Seyyed Ali Zendehbad | Engineering | Editorial Board Member

Dr. Seyyed Ali Zendehbad | Engineering | Editorial Board Member

Islamic Azad University, Mashhad | Iran

Author Profile

Scopus

Early Academic Pursuits 🎓

Dr. Zendehbad’s academic journey began with a strong foundation in electronic and information technology engineering. He pursued multiple degrees, culminating in a Ph.D. in Biomedical Engineering from the Islamic Azad University of Mashhad. His doctoral research focused on improving upper limb function in stroke patients using biofeedback and muscle synergy analysis—an innovative approach with profound implications for rehabilitation science.

Professional Endeavors 👨‍🏫

Dr. Zendehbad has an impressive academic career as a professor and head of the Biomedical Engineering department at various prestigious institutions. He has taught specialized courses such as neuromuscular system control, biological system modeling, and biomedical research methodologies. Beyond academia, he has contributed to industry research, including the development of imaging quality enhancements for functional hard endoscopes.

Contributions and Research Focus 🔬

Dr. Zendehbad’s research primarily focuses on:
✅ Electromyogram (EMG) signal classification and analysis
✅ Muscle synergy patterns in stroke rehabilitation
✅ AI-driven biofeedback and assistive technologies
✅ Telehealth solutions and trustworthy AI applications in medical engineering

His work in stroke rehabilitation, particularly in biofeedback mechanisms and AI-driven recovery systems, has set new benchmarks in the field.

Accolades and Recognition 🏅

Dr. Zendehbad’s pioneering work has been recognized with several prestigious awards:
🏆 First Place - 31st Congress of Neurology and Clinical Electrophysiology (2024)
🏆 First Place - Shahid Beheshti University Startup Competition in Telerehabilitation (2021)
🏆 First Place - Mashhad University of Medical Sciences Startup Competition (2020)

These accolades reflect his outstanding contributions to medical engineering and rehabilitation technologies.

Impact and Influence 🌍

Dr. Zendehbad’s research has had a profound impact on both academia and industry. His contributions to AI-driven rehabilitation technologies have paved the way for more effective stroke recovery methods. Additionally, his role in startup competitions has facilitated innovation in telehealth and telerehabilitation, making cutting-edge healthcare solutions more accessible.

Legacy and Future Contributions 🚀

Dr. Zendehbad continues to push the boundaries of biomedical engineering. His ongoing research in AI applications for fatigue detection (FatigueNet project) and telehealth ethics (Trustworthy AI in Telehealth) demonstrates his forward-thinking approach. His legacy will undoubtedly inspire future researchers and innovators in the field of bioelectric engineering and medical technology.

 

Publications


📄 TraxVBF: A Hybrid Transformer-xLSTM Framework for EMG Signal Processing and Assistive Technology Development in Rehabilitation

  • Authors: Seyyed Ali Zendehbad, Athena Sharifi Razavi, Marzieh Allami Sanjani, Zahra Sedaghat, Saleh Lashkari
  • Journal: Sensing and Bio-Sensing Research
  • Year: 2025

📄 Identifying The Arm Joint Dynamics Using Muscle Synergy Patterns and SVMD-BiGRU Hybrid Mechanism

  • Authors: Seyyed Ali Zendehbad, Hamid Reza Kobravi, Mohammad Mahdi Khalilzadeh, Athena Sharifi Razavi, Payam Sasan Nezhad
  • Journal: Frontiers in Biomedical Technologies
  • Year: 2024

📄 Presenting a New Muscle Synergy Analysis Based Mechanism to Design a Trackable Visual Biofeedback Signal: Applicable to Arm Movement Recovery After Ischemic Stroke

  • Authors: Seyyed Ali Zendehbad, Hamid Reza Kobravi, Mohammad Mahdi Khalilzadeh, Athena Sharifi Razavi, Payam Sasan Nezhad
  • Journal: IEEE Access
  • Year: 2023

📄 A New Visual Biofeedback Protocol Based on Analyzing the Muscle Synergy Patterns to Recover the Upper Limbs Movement in Ischemic Stroke Patients: A Pilot Study

  • Authors: Seyyed Ali Zendehbad, Hamid Reza Kobravi, Mohammad Mahdi Khalilzadeh, Athena Sharifi Razavi, Payam Sasan Nezhad
  • Journal: The Neuroscience Journal of Shefaye Khatam
  • Year: 2023

📄 Investigation and Analysis of Feature Extraction Methods Based on Multi-Objective Genetic Algorithm and Support Vector Machine for Classification of Electromyogram Signals of Arm Muscles

