This chapter discusses assistive technologies applied in people with autism spectrum disorders and how these technologies promote their adaptation. We analyzed different technological application areas such as detection, assessment, diagnosis, intervention, training, learning, environment control, communication, mobility, and access. In recent years there has been a notable increase of publications and works related to the use of assistive technologies applied to Autism Spectrum Disorders. While most of the publications present novel systems, devices, and applications (smartphones, tablets, robots, avatars, etc.), general evaluation of the results is insufficient. Future lines of research are targeted to realize intelligent environments in order to integrate all knowledge and technological developments made in recent years.
a b s t r a c tThe predictive value of a developmental scale used during the first year of life is of great interest when planning early interventions. The predictive value of an instrument is the probability of hitting the diagnosis of disorder or developmental delay of a child. The cut-off point between normal and disability development recommended by the Merrill-Palmer-R Scale (MP-R) is the mean -1 , assuming a normal distribution. The MP-R scores in a sample of 291 children under one year old from the Valencian community were analysed. Even though the distribution of the MP-R scale in this sample was not normal, the forecast results were good. Additionally, the development scores using a new version of the scale were assessed using the Rasch model. Comparing the predictive value of the MP-R using two calculated cut-off points, both methods achieved good predictive values. We discuss if the cut-off point scores based on criteria should be used instead of typical scores. Palabras clave:Merrill Palmer R Validez diagnóstica Punto de corte Trastorno del desarrollo r e s u m e n El valor predictivo de una escala de desarrollo utilizado durante el primer año de vida es de gran interés en la planificación de las intervenciones tempranas. El valor predictivo de un instrumento es la probabilidad de acertar el diagnóstico de trastorno o retraso en el desarrollo de un niño. El punto de corte entre el desarrollo normal y la discapacidad recomendado por el MP-R es la media -1 , suponiendo una distribución normal. Se analizaron las puntuaciones de escala Merrill-Palmer-R (MP-R) en una muestra de 291 niños menores de un año de edad de la Comunidad Valenciana. A pesar de que no se distribuyen normalmente las puntuaciones de la escala MP-R en esta muestra, los resultados predichos eran buenos. Además, las puntuaciones de desarrollo utilizando una nueva versión de la escala se evaluaron utilizando el modelo de Rasch. Al comparar el valor predictivo de la MP-R utilizando dos puntos de corte calculados, ambos métodos obtuvieron buenos valores predictivos. Se discute si deben utilizarse los puntos de corte basados en criterios en lugar de las puntuaciones típicas.
This chapter discusses assistive technologies applied in people with autism spectrum disorders and how these technologies promote their adaptation. We analyzed different technological application areas such as detection, assessment, diagnosis, intervention, training, learning, environment control, communication, mobility, and access. In recent years there has been a notable increase of publications and works related to the use of assistive technologies applied to Autism Spectrum Disorders. While most of the publications present novel systems, devices, and applications (smartphones, tablets, robots, avatars, etc.), general evaluation of the results is insufficient. Future lines of research are targeted to realize intelligent environments in order to integrate all knowledge and technological developments made in recent years.
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