TSN’s Emotionally
Immersive TechnologyTM

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What is the attentiveness of your online audience?

TSN’s Emotionally Immersive Technology (EIT) measures the audience's willingness to participate in the listening and learning process (behavioral engagement) and his/her emotional attitude towards participation (emotional engagement). First, EIT captures the audience via video and tracks each face through the video frames. Then novel computer vision and machine learning approaches are used to identify the attentiveness level.

BACKGROUND

Through computer vision and machine learning EIT provides emotional analytics in any video or image formats. Our novel Deep Region Learning-based architecture extracts facial micro-expressions accurately.

Our innovative deep region learning-based technology allows us to extract emotions accurately from images. Employing this technology in our daily devices creates emotionally intelligent devices that can understand how our audience feels. From screen mounted cameras we collect video recordings of subjects in a mostly unstructured setting and gather annotations from a panel of humans for assessing student engagement levels. Next we present the predicted results of different representations of engagement, both with subject-independent and individual-specific models, and quantify the performance gap between the generalized and personalized models for engagement prediction. While the subject-independent performance is challenged by data sparsity, results show that the individual-specific models can predict engagement well even with very few labeled examples.

Our EIT serves as the crucial component of our core application used in online learning and content-centric instructional systems. While participation in on-line training and education has been rapidly adopted universally in an attempt to reduce education costs, in the world of education, existing online systems for lectures, are yet to be effective or considered equal in value to traditional classroom teaching. The purpose and commercial potential of this EIT technology is to significantly transform on-line education making it more effective than in the past.

The impacts of EIT reach far beyond online education and promise to be highly applicable to problems in many markets:

  • Healthcare
    • Mental Health - In 2013 mental disorders in the USA topped the list of the most costly health conditions, with spending at US$201 billion. EIT technology can help in decreasing this cost through early detection of human emotional disturbance by providing a detailed feedback of a patient’s psychiatric condition.
    • Autism – Autism coaching is another important health application for EIT and can be used for regular quantitative monitoring of the development of autistic children.
    • Pain Level Assessment - EIT can be applied when the severity of pain cannot easily be communicated.
  • Transportation
    • Applications in the automotive market sector are multiple especially the detection of driver drowsiness.
    • Monitoring the level of driver attentiveness.
    • The detection of emotion in the driver in order to improve car safety.
  • Retail and Advertising
    • EIT can be used for emotion analytics to determine how subjects respond emotionally to brand advertising and product usability.
  • Other Markets
    • Additionally, EIT is acutely relevant for other market sectors such as the mobile phone, virtual reality, robotic telepresence and security.