Associate Editors

Dr. Artemiadis’ primary research interests have been in robotics and autonomous systems that interact with humans. The goals of his research have been to improve the quality of life by developing and controlling robotic devices that physically and cognitively interact and collaborate with humans. This interaction can be with devices that assist and augment human capabilities, as well as provide motor rehabilitation therapy to impaired individuals. In order to accomplish this, Dr. Artemiadis’ research has been focusing on answering important questions regarding the symbiosis of humans and robots in environments that involve physical and cognitive interaction.

Dr Arvaneh’s research interest includes brain-computer interface, assistive technology, prosthetic control, cognitive processes and their clinical applications. She applies her expertise in adaptive signal processing and machine learning to accurately detect different biomarkers within brain and other physiological signals. She has incorporated these biomarkers in a range of robotic stroke rehabilitation, brain monitoring and cognitive performance enhancement experiments both in the laboratory and clinical settings. Dr Arvaneh is the head of Physiological Signals and Systems laboratory in the Automatic Control and Systems Engineering department at University of Sheffield, where analytical and experimental techniques are combined to develop improved therapeutic, assistive, adaptive and rehabilitative technologies for a variety of conditions.

Her research interests are mainly related to the processing of biomedical signals and images and to the development of innovative methodologies for feature extraction and for enhancement of the information content and the formulation of new interpretative models to be applied both in physiological studies and in clinics.

Applications are in the analysis of signals and images from the central nervous system, including EEG, sEEG, fMRI, fNIRS, MRI for a better understanding of the physiological mechanisms related to cognitive processes, brain plasticity, rehabilitation, and for the characterization of pathological conditions, such as epilepsia, cerebral palsy, traumatic brain injury. Further studies of peripheral signals, heart rate, blood pressure, respiration, are focused on cardiovascular modelling and emotion recognition.

The methodological effort focuses mainly on the development of time-frequency analysis; parametric recursive identification; multi-variable parametric modeling; non-linear feature extraction; linear and non-linear synchronization of biomedical series; data, signal and image fusion.

Dr. Thomas C. Bulea is a Staff Scientist in the Functional & Applied Biomechanics Section of the Rehabilitation Medicine Department at the National Institutes of Health Clinical Center, Bethesda, MD. Dr. Bulea’s research focuses on integration of neural interfacing and functional neuroimaging with rehabilitation robotics for evaluation and treatment of movement disorders and paralysis. Specific focus areas include combining electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) with motion capture and electromyography (EMG) to study brain-body dynamics during movement, development and evaluation of assistive devices and technology to improve motor function, and evaluation of novel rehabilitation therapies, including human-machine interaction and integration of virtual reality, to enhance motor learning and functional recovery. A recent emphasis has been on the development of pediatric exoskeletons and their evaluation in children with cerebral palsy.

He obtained a degree in Electronic (Biomedical) Engineering from the University of Genoa, Italy, in 1998, then a Ph.D. in Artificial Intelligence (Mathematical Logic) from the School of Informatics of the University of Edinburgh, Scotland, in 2005. He then turned his attention to assistive robotics and spent 4.5 years as a post-doctoral fellow at the Advanced Robotics Laboratory of the University of Genoa, Italy. Since 2009 he is a researcher at the Institute of Robotics and Mechatronics of the DLR – German Aerospace Center. Since 2021 he is a full professor in assistive robotics at the Friedrich-Alexander University of Erlangen-Nuremberg, Germany. He has (co)authored some 150 scientific papers, is involved in a few national and international research projects, and regularly serves for international editorial boards and committees.

Wei Chen is Professor, Director of Center of Intelligent Medical Electronics at School of Information Science and Technology, and Director of the Physiological Signal and Sleep platform in the Human Phenome Institute, at Fudan University, Shanghai, China. She is also an Associate Editor of IEEE Journal on Biomedical Health Informatics (J-BHI).

Her research interests include patient health monitoring, sleep monitoring, brain activity monitoring, smart sensor systems, wearable sensor systems, health robotics, machine learning and data fusion for healthcare. Her research center mainly focuses on advanced sensor systems; monitoring physiological, psychological and behavioral signals; multi-modal signal processing and data fusion, as well as user-centered design. Her center aims at improving quality of life, empowering patients for personalized health management; and providing doctors more accurate and efficient clinical decision support. Her research in the areas of neonatal monitoring, sleep monitoring, and smart rehabilitation covers healthcare for people of different age groups, from neonates to elderly.

Dr. Fani Deligianni is a Senior Lecturer (Associate Professor) at the School of Computing Science at the University of Glasgow, UK. She is also the lead of the Computing Technologies for Healthcare theme. Dr Fani Deligianni’s holds a PhD in Medical Image Computing (Imperial College London), an MSc in Advanced Computing (Imperial College London), an MSc in Neuroscience (University College London) and a MEng (equivalent) in Electrical and Computer Engineering (Aristotle University, Greece).

Her research interests involve the development of machine learning approaches to process neurophysiological and human motion data to improve performance of human-AI systems and preserve human health and wellbeing. She has a strong track record on statistical machine learning with brain MRI data, human motion analysis as well as adaptive brain computer interfaces and wearable sensing technologies.

