I'm Reza, M.Sc. candidate of Télécommunications at University of Quebec, INRS-EMT.

My research interests lie at the cross-roads of Physiological Computing, Virtual Reality, and Multi-sensory experiences! At the moment, I am using different methods to study the capabilities of HMD-VR to enhace quality-of-experience and leverage it for rehabilitation applications!

You can find me on:

Check out my ResearchGate and Google Scholar!

Multisensory VR Experience

Our first paper: Review of systems that integrated VR with wearables for stroke rehabilitation!

Head-Mounted Display-Based Virtual Reality and Physiological Computing for Stroke Rehabilitation: A Systematic Review

Then we attempted to see what is the impact of multisensory VR on QoE subscales (e.g., immersion, realism, engagement):

QoMEX’ 2022: Multisensory Immersive Experiences: A Pilot Study on Subjective and Instrumental Human Influential Factors AssessmentMetroXRaine: Quantifying User Behaviour in Multisensory Immersive Experiences

Then we proposed a multisensory VR training paradigm! However, its papers are under review. We investigated its QoE aspects in a paper submitted to the “quality and user experience” journal. Plus, the effects on MI-BCI performance are reported in a Frontiers journal! I hope they get accepted and published as soon as possible!

Towards Instrumental Quality Assessment of Multisensory Immersive Experiences Using a Biosensor-Equipped Head-Mounted DisplayEnhancing Motor Imagery Efficacy Using Multisensory Virtual Reality Training

Learn more about Oranges V2: An experiment with scents and force feedback!

Latest News

Attending to Scientist2Entrepreneur (S2E) Program! Finding my way into the world of startups!

During the last couple of months, I have been reading literature and gathering information on gaps that we have in the intersection of health, VR, and ML-AI. I came up[…]

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TeTrA: Jump to speech controlled VR env

It was one of my dreams that someday there will be games controlled via brain, speech, and body movements! However, I’ve seen Kinect which helps you to control the game[…]

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The Oranges: A multi-sensory Experience

During past weeks, I was designing and collecting data to investigate QoE items in an multi sensory environment enabled with olfactory and haptic feedback. The results will be published soon![…]

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The organizations I have contributed

OpenLab at UHN

Traumas cote-nord

Lady Davis Institute at JGH

University of Tabriz

Tabriz University of Medical Sciences

Ardabil University of Medical Sciences

East Azerbaijan National Elite Foundation

BCI Lab at University of Tabriz

Cyberpsychology Lab of Université du Québec at Outaouais (UQO)


Check out my IG! Where I share my main hobby, photography!

  • #montreal #canada #911 #porsche #car #photography #canon
  • #montreal #canada #911 #porsche #car #photography #canon
  • #montreal #canada #911 #porsche #car #photography #canon
#montreal #canada #911 #porsche #car #photography #canon
#montreal #canada #911 #porsche #car #photography #canon
2 months ago
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#montreal #canada #911 #porsche #car #photography #canon
#montreal #canada #911 #porsche #car #photography #canon
2 months ago
View on Instagram |
#montreal #canada #911 #porsche #car #photography #canon
#montreal #canada #911 #porsche #car #photography #canon
2 months ago
View on Instagram |

Other Projects

Immersive VR Environment For Patients Who Have suffered from Aphasia

An application of AI in Medicine

Online COVID-19 Diagnoser

An outbreak of SARS-CoV-2 shocked healthcare systems around the world. It began in December 2019 in Wuhan, China, and spread out in over 120 countries in less than three months. Imaging technologies helped in COVID-19 fast and reliable diagnosis. CT-Scan and X-ray imaging are popular methods. This study is focused on X-ray imaging, concerning limitations in small cities to access CT-Scan and its costs. Using deep learning models helps to diagnose precisely and quickly. We aimed to design an online system based on deep learning, which reports lung engagement with the disease, patient status, and therapeutic guidelines. Our objective was to relieve pressure on radiologists and minimize the interval between imaging and diagnosing. VGG19, VGG16, InceptionV3, and ResNet50 were evaluated to be considered as the main code of the online diagnosing system. VGG16, with 98.92% accuracy, achieved the best score. VGG19 performed quite similarly to VGG16. VGG19, InceptionV3 and ResNet50 obtained 98.90, 71.79 and 28.27 subsequently.


I’m Reza Amini Gougeh, holding B.Sc. of Biomedical Engineering from the University of Tabriz, Iran and studying M.Sc of Telecommunication in INRS, at MuSAE Lab., Montreal, QC! I love to extend my knowledge over different fields of BME. As you know, this field uses mechanics, electronics, materials, and medical science to help health-care system including rehabilitation procedures. Programming ,as a beneficial tool, has a crucialrole in reaching acceptable outcomes. When I was 16, I learned front-end design using HTML and CSS. After a while, I learned C and C++. In university, I had challenging problems, so I attracted to python and MATLAB, which were more efficient and fast in Data analyzing. In early 2018, I interested in BCI systems, and tried to read and research more in this field. This passion led me to be a member of BCI Lab. After having an invitation from Iran’s National Elites Foundation to work on VR game to enhance 3D-object comprehension in elementary students, I decided to use my knowledge in game designing to help people who suffer from dementia.

Attending MuSAE Lab., was one of the most happiest events of my life! Having a cool, knowledgeable and supportive team around me, increases productivity.

By joinng to DREAM BIG research as RA in June 2021, I had opportunity to implement my knowledge over ML and AI on helping/evaluating mental health issues.