  • Authors: Seyyed Ali Zendehbad, Siyamak Haghipour, Hamid Reza Kobravi, Seyyed Amir Zendehbad
  • Journal: Journal of New Research in Engineering Sciences
  • Year: 2016

 

Xiaoli Wu | Engineering | Best Researcher Award

Prof. Xiaoli Wu | Engineering | Best Researcher Award

Nanjing University of Science and Technology | China

Author Profile

Scopus

Orcid

🌟 Early Academic Pursuits

Dr. Xiaoli Wu embarked on her academic journey with a Bachelor's degree in Industrial Design from Shaanxi University of Science & Technology in 2003. Her strong aptitude for design and engineering led her to pursue a Master's in Mechanical Design and Theory, also at Shaanxi University. She further honed her expertise with a Ph.D. in Mechanical Engineering from Southeast University, focusing on Human-Computer Interaction. This robust academic foundation equipped her with the multidisciplinary knowledge required for her groundbreaking research in human-computer interaction and intelligent design systems.

🚀 Professional Endeavors: An International Journey

Dr. Wu's professional career spans continents and disciplines. She began as an Assistant Lecturer at Hohai University, steadily rising to the rank of Professor in 2019. Her international experience includes roles as a Research Scholar at the Australian National University, Academic Visiting Professor at UCL Interaction Centre, and the University of Birmingham's School of Computer Science. Currently, she is a Professor in the Department of Industrial Design at Nanjing University of Science & Technology, where she also serves as Dean of the Research Centre for Human Factors and Intelligent Interaction. Her extensive teaching portfolio includes subjects like Design Cognition and Ergonomics.

📚 Contributions and Research Focus

Dr. Wu’s research focuses on human factors in design, information visualization in human-machine systems, and intelligent interaction. She has significantly contributed to understanding visual cognition mechanisms, error factors in task interfaces, and design optimization in intelligent manufacturing. Her books, including Human Computer Interaction in Intelligent Manufacturing and Design and Cognition, are seminal texts in her field. As an editor and reviewer for top journals, she continues to shape the academic discourse in human-computer interaction and cognitive ergonomics.

🏆 Accolades and Recognition

Dr. Wu's contributions have been recognized with numerous awards, including the prestigious “333” High-level Scholars of Jiangsu Province and multiple grants from the National Natural Science Foundation of China. Her research projects, often supported by substantial funding, focus on cutting-edge topics like multi-modal information flow and intelligent manufacturing. Her achievements underscore her reputation as a leader in ergonomic design and human-computer interaction research.

🌍 Impact and Influence

Dr. Wu’s work bridges academic innovation and practical application, impacting industries ranging from manufacturing to digital media. As Executive Director of the Chinese Ergonomics Society and a key member of other professional organizations, she influences national and international standards in design and human-machine systems. Her teaching and mentorship have shaped the next generation of designers and engineers, ensuring her expertise ripples across fields and disciplines.

🌟 Legacy and Future Contributions

With a career marked by innovation and international collaboration, Dr. Wu’s legacy is one of advancing the frontiers of intelligent design and interaction systems. Her ongoing projects, such as the design of real-time monitoring systems in intelligent manufacturing, promise to redefine human-computer interaction. Her future contributions, bolstered by her upcoming publications, will undoubtedly continue to inspire and drive progress in her field. Dr. Wu’s work ensures a more ergonomic and user-centered technological future.

 

Publications


📔Research on similarity bias in dual objective visual search based on nuclear power human-machine interface icons
Author(s): He, Y., Wu, X., Yang, X., Zhou, J., Yu, D.
Journal: International Journal of Industrial Ergonomics
Year:2024


📔Cognitive evaluation based on regression and eye-tracking for layout on human–computer multi-interface
Author(s): Wang, L., Tang, W., Montagu, E., Wu, X., Xue, C.
Journal: Behaviour and Information Technology
Year:2024


📔Effective factors of icons searching performance based on visual attention capture for the nuclear power plants
Author(s): Wu, X., Zhou, C., He, Y., Li, Q., Yu, S.
Journal: Journal of the Society for Information Display
Year:2023


📔Study on the correlation and inhibition of visual marking and industrial icons
Author(s): Wu, X., Zhang, K., Fang, Z., Wang, X., Li, Q.
Journal: Displays
Year: 2023


📔How information within the perceptual span guides visual search and aids perception
Author(s): Chen, Y., Liao, C., Wu, X., Fang, Z., Zhang, L.
Journal: Displays
Year: 2023