Dr. Doborjeh is currently a lecturer in the Computer Science Department at Auckland University of Technology, New Zealand and is affiliated with Knowledge Engineering & Discovery Research Institute and as an associate researcher. Doborjeh has been principally researching in the field of Neuroinformatics, where she develops new methods based on brain-inspired artificial intelligence technologies to improve decision-making and decision support. Her research interest also includes deep learning, spiking neural networks, cognitive computation, mental/brain health informatics, spatiotemporal brain data analysis, and personalised modelling. She is also experienced in modelling, visualising, clustering and classifying of different types of brain data including EEG, MRI and fMRI. Doborjeh has been leading several successful collaborative projects in health informatics to develop prognostic/diagnostic systems for detection and prediction of mental issues and neurological diseases such as depression, cognitive impairment, dementia and stroke.

Professor Domingo’s goals are to elucidate the best methods for locomotor rehabilitation after neurological injury based on principles of biomechanics, motor learning and control. She seeks to understand how different types of error impact motor learning of walking balance in intact and disordered nervous systems. Related to this, she is interested in the role of proprioceptive sense in the recovery of balance and skilled walking function. She aims to use this knowledge to develop and optimize the use of physical guidance and rehabilitation robotics in restoring gait and balance in individuals with spinal cord injury and in older adults. She is also interested in improving the health and wellness of disabled populations using wearable sensors.

Dr. Gutierrez Farewik is a Professor of Biomechanics at the Department of Engineering Mechanics at KTH Royal Institute of Technology, and leads the KTH MoveAbility Lab.  She also has an affiliation to the Department of Women’s and Children’s Health at Karolinska Institutet. Her research interests span several biological scales, and include modelling, predictive simulation and device design for children and adults with motor disorders. She and her group combine experiments with numerical modelling to study the short- and long-term consequences of motor disorders, as well as the factors that influence a person’s movement strategy. They are developing biosignal-controlled assistive-as-needed devices for the lower extremities for applications in neurorehabilitation and habilitation, with a goal to increase movement efficiency, preserve available neural pathways and complement the user’s functional abilities.

Dr. Fisher is an Assistant Professor in the Department of Physical Medicine and Rehabilitation at the University of Pittsburgh and Director of Education for the Rehab Neural Engineering Labs. His research interests focus on the development of neuroprosthetic systems to restore function after injury or disease to the nervous system, including limb amputation and spinal cord injury. His ongoing research efforts include the clinical testing of spinal cord stimulation to restore sensory function after the loss of a limb and pre-clinical development of devices to stimulate the spinal cord and vagus nerve to control sensory, bladder, and gastrointestinal function. In 2021, he was awarded the North American Neuromodulation Society’s Kumar New Investigator Award for his research on the use of cervical spinal cord stimulation to restore sensory function after upper-limb amputation.

My scientific research investigates the field of neurological motor rehabilitation and motor assistance during daily life activities of fragile people or during exhausting activities of workers. This is both a key critical issue of our society, and an interesting scientific research field. In a multidisciplinary team, I concentrate on the mechanical design of both rehabilitation and assistance devices toward exoskeletons, to allow the movement to be perceived as more natural, and the control design toward patients’ initiated/controlled approaches, to include users’ personal motor programming in the loop. As a further step, any device design naturally needs validation, both in terms of the effectiveness of the rehabilitation or assistance, and the device’s usability and acceptability. The same user-centered approach is successful when investigating strategies to relieve a worker’s musculoskeletal system when performing exhausting activities. Biomechanical analysis, wearability, and ergonomics are in this case the key ingredients. My research aims to enable solutions “from cure to care” and leverages multidisciplinary methodologies, including mechatronic design, human-machine interaction, and artificial intelligence. My focus is on the investigation of rehabilitation biomarkers and motion control strategies toward the development of human-centered and personalized technologies to give frail people the possibility of doing anything today that they couldn’t do yesterday and to work toward effective usability and democratic adoption of the developed technologies.

Dr. Guarin is an Assistant Professor in the Biomedical Engineering program at the Florida Institute of Technology, Melbourne, FL. USA. Dr. Guarin received his Master’s and Doctorate degrees in Biomedical Engineering from McGill Univerity and was a postdoctoral trainee at Harvard University and the University of Toronto/ Toronto Rehabilitation Institute. He is the director of The Movement Estimation and Analysis; his research areas include neuroscience, signals analysis and synthesis, machine learning, and computer vision. Dr. Guarin’s work is focused on translating engineering approaches to develop disease-modifying therapies for patients with neuromuscular diseases and novel methods for disease diagnosis that are sensitive for early diagnosis.

Dongyun Gu is Professor in the Department of Orthopaedic Surgery of Shanghai Ninth People’s Hospital affiliated to Shanghai Jiao Tong University School of Medicine and has a joint appointment with the School of Biomedical Engineering of Shanghai Jiao Tong University, China. She is the Deputy Director of Engineering Research Center of Digital Medicine & Clinical Translation of the Ministry of Education, China, which has been the first national center that focuses on innovative translational research and development of digital medicine. Dr. Gu’s research interests include gait analysis, musculoskeletal biomechanics, wearable devices and machine learning. Her research group investigates human gait disorder affected by physical disability, neurological disorders, musculoskeletal pathology and age-related diseases, with a goal of developing gait rehabilitation interventions and improving clinical decision-making. They also focus on the development of wearable gait analysis systems and deep-learning based human pathological gait recognition.

