ISEK-JEK Tutorials
ISEK is pleased to announce the novel ISEK- JEK Tutorials, a series of online events starting in Summer 2021. The ISEK- JEK Tutorials are based on tutorial papers published in the Journal of Electrophysiology and Kinesiology (JEK).
They are intended for students to provide technical background on some fundamental topics in Electrophysiology and Kinesiology research, and most importantly, to answer questions that trainees might have on these topics.
Each event in this series will consist of 90 minutes of live presentations and Q&A periods.
ISEK Tutorials will be recorded and available on the website.
There are no fees to participate in the ISEK – JEK Tutorials, but you must register to participate.
Webinar Recording Disclaimer
Please note that webinars are recorded. By your presence at an ISEK webinar, you consent to be photographed, filmed and/or otherwise recorded. Your registration constitutes your consent to such photography, filming and/or recording and to any use for any purpose in accordance with the Society mission and standard of conduct. You are welcome to keep your camera off during these events, you and not the Society, is responsible for these setting options.
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Past Events
Open source software to decompose and edit EMG signals
Tuesday, December 5 at 8:00-9:30am UK time
In partnership with the International Motoneuron Society and MotusAcademy
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Presenters
Simon Avrillon
Department of Bioengineering, Imperial College London
My scientific journey began in 2015 at the University of Paris Saclay, France, where I was awarded a PhD scholarship from the French Ministry of Research and worked with the French Institute of sport. After these initial experiences, I sought international mobility to learn new methods and expand the scope of my knowledge. I spent two months at the University of Queensland, Brisbane, Australia, in the Department of Biomedical Science; two years at Northwestern University, Chicago, United States, in the Department of Physical Medicine and Rehabilitation; and I have been working at Imperial College London, United Kingdom, in the Department of Bioengineering for the past one and a half years.
The overarching research goal of my early career is to understand how the nervous system coordinates its effectors, specifically the motor units, to produce movements in both health and disease. My research focuses on studying how the nervous system transmits common inputs to multiple motor units in the spinal cord in order to reduce the dimensionality of movement control. To support this research, I have contributed to the optimization of electrode design and algorithms that separate electromyographic signals into single motor unit activity. Additionally, I have developed methods and software to decode the activity of individual motor units in real time, utilizing blind-source separation and artificial neural networks.
Dario Farina
Department of Bioengineering, Imperial College London
Professor Farina has been Full Professor at Aalborg University, Aalborg, Denmark, (until 2010) and at the University Medical Center Göttingen, Georg-August University, Germany, where he founded and directed the Institute of Neurorehabilitation Systems (2010-2016) until he moved to Imperial College London as Chair in Neurorehabilitation Engineering. His research focuses on biomedical signal processing, neurorehabilitation technology, and neural control of movement. Within these areas, he has (co)-authored approximately 400 papers in peer-reviewed Journals and >500 conference abstract and papers. He has been the President of the International Society of Electrophysiology and Kinesiology (ISEK) (2012-2014) and is currently the Editor-in-Chief of the official Journal of this Society, the Journal of Electromyography and Kinesiology. He is also currently an Editor for IEEE Transactions on Biomedical Engineering and the Journal of Physiology.
Decoding motor unit activity from high-density EMG signals: methodological considerations and recent advances
In partnership with the International Motoneuron Society
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Agenda
Aleš Holobar (45 min)
- Introduction to motor unit (MU) identification: spatiotemporal properties of MU electrical activity
- Spatial, temporal and MU filters
- Blind source separation approach to MU identification: learning of MU filters and their application to HDEMG signals
- Banks of MU filters and their efficiency in different skeletal muscles: isometric conditions
- Banks of MU filters and their efficiency in different types of contractions: isometric, dynamic and elicited contractions
Discussion and questions (30 min)
Reference materials
For engineers and experts in signals processing:
- Holobar, A., Farina D., 2021, Noninvasive Neural Interfacing With Wearable Muscle Sensors: Combining Convolutive Blind Source Separation Methods and Deep Learning Techniques for Neural Decoding. IEEE Signal Processing Magazine 38, 103-118.
