Dr. Leontios Hadjileontiadis
Dr. leontios hadjileontiadis Professor Department Chair Biomedical Engineering and Biotechnology

Contact Information


Prof. Leontios Hadjileontiadis received his Advanced Diploma degree in electrical engineering and the Ph.D. degree in electrical and computer engineering (ECE) from the Aristotle University of Thessaloniki (AUTH), Thessaloniki, Greece, in 1989 and 1997, respectively, the Ph.D. degree in music composition from the University of York, York, U.K., in 2004, and the Diploma degree in musicology from AUTH, in 2011. His research interests include advanced signal processing, machine learning, biomedical engineering, affective computing, serious games, and active and healthy ageing. He is working on signal processing in the fields of biomedical engineering (bioacoustics, ECG data compression, high density EEG-based 3D vector field tomography) affective computing (EEG-based emotion recognition), educational data analytics (blended-, affective-, collaborative-learning modeling), non-destructive testing data analysis (crack detection in beams and plates), behavioral modeling (swarm-based decomposition/transform, cochlear decomposition/transform) at the Department of Biomedical Engineering at Khalifa University, where he serves also as its Chair. Dr. Hadjileontiadis is a Senior Member of the IEEE.

  • PhD, Music Composition, University of York (UK), 2004
  • Advanced Diploma, Musicology, Aristotle University of Thessaloniki, Thessaloniki, Greece. (2011)
  • PhD, Electrical and Computer Engineering, Aristotle University of Thessaloniki, Thessaloniki, Greece (1997)
  • Advanced Diploma, Electrical and Computer Engineering, Aristotle University of Thessaloniki (Greece), 1989

  • Biomedical Circuits and Signals (BMED640)
  • Independent Study II (BMED391)
  • Selected Topics in Biomedical Engineering (BMED694)
  • Senior Design Project I (BMED497)
  • Senior Design Project I (BMED497)
  • Senior Design Project II (BMED498)
  • Special Topics In BMED (BMED495)

Affiliated Research Institutes/Centers
  • Healthcare Engineering Innovation Center

Research Interests
  • Advanced signal processing
  • Biomedical engineering
  • Affective computing
  • Artificial inteligence/Machine Learning/Deep Learning
  • Behavrioral modeling
  • Active and healthy ageing
  • Serious games
  • Biomusic composition

Research Projects

OsteoMentor will assist osteoporosis patients in long-term self-managing of the disease, eliminating treatment drop-outs via radically new ICT-based personalized mentoring and interventions for empowering, motivating and helping them to improve and maintain their independence, functional capacity, health status, as well as preserving their physical, cognitive, mental and social well-being. 

OsteoMentor is an Android-iOS AI-based mHealth application, solely dedicated for the self-management of osteoporosis. It is the first mHealth application utilizing VR and AR technologies and computer game environments designed for the support of patients. The functionality of OsteoMentor is on capturing data from a wide variety of sources that will let the behavioral profile to infer the emotional state of the user and could provide to the virtual coaching the ability for affective computing.

he main functionality of OsteoMentor is the coaching of older adults targeting the elimination of osteoporosis’ risks of fracture, falls and depression and the proactive sustaining of their independence during ageing. The OsteoMentor platform will realize supportive feedback by a holistic, three-pillar, user-based approach: i) Personalized Game Suite (PGS), ii) Diet & Medication Recommendation (DMR) and iii) Lifestyle Recommendation (LR) that will be employed both in the smart-home as well in the smart-city concept.
OsteoMentor will also provide the statistics of extreme gestures (x-Gestures) identified by the accelerometer of the user (in his/her smart-watch) that could create or increase the risk for fractures. These statistics are sent both to the user and the attending physician, as motivational feedback to follow behavioral changes towards less risky gestures, in terms of deteriorating the fracture symptoms.
Moreover, to boost user’s engagement, a virtual reality path will be attempted, in order to foster mobilization of the patient via marching in the real world, yet moving in the virtual reality world (e.g., via Google Street view)within virtual routes with various contents, e.g. ,historical, natural, exhibitions, etc. 

Please visit: http://osteomentor.com/

Research Staff and Graduate Students:

Shiza Saleem Research Engineer
Ghada Alhussein PhD Student
Mohd Khalil Jehad Abu Hantash PhD Student