Professor Houdijk leads the rehabilitation section of the department of Human Movement Sciences at the University Medical Center in Groningen, The Netherlands. His team takes a multidisciplinary approach to study movement pathology taking into account biomechanica, physiological and motor control aspects. From a theoretical perspective they contribute to the understanding of (functional consequences of) movement pathology, diagnostics and interventions. Professor Houdijk’s personal expertise and research interest lies in the energetics and control of human walking and the  development and evaluation of assistive technology to enhance walking ability.

Xiaoling Hu is an Associate Professor in Department of Biomedical Engineering, The Hong Kong Polytechnic University. She has served in IEEE EMBS Hong Kong and Macau Joint Chapter as a committee member more than ten years. Currently, she is the vice Chair of the chapter. Her research interests include neural engineering, hybrid robotic system, biomechatronic engineering, bio-signal processing, stroke rehabilitation, sports medicine, wearable technology, and quantitative measurement for diagnosis and evaluation.

Dr. Huang is a Professor of Biomedical Engineering in the Joint Department of Biomedical Engineering at the University of North Carolina at Chapel Hill (UNC) and North Carolina State University (NCSU) and the Director of the NCSU/UNC Closed-Loop Engineering for Advanced Rehabilitation (CLEAR) Core. Dr. Huang’s research interest lies in neural-machine interfaces for prostheses and exoskeletons, wearer-robot interaction, adaptive and optimal control of wearable robots, and human movement control. She pioneered EMG-based neural interface for robotic prosthetic legs. This work has won her the Delsys Prize in 2008. Her lab also invented novel control for multifunctional prosthetic arms based on EMG-driven musculoskeletal models. Her current research focuses on (1) optimal adaptive control of wearable robots with human-in-the-loop, (2) fault-tolerance in wearer-robot interaction, and (3) shared control of artificial limbs. She is a senior member of IEEE and member of the Society for Neuroscience and BMES.

Delaram Jarchi is a Lecturer in Artificial Intelligence (AI) and machine learning at the School of Computer Science and Electronic Engineering, University of Essex, Essex, UK. Her research has been focused on the use of wearable sensors for healthcare applications including designing new algorithms and validation of commercial wearable sensors for robust estimation of physiological parameters such as heart rate, respiratory rate and blood oxygen saturation level in very unobtrusive ways. Her research interests include Body Sensor Network, Internet of things (IoT), bio-signal processing, adaptive signal processing and machine learning.

Dr. Jeong has been working on economic and social decision-making neuroscience and its applications to Brain Engineering (Brain-Machine Interface and Brain-inspired A.I.) and Computational Psychiatry (Alzheimer’s disease, Depression and Suicide, and Addiction etc.). He performs the multimodal integration of EEG and fMRI to investigate brain dynamics underlying decision-making based on nonlinear dynamics, complex network theory, and complex system modeling methods. Particularly, he has been examining the connectome (i.e., complete wiring diagram of a whole brain) of c. elegans, Drosophila, monkey, and human to understand the organizational principles underlying the structures of the brain. Furthermore, he used the game theory and behavioral economics paradigm to monitor human decision-making processes and investigate brain dynamics of economic and social decision-making. As the applications of brain dynamics for decision-making, we utilized machine learning and nonlinear dynamics to develop brain-robot interfaces for patients with upper limb disabilities and strokes.

Dr. Jiang is interested in signal processing and machine learning methods for bio-signals, such as electromyography (EMG), electroencephalogram (EEG), electrocardiogram (ECG), and fNIRS. The applications of Dr. Jiang’s research focuses on the development of novel human-machine interfaces (HMI) based on these bio-signals and the various applications of the HMIs in brain-computer interfaces, prosthetic control and wearable devices for healthcare and beyond.

Dr Kameneva’s research interests include visual neuroscience and computational modelling; her research combines engineering tools and mathematical methods to solve open problems in biology and medicine. Dr Kameneva has expertise in control theory tools and their applications in life sciences and neuroprosthetic implants. Dr Kameneva contributes to the understanding of neural information processing in response to stimuli; she studies how electrical and optical stimulation affects neural activations and works on the development of new stimulation methods that can be used across a broad range of medical bionics applications.

Dr. Kamper’s research interests focus on the neuromechanics of the upper extremity and the restoration of upper extremity function following neurological injury. Studies of biomechanics and motor control are undertaken with the goal of identifying impairment mechanisms in individuals following neurological damage. Knowledge of these mechanisms guides the development of novel interventions, including virtual reality and soft exoskeletons.

Dr. Sang Hoon Kang is an Associate Professor in the Mechanical Engineering at UNIST and the Director of the Robotics and Rehabilitation Engineering Lab (R^2EL). Dr. Kang’s research interests include rehabilitation robotics/mechatronics and biomechanics of human movement, with an emphasis on rehabilitation medicine. He has been working on an upper-limb exoskeleton robot for neurorehabilitation, robust methods and robots for estimating upper limb mechanical impedance representing rigidity/spasticity, a real-time estimation method of knee 3D moments during stepping on a trainer for diagnosis/training of patients with knee osteoarthritis, a stepping device for the prevention and rehabilitation of the elderly with knee osteoarthritis or with sarcopenia at risk, and a device for evaluating joint proprioception under different external torques. He is a member of IEEE. He is the chair of the Technical Committee on Rehabilitation Robot, Korea Robotics Society, and Board Member of Korea Robotics Society, Korean Society of Medical Robotics, and the Bioengineering Division of The Korean Society of Mechanical Engineers.