For experimenters interested in a correct use of the methods:
- Del Vecchio A, Holobar A, Falla D, Felici F, Enoka RM, Farina D. Tutorial: Analysis of motor unit discharge characteristics from high-density surface EMG signals. J Electromyogr Kinesiol. 2020 Aug;53:102426. doi: 10.1016/j.jelekin.2020.102426
- Hug F, Avrillon S, Del Vecchio A, Casolo A, Ibanez J, Nuccio S, Rossato J, Holobar A, Farina D. Analysis of motor unit spike trains estimated from high-density surface electromyography is highly reliable across operators. J Electromyogr Kinesiol. 2021 Jun;58:102548. doi: 10.1016/j.jelekin.2021.102548.
For physiologists experts in motor unit studies:
- Farina D, Negro F, Muceli S, Enoka RM. Principles of Motor Unit Physiology Evolve With Advances in Technology. Physiology (Bethesda). 2016 Mar;31(2):83-94. doi: 10.1152/physiol.00040.2015
Presenter
Aleš Holobar
Aleš Holobar received his PhD in computer science from the University of Maribor, Slovenia (2004). He is currently a Professor and the Head of the Institute of Computer Science at the Faculty of Electrical Engineering and Computer Science, University of Maribor. His research focuses on digital signal processing, human–machine interfaces, biomedical signal processing, and rehabilitation engineering. He has coauthored more than 100 articles in peer-reviewed journals.
An introduction into the analysis of stabilizing feedback control of walking
Stable gait, defined as gait that does not lead to falls, requires control of the body center of mass relative to the base of support. Model studies suggest that this requires active, feedback control, especially in the mediolateral direction. In older adults and in individuals with neurological or orthopedic disorders that affect walking ability falls during gait are a common cause of injuries, hospitalization and loss of independence. In this tutorial, we will discuss how gait analysis can be used to assess impairments of stabilizing feedback control of gait. We will present methods ranging from those that require limited input data (e.g. position data of markers placed on the feet and pelvis only) and relatively simple analyses to those that require full-body kinematics and musculoskeletal modeling and we will discuss what information on feedback control can be gleaned from each of these.
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Presenters
Prof.dr. Jaap van Dieën
Department of Human Movement Sciences, Vrije Universiteit Amsterdam, Amsterdam Movement Sciences
Jaap van Dieen is professor biomechanics and head of the department of Human Movement Sciences at the Vrije Universiteit Amsterdam. His research focuses on: 1) Control of posture and gait (with a focus on trunk control): how can control be assessed, what are the determinants of control quality, how is this affected by disorders, and how can it be improved? 2) Low-back loading: how can it be assessed and how can it be reduced? 3) Measurement tools for biomechanical and neurophysiological assessment for application outside the lab. Jaap van Dieën has successfully supervised over 60 PhD students and (co-) authored over 500 papers in international scientific journals. He is currently the editor in chief of the section Biomechanics and Control of Human Movement of Frontiers in Sports and Active Living and serves on several editorial boards
Dr. Maarten Afschrift
Department of Human Movement Sciences, Vrije Universiteit Amsterdam, Amsterdam Movement Sciences.
Maarten Afschrift is an assistant professor at the department of Human Movement Sciences at the Vrije Universiteit Amsterdam. His research focuses on: 1) perturbation experiments and simulations to gain insight in human balance control and in the factors that limit balance control in elderly. 2) balance supporting control of wearable robotic devices. 3) Simulations of human movement to predict the effect of mechanical interventions, such as an exoskeleton, on human movement.
Dr. Sjoerd Bruijn
Department of Human Movement Sciences, Vrije Universiteit Amsterdam, Amsterdam Movement Sciences.
Sjoerd Bruijn is an associate professor at the department of Human Movement Sciences at the Vrije Universiteit Amsterdam. His research focuses on how most humans can walk on two legs with such remarkable ease, and why pathology and ageing decrease this ability; in short, he studies “human gait stability”. In doing so, he tries to tackle 3 main questions; 1. How can we quantify gait stability properly? 2. How do humans achieve a stable gait pattern (what is the role of passive mechanics, what is the role of control? At which levels in the nervous system does control originate?), and 3. Can we apply the mechanisms we studied in the second question to help people with impaired gait stability? While he usually takes a more fundamental approach to these questions, he often collaborate with clinical partners.
