BEBE-Learning, software to assist in the early detection of Autism Spectrum Disorder (ASD)

  • From Spain
  • Responsive
  • Patents for licensing

Summary of the technology

Software tool designed to assist in the early detection of Autism Spectrum Disorder (ASD) in children through the visual analysis of videos.


Details of the Technology Offer

New and innovative aspects

  • Eye Tracking Technology: Utilizes eye tracking to gather objective data on how children visually interact with videos.
  • Artificial Intelligence: Employs neural network models to analyze visual patterns, enabling accurate and objective assessment.
  • Continuous Adaptability: Can improve with new data, maintaining its effectiveness over time.
  • Early and Objective Detection: Allows for the early and precise identification of ASD, which is crucial for early intervention and a better prognosis.
  • Bias Reduction: Minimizes the influence of subjectivity in assessments, providing results based on objective visual data.

Main advantages of its use

  • Time and Resource Savings: Compared to traditional methods, it can save time and resources in the diagnostic process.
  • Remote Medicine Potential: Facilitates the remote evaluation of children, which is especially relevant in situations where in-person visits can be difficult or costly.
  • Support for Research and Continuous Improvement: Contributes to scientific research by providing objective data for studies on ASD and its visual manifestations, allowing the tool to adapt and improve with new data.
  • Facilitates Clinical Decision-Making: Assists healthcare professionals and psychologists in making more informed decisions in diagnosis and treatment planning.


This innovative tool focuses on collecting data related to Autism Spectrum Disorder (ASD) in children through the visual analysis of videos. The process begins by presenting a series of specially designed videos to the children. While watching these videos, eye-tracking technology is used to record and analyze in real-time where the children are directing their gaze.
The data collected from this eye-tracking is translated into a set of variables, which are used as input for artificial neural network models. These models have the ability to learn and detect complex patterns in the eye-tracking data. Furthermore, variable selection techniques are incorporated to ensure the robustness of the models and enhance their accuracy.
Moreover, this tool has the capability to adapt and improve over time as more data accumulates. This ensures that the system can continuously fine-tune itself and maintain consistent accuracy in detecting ASD.
The primary application of this tool is to provide accurate diagnoses of ASD in children, even at early ages. Early identification of ASD is crucial as it allows for timely intervention and the early commencement of therapies and support, which can significantly improve the long-term prognosis for children with ASD.
In addition to its clinical diagnostic use, this tool also has implications for ASD research, as it can help better understand the visual patterns associated with the disorder.


The software enables improved detection and diagnosis of ASD, with the potential to benefit children, families, healthcare professionals, as well as research and the development of more effective treatments.

Intellectual property status

Protected by software

Current development status

Device already developed and validated for industrialization.

Desired business relationship

Commercial Agreement, License Agreement, Technical Cooperation: further development; Technical Cooperation: testing new applications; Technical Cooperation: adaptation to specific needs.

Intellectual property status

  • Granted Patent
  • Patent application number :Software

Attached documents

Related Keywords

  • Biological Sciences
  • Social and Economics concerns
  • Computer related
  • Genetic Engineering / Molecular Biology
  • Medical Health related
  • Research
  • Software
  • artificial intelligence
  • early detection
  • Artificial Neural Networks
  • Autism
  • visual tracking
  • video selection
  • adaptability


The aim of the The Technology Transfer Office (TTO) of the Univesidad de Burgos is to promote Innovation technology through the reseach results transfer and the conexions between the University and the new needs and requirements of the society - we are the link between the University and the Industry. Contact person: José Manuel López (


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