Tytuł Data publikacji Autor
The article presents a research study on recognizing therapy progress among children with autism spectrum disorder. The progress is recognized on the basis of behavioural data gathered via five specially designed tablet games. Over 180 distinct parameters are calculated on the basis of raw data delivered via the game flow and tablet sensors - i.e. touch screen, accelerometer and gyroscope. The results obtained confirm the possibility of recognizing progress in particular areas of development. The recognition accuracy exceeds 80%. Moreover, the study identifies a subset of parameters which appear to be better predictors of therapy progress than others. The proposed method - consisting of data recording, parameter calculation formulas and prediction models - might be implemented in a tool to support both therapists and parents of autistic children. Such a tool might be used to monitor the course of the therapy, modify it and report its results.
2017
Agata Kołakowska,
Agnieszka Landowska,
Anna Anzulewicz,
Krzysztof Sobota
The paper concerns technology of automatic emotion recognition applied in e-learning environment. During a study of e-learning process the authors applied facial expressions observation via multiple video cameras. Preliminary analysis of the facial expressions using automatic emotion recognition tools revealed several unexpected results, including unavailability of recognition due to face coverage and significant inconsistency between the results obtained from two cameras. The paper presents the experiment on e-learning process and summarizes the observations that constitute limitations of emotion recognition from facial expressions applied in e-learning context. The paper might be of interest to researchers and practitioners who consider automatic emotion recognition as an option in monitoring e-learning processes.
2017
Agnieszka Landowska,
Grzegorz Brodny,
Michał Wróbel
The paper concerns the automation of measuring progress of children with autism spectrum disorder. The proposed approach combines diverse approaches: e-technologies and mobile applications for autism, behavioral metrics derived from gyroscope and game state with machine learning methods to find interconnections between the metrics and the progress of a child. The paper presents a gyroscope-based game, specifically designed as an investigation tool for therapy progress monitoring. The game enables registration of behavioral patterns of use of the applications and tablet. The paper presents how the game was used in a study of behavioral metrics. 31 children with autism took part in the study. Each of them played the game several times during a 6-months period. The data gathered during the gameplay are used to calculate a set of metrics, that might be used in evaluation of a child's progress. Results in terms of classification accuracy reach 80%, however they depend on the particular skill category. The best accuracies are obtained for evaluation of stereotypic behaviors and gross motor skills of a child. The approach presented in the study is novel and was not applied before, therefore it might be interesting for other researchers working on supporting technologies for autism. The results might be also interesting for practitioners applying e-technologies in autistics therapy.
2017
Agata Kołakowska,
Agnieszka Landowska,
Katarzyna Karpienko
Te paper reports current stage of the project Automated Terapy Monitoring for Children with Developmental Disorders of Autism Spectrum (AUTMON), that aims at development of methods and tools to allow for the automatic evaluation of the therapy progress among children with autism. Finding objective measures suitable for evaluating therapy progress would let create a system supporting those who diagnose autism and the therapists working with the children. In future these measures could be also applied as optimization criteria in defning the optimal therapy path. Such tool could be helpful in preparing the therapy plan, choosing the type of tasks and their frequency. It might also follow the therapy course, predict its direction and indicate the points which probably require intervention and changing the plan. Obviously it would never replace a therapist, but make his work more effective. Moreover, it could also support the parents in their efforts to objectively report valuable observations to the therapists, which would be especially important in the case of a limited access to therapy centers.
2017
Agnieszka Landowska,
Agata Kołakowska,
Michał Wróbel
Artykuł dotyczy aktualnych trendów w konstrukcji inteligentnych systemów edukacyjnych, uwzględniających stan emocjonalny ucznia w doborze ścieżki nauczania. Artykuł przedstawia założenia i rezultaty badania ankietowego, którego celem było określenie, jak zastosowanie automatycznego rozpoznawania emocji jest postrzegane w kontekście edukacyjnym. Badanie przeprowadzono wśród studentów oraz pracowników uczelni wyższych w Polsce. Rezultaty mogą być przydatne dla badaczy informatyki afektywnej, zajmujących się zastosowaniami w edukacji, a także dla producentów aplikacji edukacyjnych, rozważających rozszerzenie systemów o aspekt rozpoznawania emocji.
2017
Agnieszka Landowska,
Grzegorz Brodny
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