Surface EMG detection in space and time, conditioning and pre-processing
This webinar is oriented to non-engineers and is based on the first two Tutorials published in the Journal of Electromyography and Kinesiology concerning surface EMG:
Merletti R., Muceli S., Tutorial. Surface EMG detection in space and time: best practices. Journ. of Electromyogr. and Kinesiol., 2019; 49:doi.org/10.1016/j.jelekin.2019.102363
Merletti R., Cerone G.L. Tutorial. Surface EMG detection, conditioning and pre-processing: best practices, Journ. of Electromyogr. and Kinesiol., 2020;
54 102440, doi:10.1016/j.jelekin.2020.102440
A short introduction describes the barriers to the widespread use of sEMG, as addressed in the Frontiers project https://www.frontiersin.org/research-topics/11157, and the need to overcome them.
The lecture of Dr. Muceli addresses the best practices concerning sEMG electrode geometry and location. The lecture of Dr Cerone addresses the best practices concerning amplification, filtering and conditioning of the raw sEMG signal. Both lectures provide a simple technical bases for proper sEMG detection and recording by clinical operators.
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Agenda
Roberto Merletti
- The potential of sEMG observation and measurements for rehabilitation operators
- The need for teaching rehabilitation operators about sEMG
- The results of the Frontiers Project on barriers to clinical use of sEMG
- Future perspectives (large HDsEMG systems covering a limb)
Silvia Muceli
- The surface EMG image and its sampling with an electrode pair or an electrode grid
- The averaging (low pass filtering) effect of the electrode area
- The propagation of Motor Unit action potentials
- End-of-fiber effect and crosstalk
Discussion: 10 min
Giacinto Luigi Cerone
- The coupling between body-electrodes and biopotential amplifiers. Rejection of power line interference and relevance of Wireless Systems
- The importance of skin treatment to lower impedances and artifacts
- Conditioning of sEMG signals. Concept of filter (low pass, high pass, notch)
- Artifacts in the EMG recoding
- Concept of sampling and conversion into binary numbers.
Discussion: 10 min
Presenters
Giacinto Luigi Cerone, Ph.D
Laboratory for Engineering of the Neuromuscular System, Dept of Electronics and Telecommunications, Politecnico di Torino, Turin, Italy
Giacinto Luigi Cerone obtained the M.Sc. degree and the Ph.D in Biomedical Engineering summa cum laude from Politecnico di Torino, Torino, Italy, in 2014 and 2019 respectively. Currently he is a Post-Doc Researcher at the Laboratory for Engineering of the Neuromuscular System at Politecnico di Torino. In 2020 he was awarded as Innovative Engineer of the Year by the Turin Engineering Association. His main activity concerns the hardware, firmware, software design and certification of biomedical instrumentation. His research activity with is mainly focused on the design of modular, wireless and embedded systems for the acquisition of electrophysiological signals, the neuromuscular electrical stimulation and the tele-monitoring of vital parameters.
Roberto Merletti, Ph.D., ISEK Fellow
Former Full Prof. of Rehabilitation Engineering, Lab. For Engineering of the Neuromuscular System, Politecnico di Torino, Italy
Prof. Roberto Merletti graduated in Electronics Engineering from Politecnico di Torino, Italy, and obtained his M.Sc. and PhD in Biomedical Engineering from the The Ohio State University, USA. He has been Associate Prof. of Biomedical Engineering at Boston University where he was also Research Associate at the NeuroMuscular Research Center. He has been Full Prof, of Rehabilitation Engineering at Politecnico di Torino where he established, in 1996, the Laboratory for Engineering of the Neuro-muscular System (LISiN) of which he has been Director up to 2015. He has trained at LISIN more than 70 researchers (15 doctoral students) from various countries.
Silvia Muceli, Ph.D.
Assistant Professor, Electrical Engineering Chalmers University of Technology, Sweden
Silvia Muceli is Assistant Professor in Life Science Engineering at Chalmers University of Technology, Gothenburg, Sweden. She received her MSc in Electronics Engineering from the University of Cagliari, Italy, in 2007, and PhD in Biomedical Science and Engineering from Aalborg University, Denmark, in 2013. She worked as postdoctoral researcher at the University Medical Center Göttingen, Georg-August University, Germany, and Imperial College London, UK, until 2019. Her main research interests include surface and intramuscular electromyography, biomedical signal processing and modelling, bioelectrode design, neurophysiology of movement, sensorimotor development, and advanced prosthetic control.