Using Neuro affective Computing for treatment of stroke patients

Strokes are leading causes of death and disability. The stroke rehabilitation market is therefore a very large market and the commercial interest in electroencephalogram (EEG) is growing. The EIT Digital Doctoral School has opened an industrial doctorate position at GTEC and the University of Trento to develop a software platform to ultimately improve the quality of life for stroke patients. You can apply now.

The foreseen collaboration between EIT Digital Doctoral School, GTEC, and the University of Trento will lead to a unique knowledge exchange in the areas of innovative brain-computer interfaces, stroke rehab technologies and business developments. Due to the work of the industrial doctorate, GTEC aims to be the first to enter the market with such technologies and as such create new employment.

Stroke and therapy

Stroke, a condition where the blood supply to the brain is disrupted, is ranked as the second leading cause of death worldwide with an annual mortality rate of about 5.5 million. Worldwide, about 15 million people suffer from a stroke each year (World Health Organisation).  About half of the stroke survivors are left with permanent movement disability. GTEC and the University of Trento estimate that there are in the EU alone, over 8000 entities to provide therapy for stroke, ranging from small, specialised therapy centres like the RecoveriX-Gyms to major hospitals. Stroke rehab is a very large market. The idea of Neuro affective Computing has been explored in laboratories; it remains impractical for real-world use.

Movement rehabilitation is not possible for persons with some birth conditions, injuries or progressive diseases that disable the arms. They benefit best through artificial limbs. To control artificial limbs GTEC wants to support next-generation motor rehabilitation therapy by helping patients regain movement after stroke using a brain-computer Interface that can allow patients to connect with robots, Virtual Reality (VR) systems or other tools used in therapy. Brain-Computer Interaction, and the intelligent applications based on them, are expected to have very high growth in coming years.


The state-of-the-art for real-time collection of EEG data from people is changing rapidly. Until recently, most EEG systems were not practical outside of laboratory settings for many reasons. Electrodes require messy electrode gel and cables connecting the ugly and expensive cap to a computer and real-world noise sources create unacceptable noise in the EEG signal.

Now, software for mainstream EEG applications is becoming more advanced as public and commercial interest in EEG grows.

There is, however, little emphasis on usability and Human Computer Interface considerations for non-expert users outside of the lab. Validation with end users, including usability testing, in particular, end users with special needs such as stroke patients are often ignored until the system is complete.  GTEC’s RecoveriX system, introduced in 2016, already includes VR tools to help persons with stroke, but they do not adapt to emotion.


The industrial doctorate research will focus on the software development and the human-computer interaction aspects. GTEC has extensive software libraries to support data recording, data tagging, numerous pre-processing, analysis and classification activities, data visualization and reporting, secure storage and other tasks.

To build the software, the industrial doctorate will be using Brain-Computer Interface. The software will process the brain signals in a more optimal way to improve Signal to Noise ratio. The industrial doctorate candidate will also work on extending the capacity of the algorithms to provide more advanced functions and create new applications that are not in the market yet.

The adaptation of the interactive applications will be based on the user’s mental state, which will be classified in real-time using the electroencephalogram (EEG). The PhD student will conduct usability testing with healthy persons, without excessive development time.

He or she will explore the business conditions for the industrialisation of the prototype system and create a spinoff with the support of EIT Digital.

Expected outcome

The main goals of this industrial doctorate are to produce knowledge and build a complete system for adaptive EEG-based systems based on emotion, across three specific use cases in the markets of haptic feedback via wearables, VR environments and home robots.

If the processing of the signals can be improved by advanced algorithms, the recovery of patients can be further improved in terms of time required and the extent of recovered function. In addition to new and scalable software tools, this project could lead to new services for professional companies specialized in motor rehabilitation therapy.

If this project is successful, everyday people can enjoy tools that adapt automatically to help them achieve their goals - without any need for expensive and bulky equipment, electrode gel or technical expertise.

The two goals will comprise:

  • Interactive, user-friendly software to help users (1) manage their EEG system, including quick mounting, maintenance and troubleshooting; (2) select the type of task, task parameters etc; (3) monitor their own EEG activity such as the intensity of their imagined grasping after the therapists asks to imagine grasping; (4) develop their own user-state adaptation programs and (5) print or email reports.
  • New/improved algorithms, parameters, processing chains and other details to manage EEG data and extract information about user state while trying to accomplish goals during the interaction with a system;
  • A Business Plan within the PhD thesis that evaluates commercial aspects with respect to post-project opportunities, including three recommended directions. GTEC will also consider new applications for new groups beyond those mentioned above: adaptive VR and haptic feedback might be developed into new tools for neuromarketing, improved training for athletes or other users, “patient-centred” psychiatry or other therapies for people with autism, stress disorders, depression, ADHD or other very broad conditions.

The academic outcomes will include:

  • two peer-reviewed Open Access publications,
  • two conference presentations,
  • five professional public interactive workshops/demos; and
  • a completed PhD thesis.


The doctoral student involved in this programme will share its time between the Co-Location Centre of the EIT Digital Trento Node and the premises of GTEC in Austria. To conduct the research the student might also visit other European universities and companies in the Netherlands and Spain to learn about a non-invasive approach that complements EEG and advanced immersion of VR.

The PhD student will participate in GTEC’s internal training courses and be following the EIT Digital Doctoral School Industrial Doctorate programme, including the leadership seminars as well. Furthermore, the PhD student will also observe the RecoveriX-Gym and interact with therapists, other staff and patients involved in a service-oriented business to provide rehabilitation therapy.


  • Title: Neuro Affective Computing: Emotion Recognition via Non-Invasive Brain-Computer Interface for Interactive Systems
  • Industrial partner: GTEC
  • Academic/research partner: University of Trento, Department of Information Engineering and Computer Science
  • Number of available PhD positions: 1 
  • Duration: 3 years 
  • This PhD will be funded by EIT Digital and GTEC


The full description of the PhD position is to be found in this PDF called Neuro Affective Computing: Emotion Recognition via Non-Invasive Brain-Computer Interface for Interactive Systems.

Please apply before 25 August, 2020.

If you are interested in applying to this position, please follow this two-step process: 

  1. Complete the EIT Digital application form here;
  2. Apply on the relevant University system at this link.

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