comprehension and seven studies on decoding. The shortlisted studies were analysed and a very limited number of modalities were found to have been used; text, graphics, audio, video, and mouse movement are used in all the studies and are termed basic modalities. Statistical analysis was also conducted on three parameters: (1) outcome of the study; (2) generalisation; and (3) maintenance. The analysis showed that CBIs were effective in facilitating these children’s learning; there was a significant improvement in the performance of children from the baseline to during and the post-intervention period. The analysis of generalisation has revealed positive results, indicating that the children were able to transfer information to a different setting or situation. Positive results are also noted from the analysis of maintenance, which indicate that the children retained information following the withdrawal of intervention. The combination of teachers’ instructions and CBI has provided better results than using either of them separately. This study has discovered 23 potential modalities and 2 potential CBIs including serious games and virtual learning environments that can be explored for language comprehension and decoding skills.

/pdf/a-systematic-review-of-modalities-in-computer-based-15jdpslysw.pdf

A systematic review of modalities in computer-based interventions (CBIs) for language comprehension and decoding skills of children with autism spectrum disorder (ASD)

Augmented Reality is a technique that can bring social story therapy into virtual world to increase intrinsic motivation of children with Autism Spectrum Disorder(ASD). By looking at the behaviour of ASD who will be difficult to get the focus, the lack of sensory and motor nerves in the use of loads on the hands or other organs will be very distressing children with ASD in doing the right activities, and interpret and understand the social situation in determining a response appropriately. Required method to be able to apply social story on therapy of children with ASD that is implemented with Augmented Reality. The output resulting from this method is 3D animation (three-dimensional animation) of social story by detecting marker located in special book and some simple game which done by using leap motion controller which is useful in reading hand movement in real-time.

https://iopscience.iop.org/article/10.1088/1742-6596/978/1/012040/pdf

Augmented reality social story for autism spectrum disorder

Fingerprint is one of the most unique parts of the human body that distinguishes one person from others and is easily accessed. This uniqueness is supported by technology that can automatically identify or recognize a person called fingerprint sensor. Yet, the existing Fingerprint Sensor can only do fingerprint identification on one machine. For the mentioned reason, we need a method to be able to recognize each user in a different fingerprint sensor. The purpose of this research is to build fingerprint sensor system for fingerprint data management to be centralized so identification can be done in each Fingerprint Sensor. The result of this research shows that by using Arduino and Raspberry Pi, data processing can be centralized so that fingerprint identification can be done in each fingerprint sensor with 98.5 % success rate of centralized server recording.

https://iopscience.iop.org/article/10.1088/1742-6596/978/1/012060/pdf

Attendance fingerprint identification system using arduino and single board computer

The World Tourism Organization (UNWTO) in 2014 released that there are 28 million visitors who visit Russia. Most of the visitors might have problem in typing Russian word when using digital dictionary. This is caused by the letters, called Cyrillic that used by the Russian and the countries around it, have different shape than Latin letters. The visitors might not familiar with Cyrillic. This research proposes an alternative way to input the Cyrillic words. Instead of typing the Cyrillic words directly, camera can be used to capture image of the words as input. The captured image is cropped, then several pre-processing steps are applied such as noise filtering, binary image processing, segmentation and thinning. Next, the feature extraction process is applied to the image. Cyrillic letters recognition in the image is done by utilizing Self-Organizing Map (SOM) algorithm. SOM successfully recognizes 89.09% Cyrillic letters from the computer-generated images. On the other hand, SOM successfully recognizes 88.89% Cyrillic letters from the image captured by the smartphone's camera. For the word recognition, SOM successfully recognized 292 words and partially recognized 58 words from the image captured by the smartphone's camera. Therefore, the accuracy of the word recognition using SOM is 83.42%

https://iopscience.iop.org/article/10.1088/1742-6596/801/1/012040/pdf

Russian Character Recognition using Self-Organizing Map

Differences possessed by children with special needs such as differences in mental traits, sensory abilities, social and emotional behavior etc. of normal children causing learning and developmental barriers on children, so that requiring more specific services. Autism is one category of children with special needs who experience delays in responding to the things around him that caused by chaos in the brain work system. The tendency of autistic children who only focus on themselves makes it difficult to concentrate on one thing and easily switch when being talked. Training focus of the child can be done by giving them basic commands presented with visually appealing from the utilization of augmented reality and leap motion controller.

https://iopscience.iop.org/article/10.1088/1742-6596/978/1/012109/pdf

Implementation of augmented reality to train focus on children with s pecial needs

Backpropagation and Direction Feature Extraction (DFE) are proposed in this paper for Chinese chess character recognition Backpropagation is a feed-forward neural network algorithm designed for learning by examples namely by calculating errors and updating weights in each epoch DFE is a feature extraction method by iterating and calculating the directons surrounding each pixel in the image to obtain the features In this research, Chinese chess characters are recognized to obtain the correct amount of each chess character in a package Due to the complex contour, stroke and pattern of Chinese chess characters, Chinese chess characters are difficult to be recognized by new learners Both Backpropagation and DFE performance are capable in recognizing Chinese chess characters with good accuracy of 98% for various sets and it is also robust from transition, brightness, image noise and rotation up to 60°

Dedy Arisandi

Papers

Augmented reality social story for autism spectrum disorder

Attendance fingerprint identification system using arduino and single board computer

Russian Character Recognition using Self-Organizing Map

Implementation of augmented reality to train focus on children with s pecial needs

Chinese chess character recognition using Direction Feature Extraction and backpropagation