Dr. Kaplanoglu leads the Biomechatronics & Assistive Technology Lab (BioAstLab®) at the University of Tennessee at Chattanooga. His research focuses on Biomechatronics systems; EMG and EEG controlled Prosthesis/Orthosis and Wearable Rehabilitation Robotics. Besides his biomechatronics research, he is also working on human-collaborative/industrial robot interaction with bio signals.

Dr. Hogene Kim seeks to develop practical technology and useful devices to people with special needs in rehabilitation engineering research. He is interested in understanding the human movement biomechanics in persons with neurological impairments and thus to find novel clinical interventions using diagnostic or therapeutic rehabilitation robotics and assistive technology in the community including rehabilitation exercise equipment. His research continues to extend real-world applications of the principles of design, instrumentations, and experimental methods in modern technology and product engineering for therapeutic advances in rehabilitation engineering.

Dr. Klute’s research aims to enhance the mobility of individuals with lower limb amputation. His interests in biomechanics and robotics include: development of prosthetic lower limbs to facilitate the complex maneuvering gait that occurs in everyday life, terrain adapting prostheses that improve balance, and prostheses that remain secure despite vigorous activity in demanding environments.

Dr. Ko is a Professor in Institute of Bioinformatics and Systems Biology in National Chiao Tung University, Hsinchu, Taiwan. Dr. Ko is also affiliated with Institute of Biomedical Engineering, and Brain Research Center in NCTU, Taiwan. Dr, Ko is also the visiting scholar in Institute for Neural Computation (INC) in University of California, San Diego (UCSD). Dr. Ko leads Neural Engineering Laboratory in NCTU and primary research interests are focusing on neural engineering related research, especially in brain computer interface (BCI), real-world neuroimaging (RWN), EEG-fMRI simultaneous recording, functional near-infrared spectroscopy(fNIRS), and neural computation in the neurological diseases such as neural rehabilitation, migraine, and sleep disorders. In academic service, Dr. Ko was the Associate Editors of IEEE Transactions on Neural Networks and Learning Systems (Impact Factor: 6.108, Rank: 3/104, of computer science, theory and methods) in IEEE Computational Intelligence Society (CIS) from 2010-2015 and served as the committee members in neural networks and fuzzy systems technical committees.

Professor Krishnan directs the Neuromuscular and Rehabilitation Robotics Laboratory (NeuRRo Lab) at the University of Michigan. He is a physical therapist by background and has vast clinical experience both in inpatient and outpatient rehabilitation. He received his PhD in Physical Therapy & Rehabilitation Science from the University of Iowa in 2009 and completed a 3-year postdoctoral fellowship in Robotics and Noninvasive Brain Stimulation at the Rehabilitation Institute of Chicago and Northwestern University. His research involves both mechanistic and interventional studies to facilitate our current understanding of neuromuscular function and regulation in the context of movement control and neuromuscular plasticity. He has a special interest in developing and testing low-cost technologies for the assessment and treatment of neurological and orthopedic conditions.

Dr. Uttama Lahiri is a faculty at Electrical Engineering with research interests in Virtual Reality based Human Computer Interaction used in Neuro-rehabilitation and Affective computing. In her research, she uses Eye Tracking, Physiology-based modeling, Signal Processing and Artificial Intelligence to develop Adaptive Physiology-sensitive Rehabilitation and Intervention techniques. She loves to work on application-oriented projects and solutions for children with Autism and Stroke-rehabilitation platforms for the elderly. She is leading the Intelligent Rehabilitation and Affective Computing Systems (IRACS) Laboratory at IIT Gandhinagar. She enjoys teaching both fundamental and advanced technical concepts of engineering to the undergraduate and the post-graduate students.

Dr. Song Joo Lee is a Principal Research Scientist in the Bionics Research Center at the Korea Institute of Science and Technology, Seoul, South Korea. She is also an associate professor at the division of Bio-Medical Science & Technology, KIST School, University of Science and Technology (UST) and directs the Neuromechanics lab.

Dr. Lee’s research interests stem from evidence-based translational research that aims to make biomechanical and (patho)physiological finding useful and improve human neuromuscular performance for patients with movement disorders. Her lab focuses on 1) understanding human neuromechanics by applying engineering principles and 2) applying the knowledge to develop rehabilitation strategies and assessment tools. Her research fields include neuromechanics, brain-computer interface, prosthetics and orthotics, and rehabilitation engineering.

Lorenzo Masia is Professor at Heidelberg University and Chair in Medical Technology and Biorobotics at the Institute of Computer Engineering. His primary research focuses on the design and development of robotic technology for human rehabilitation and augmentation, with special emphasis on soft wearable exosuits, novel actuation design and control implementation for human machine interfaces. With more than 10 years of experience in the field of Haptics, Robot-Aided Rehabilitation and Assistive Technology his research group was awarded multiple times in the leading conferences in Biorobotics and Robotic Rehabilitation winning two IEEE Best Student Paper Awards (IEEE ICORR2015 and IEEE Biorob2016), an IEEE Best Paper Award (IEEE ICORR2011), and finalist of “Best Human-Robot Interaction (HRI) Paper Award” at IEEE ICRA 2017 held in Singapore on May 2017.

Prof. Masia has been appointed twice Program Chair for the IEEE International Conference in Rehabilitation Robotics (ICORR) 2015 and IEEE Biorobotics and Biomechatronic Conference (BIOROB) 2016. He served as Chairman for Workshop/Tutorial for the IEEE International Conference on Robotics and Automation (IEEE ICRA 2017) held in Singapore on May 2017, and He was the co-Program Chair of IEEE ICORR 2017 (London, UK). In 2018 He served Program Chair for the International Conference on Neurorehabilitation (ICNR 2018) and Co-Program Chair, Editor in Chief and Editor of Publication for IEEE Biorob 2018.

Imran Khan Niazi received his B.Sc. degree in Electrical engineering (specialization: Biomedical Engineering) from the Riphah International University, Islamabad, Pakistan, in 2005 and his Master’s in biomedical engineering from University & FH Luebeck, Luebeck, Germany, in 2009 and later he got his PhD from Center of sensory-motor interaction, Health Science Technology Department, University of Aalborg, Aalborg, Denmark in 2012. After working as a research assistant professor for a year, he moved to New Zealand in 2013, where he is currently working as Dean of innovation and technology and Research director at the New Zealand College of Chiropractic. His research interests focus on rehabilitation engineering, neural engineering, and brain-machine interface for rehab with a patient-centred approach. He is interested in studying and understanding the altered mechanism of motor control and learning in neurological disorders to develop various technologies that can enhance the QOL of these patients. His publication can be found here.

Ilana Nisky is an associate professor in the Department of Biomedical Engineering, Ben-Gurion University of the Negev, where she is the head of the Biomedical Robotics Lab. She is also the head of the Israel-Italy Virtual Lab on Artificial Somatosensation for Humans and Humanoids. She is the recepient of the 2019 IEEE RAS Early Academic Career Award, the prestigious Alon Fellowship for young faculty from the Israeli Council for High Education, and the Marie Curie International Outgoing Fellowship from the European Commission. Her research interests include human motor control, haptics, robotics, human and machine learning, teleoperation, and robot-assisted surgery and rehabilitation, and her lab is supported by competitive grants from the Israeli Science Foundation, the Israel-US Binational Science Foundation, and the Ministry of Science and Technology. Nisky has authored more than 70 scientific publications in peer-reviewed journals and conference proceedings, and numerous abstracts in international conferences. She hopes that her group’s research will improve the quality of treatment for patients, will facilitate better training of surgeons, advance the technology of teleoperation and haptics, and advance our understanding of the brain.

Dr. Novak’s primary research areas are wearable robotics, rehabilitation robotics, serious games, and affective computing. Her overall goal is to improve human health and wellbeing through development and evaluation of novel intelligent and user-friendly technologies. For example, she has used signal processing and pattern recognition techniques to infer human workload levels, and has used this information to guide adaptive rehabilitation games. Additionally, she has used diverse signals to infer human motor intentions in wearable devices such as exoskeletons and prostheses. She is currently an Associate Professor of Electrical Engineering and Computer Science at the University of Cincinnati. She is a senior member of the IEEE and an active volunteer for several LGBTQ+ organizations.

Professor Ono leads the Health Science and Medical Engineering Lab of the Department of Electronics and Bioinformatics, School of Science and Technology at Meiji University, Japan. Her team focuses on combining human functional measurement and bio-signal processing techniques to develop novel applications in medical diagnosis and neurorehabilitation. Professor Ono’s personal expertise and research interest lie in the human cognitive neuroscience and neural engineering of cognitive/motor enhancement, utilizing the electrical and optical functional imaging/stimulation techniques (EEG, MEG, fNIRS, fMRI. PET, tDCS, and diffuse correlation spectroscopy).

Dr. Ram Bilas Pachori is currently a Professor in the Department of Electrical Engineering at Indian Institute of Technology Indore, Indore, India. He has authored 233 publications which include journal papers (143), conference papers (66), books (06), and book chapters (18). His publications have around 9000 citations with h index of 50 (Google Scholar, September 2021).
He works on the development of new methodologies based on the signal processing and machine learning for analysis and classification of biomedical signals and images (EEG, ECG, PCG, CT, X-ray, MRI, MEG, EMG, fundus images, lung sounds, etc.) with applications to diagnosis of various diseases like epilepsy, glaucoma, coronary artery disease, diabetes, congestive heart failure, septal defects, myocardial infarction, atrial fibrillation, amyotrophic lateral sclerosis, sleep disorders, alcoholism, human emotions, etc.
His broad research interests are in the areas of Signal and Image Processing, Biomedical Signal Processing, Non-stationary Signal Processing, Speech Signal Processing, Brain-Computer Interfacing, Machine Learning, and Artificial Intelligence in Healthcare.

Dr. Danilo Pani leads the Medical Devices and Signal Processing (MeDSP) Lab at the University of Cagliari, Italy. The MeDSP Lab is a biomedical engineering lab specialized in advanced biomedical signal processing, applied machine learning, and the development of medical devices and systems.

His research interests include cardiac electrophysiology, fetal electrocardiography, wearable sensors and systems for health monitoring and advanced human-computer interfaces, neurorehabilitation, and telemedicine. In the field of neural system and rehabilitation engineering, his main achievements are in the development and validation of novel polymer-based textile electrodes for EMG, telerehabilitation systems, and real-time systems for neural signal decoding in neuroprosthetics application.

Dr. Pani is a senior member of the IEEE, and co-founder officer of the Italian Chapter of the IEEE Sensors Council. He is organizer and chair of the International Summer School on Technologies and Signal Processing in Perinatal Medicine (TSPPM). He is an Italian expert in the Technical Committee 251 of CEN, Working Group 2.

Carolynn Patten, Ph.D., PT is with the University of California, Davis. Dr. Patten is a senior investigator with the VA Brain Rehabilitation Research Center where she holds Research Career Scientist status. In 2016, Dr. Patten was named as a Catherine Worthingham Fellow of the American Physical Therapy Association, the highest honor among APTA’s membership. Dr. Patten’s primary research interests involve neurophysiological and biomechanical approaches to understand the neural control of movement, mechanisms of disordered motor control in neuropathological conditions, and the capacity for motor recovery in adults following central nervous system injury. Her translational neuroscience research program uses a combination of techniques including transcranial magnetic stimulation (TMS), neurophysiological methods (EMG, motor unit recordings, reflex probes), neuroimaging and human performance. As a result, her research crosses disciplines including motor control, physiology, biomechanics, clinical medicine, rehabilitation and bioengineering. Dr. Patten’s research has been supported by awards from the: Department of Veterans Affairs, National Institutes of Health, Whitaker Foundation, Brooks Research Endowment and Foundation for Physical Therapy. Her current projects involve: 1) investigation of novel approaches (i.e., rTMS (repetitive transcranial magnetic stimulation), TDCS (transcranial direct current stimulation), motor priming, robotics) to reverse central neural inhibition and promote behavioral motor recovery following stroke; 2) identification of neurobehavioral characteristics of therapeutic responders and non-responders; 3) development of customized therapeutic interventions using computational modeling. Dr. Patten is cross-appointed in the Departments of Applied Physiology and Kinesiology (College of Health and Human Performance) and Neurology (College of Medicine). Her teaching responsibilities include Translational Neuroscience Research.

Elisabetta Peri is an assistant professor in the Signal Processing System group (Electrical Engineering Department) and member of the Biomedical Diagnostic Lab of the Eindhoven University of Technology. Her scientific research focuses on advancing biomedical signal processing to enable extramural patient monitoring. Signals of interest are electrophysiological signals for neuromuscular, cardiorespiratory and pregnancy applications as well as sweat-based biomarkers for patients monitoring.

Prof. Vinod’s research interests include digital signal processing, VLSI signal processing, Brain-Computer Interface and its applications in assistive technology & rehabilitation. He has on-going and completed external research grants from various funding agencies – Ministry of Education, Singapore, Ministry of Defence, Singapore, DSO National Laboratories, Singapore, European Aeronautic Defence & Space Company, Singapore Millennium Foundation, Civil Aviation Authority of Singapore, Airbus Group Innovations and Department of Science & Technology (Govt of India) amounting over $3.5 million as principal investigator. He has published over 275 papers in refereed international journals and international conferences, supervised and graduated 19 Ph.D. students. He is an Associate Editor of IEEE Transactions on Human-Machine Systems,IEEE Transactions on neural Systems and Rehabilitation Engineering, IEEE Transactions on Cognitive and developmental Systems, IEEE Systems, Man & Cybernetics Magazine and Springer Journal of Circuits, Systems & Signal Processing and a Senior Member of IEEE. Vinod was a Co-Chair (Brain-Machine Interface Systems) of IEEE Systems, Man & Cybernetics Society for which he won the award of the ‘Most Active Technical Committee in Human-Machine Systems’ of IEEE Systems, Man and Cybernetics Society in three consecutive years – 2015, 2016 and 2017.Vinod was a Co-Chair (Brain-Machine Interface Systems) of IEEE Systems, Man & Cybernetics Society for which he won the award of the ‘Most Active Technical Committee in Human-Machine Systems’ of IEEE Systems, Man and Cybernetics Society in three consecutive years – 2015, 2016 and 2017.Vinod was a Co-Chair (Brain-Machine Interface Systems) of IEEE Systems, Man & Cybernetics Society for which he won the award of the ‘Most Active Technical Committee in Human-Machine Systems’ of IEEE Systems, Man and Cybernetics Society in three consecutive years – 2015, 2016 and 2017.

Dr. Philip Requejo is the Director of the Rehabilitation Engineering Department and Associate Director of the Pathokinesiology Laboratory at Rancho Los Amigos National Rehabilitation Center. He serves as a faculty member at the University of Southern California in the Departments of Biomedical Engineering, Human and Evolutionary Biology, and Biokinesiology and Physical Therapy. He also is the Director of Rehabilitation Engineering Department and Co-Director of the RERC on Technologies for Successful Aging with Disability at the Model Systems Knowledge Translation Center (MSKTC). The MSKTC is a national center that helps facilitate the knowledge translation process to make research meaningful to those with Spinal Cord Injury (SCI), Traumatic Brain Injury (TBI) and Burn Injury (Burn). He received his undergraduate degree in Electrical Engineering and PhD degree in Kinesiology from the University of Southern California. He is a faculty in the Department of Biomedical Engineering and Department of Kinesiology, and Department of Biokinesiology and Physical Therapy at USC. His research primarily falls into several broad areas of rehabilitation engineering and biomechanics research; focusing on the design, analysis, and implementation of technologies to preserve and enhance mobility in those with spinal cord injury- particularly focusing on the biomechanics of the weight-bearing shoulder to prevent and treat shoulder pain.

Dr. Emily Rogers-Bradley is an Assistant Professor at the University of Calgary in the departments of Mechanical and Manufacturing Engineering and Biomedical Engineering. Dr. Rogers-Bradley is the director of the Adaptive Bionics Lab, researching the design of quasi-passive prostheses and exoskeletons that adapt to speed, terrain, and ground surface for walking and running optimization. Her research merges precision machine design, biomechanics, and robotics for the development of new types of prostheses and exoskeletons. Prior to joining the University of Calgary she obtained her PhD in Mechanical Engineering from Massachusetts Institute of Technology in February 2023. She received a SM in Mechanical Engineering from MIT in 2019 and a SB in Biomedical Engineering from Harvard University in 2015. She has also spent several years in industry as a Mechatronics Engineer at Ekso Bionics, where she designed robotic exoskeletons for stroke and spinal cord injury rehabilitation. Her work has been featured in the PBS NOVA documentary ‘Augmented’, a permanent exhibit in the Boston Museum of Science, and she is a named inventor on 3 patents.

Massimo Sartori is an Associate Professor at the University of Twente where he directs the Neuromechanical Modelling and Engineering Lab. Dr Sartori’s primary research focuses on interfacing assistive robotic technologies with the neuromuscular system for enhancing human movement. A distinctive trait of Dr Sartori’s approach is that of fusing multi-scale musculoskeletal modelling formulations with bioelectrical recordings to investigate basic mechanisms of movement neuromechanics in vivo. On these topics he has been awarded prestigious personal grants (ERC Starting Grant, Marie Skłodowska-Curie Fellowship), is PI in large-scale consortium-based projects (i.e. H2020 EFRO GUTs), and received several awards (e.g. NIH/OpenSim Outstanding Research). In 2018, Dr Sartori served as Workshop Chair at IEEE BioRob.

Marianna Semprini got a BS in Biomedical Engineering and a MS in Bioengineering (Neuroengineering curriculum) both at the University of Genoa (Italy) in 2004 and 2007 respectively. In 2007 she was research fellow at Northwestern University (Chicago, IL, USA). In 2011 she received a PhD in Robotics, Neurosciences and Nanotechnologies from the Istituto Italiano di Tecnologia (IIT). 

She is currently Clinical Research Team Manager at IIT-INAIL Rehab Technologies Lab of the Italian Institute of Technologies. Her current interests are  neurorehabilitation, neuroprostheses and neural control of movement

Dr. Sharma leads Neuromuscular Control and Robotics lab in the Joint Department of Biomedical Engineering at NC State University and UNC-Chapel Hill. His research lab focuses on the modeling, optimization, and control of functional electrical stimulation (FES) and hybrid exoskeletons that combine FES and a powered exoskeleton. The lab also researches ultrasound imaging-derived and surface electromyography signals that quantify muscle contractility changes during FES-evoked and voluntary limb movements. The research uses a variety of control design tools ranging from Lyapunov-based nonlinear control design, model predictive control, dynamic optimization, neural networks(NN)-based adaptive control, NN-based optimal control, and data-driven modeling and control.

Lab Website: http://www.sharmalabncsu.org/

Dr. Shull’s research interests include human performance measurement and analysis, wearable sensors, biomechanics of locomotion, and machine learning. His laboratory develops wearable systems to explore principles of human movement and movement modification. His group combines robotic, haptic, and biomechanics principles to create unique sensors, real-time models, sensor fusion algorithms, and novel feedback devices. They focus on human movement in laboratories, in clinics, and in natural environments such as a home or office. Target applications are in medicine such as osteoarthritis and stroke, and in athletics such as basketball and running.

Dr Siuly’s research interest includes Biomedical Signal Processing, Detection and Prediction of Neurological Abnormality from Brain Signal Data (e.g. electroencephalogram (EEG) signal data), Brain-Computer Interface, Machine Learning, Deep learning, Pattern Recognition, Artificial Intelligence and Medical Data Mining. She already made significant contributions to the mentioned areas that have been published in top leading journals and conferences. The key aim of her current research is to develop an innovative computer-assisted analysis system that can be used for detecting and predicting neurological abnormalities from EEG signal data. This system will assist medical specialists/experts to rapidly identify neurological problems and provide appropriate treatments and care information for patients.

Dr. Junfeng Sun is a full professor of biomedical engineering at School of Biomedical Engineering and Med-X Research Institute, Shanghai Jiao Tong University. He is IEEE Senior Member, Associate Editor of IEEE Transactions on Neural Systems & Rehabilitation Engineering (2022-) and Medical and Biological Engineering and Computing (2018-). His research interests include transcranial ultrasound stimulation techniques, neuroimaging techniques and analysis methods, and applications of these techniques to cognitive function and therapeutic intervention for brain diseases including depression, schizophrenia, and stroke.  He has published more than 70 papers in SCI journals.

Dr. Yu Sun is a Research Professor in the Department of Biomedical Engineering at Zhejiang University and is also affiliated with the Department of Radiology, the Children’s Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, China.  Dr. Sun’s research emphasis has been placed on the integration of the neural engineering, cognitive sciences, and virtual reality in service of insights into functions of the brain, cognition, and behavior. In particular, his research work of brain connectome studies of neuroergonomics and brain state monitoring has provided nascent insights into the neural mechanisms of mental workload/fatigue. Another area of interest is brain-computer interface and its clinical applications such as neural rehabilitation. In academic service, Dr. Sun is also an associate editor of the journal Medical & Biological Engineering & Computing (MBEC), and a youth corresponding expert of the journal Engineering.

Karen L. Troy directs the Musculoskeletal Biomechanics Laboratory, where she investigates questions related to musculoskeletal health and structure, physical activity, and biomechanics, in healthy and clinical populations. She has expertise in computational biomechanics and finite element modeling, aging and fall avoidance, and medical imaging. She has worked on clinical trials targeting bone health in both healthy women and people with spinal cord injury. She collaborates with physicians in the areas of orthopaedic trauma, radiology, rheumatology, and physical medicine and rehabilitation.

Dr. Carmen Vidaurre is Ramon y Cajal fellow at the public University of Navarre, Dp of Statistics, Informatics and Mathematics, in Spain. From 2008 to 2016, she was a member of the Machine Learning Group at TU-Berlin, Berlin, Germany, where she was in charge of several national and international research projects. Between 2006 and 2008, she was Marie Curie fellow at the IDA group of the Fraunhofer Institute in Berlin, Germany. In 2006 she was post-doc researcher at CIMA in Pamplona, Spain. From 2002 to 2005 she was guest researcher at the TU-Graz, Institute of Biomedical Engineering, in Austria, where she pursued her PhD in the field of Brain-Computer Interfacing.

Her research interests are about the development of optimized multimodal methods for the understanding of motor control and their application to functional motor rehabilitation. She is also interested in the development of principled optimized procedures to ease the processing of neuroscientific data and to increase our understanding of the nervous systems.

Dr. Vuckovic’s research interests are in cortical basis of sensory motor control and neuroplasticity. Recently she has been developing novel Brain Computer Interface strategies for patient self-managed therapies. She is also interested in EEG markers of neurological conditions such as neuropathic pain and in development and clinical testing of EEG and fMRI based neuromodulatory therapies based on single and multiple users.

Dr. Wang received his PhD in Computer Science and Engineering from Zhejiang University, China in 2007. From 2007 to 2010, he worked as a postdoctoral fellow at the Department of Information Engineering, The Chinese University of Hong Kong. Currently, he holds the position of Professor at the College of Computer Science and the Qiushi Academy for Advanced Studies, Zhejiang University. His research interests lie in the areas of brain-computer interface, artificial intelligence, and machine learning. Dr. Wang’s research aims to improve the quality of life for people with tetraplegia by enabling direct cortical control of robotic devices, and to enhance the quality of life for patients with treatment-resistant epilepsy or depression through the development of closed-loop brain stimulation methods.

Dr. Wong’s research interests are broadly separated into neural prostheses and systems neuroscience. In the field of neural prostheses, Dr Wong is interested in brain machine interfaces for upper limb movement control, cortical and retinal stimulation studies (Bionic vision), improved cochlear implant fitting techniques, new electrode technologies and the general use of local field potentials to improve neural prostheses. On the basic neuroscience side, Dr Wong studies the role of the local field potentials in communication across brain areas and in multi-effector decision making, reward learning and movement planning. This is done with a mix of recording techniques from in vivo electrophysiology, to EEG, MEG and fMRI.

Dr. Wu received his PhD in Electrical Engineering from the University of Southern California. He is now Professor in the School of Automation, Huazhong University of Science and Technology, Wuhan, China, and directs its Brain-Computer Interface and Machine Learning Lab. His research interests include affective computing, brain-computer interfaces, computational intelligence, and machine learning. He has published over 100 papers in these areas. He is also an Associate Editor of the IEEE Computational Intelligence Magazine, and the IEEE Transactions on Human-Machine Systems.

Dr. Yao’s research interests include EEG inverse and forward, quantitative EEG (qEEG), simultaneous EEG and fMRI, and Brain-Apparatus Conversation (Bacomics). He got his first PhD in Applied Geophysics (1991) at Chengdu University of Technology, and second PhD in Biomedical Science (2005) at Aalborg University. He is a full professor since 1995, a Changjiang Scholar Professor (2006), and the Director of Key Laboratory for NeuroInformation of Ministry of Education of China, and the Director of International Joint Research center for Neuroinformation of Ministry of Science and Technology of China. He is an AIMBE Fellow (2017) and “Roy John Award” winner (2018).

Matías Zañartu is an Associate Professor in the Department of Electronic Engineering and the Head of the Biomedical Engineering research of the Advanced Center for Electrical and Electronic Engineering at Universidad Técnica Federico Santa María in Valparaiso, Chile. He received his Ph.D. and M.S. degrees in electrical and computer engineering from Purdue University, West Lafayette, USA, and his B.S. in acoustical engineering from Universidad Tecnológica Vicente Pérez Rosales, Santiago, Chile. His interests are centered on the development of digital signal processing, system modeling, and biomedical engineering tools that involve speech, audio, and acoustics. His recent research efforts have revolved around developing quantitative models that describe nonlinear effects in human speech production, and applying these physiological descriptions for the development of communication and clinical technologies.

Dr. Ping Zhou is a Professor in Physical Medicine and Rehabilitation at the University of Texas Health Science Center at Houston (UTHealth), TX, USA. He directs the NeuroMyo Engineering for Rehabilitation Laboratory of the TIRR Memorial Hermann Hospital, Houston, TX, USA, and the Neuromuscular Performance & Rehabilitation Laboratory of the Guangdong Work Injury Rehabilitation Hospital, Guangzhou, China. His current research interests include biomedical signal (in particular, EMG) processing, motor unit pathophysiology after neurological injuries, noninvasive electrodiagnosis of neuromuscular diseases, advanced myoelectric control, and assistive devices for neurorehabilitation.