Goals: Part 1 will discuss the fundamentals, methodologies and recommendations for recording sEMG signals. Part 2 will discuss the use of EMG in the assessment of muscle performance and endurance and provide a live demonstration.
Who should attend? The workshop is designed for researchers just beginning to use EMG. However, the intermediate and advanced EMG researcher will be able to refresh their knowledge of the science and ask specific questions to experts in the field.

The workshop will address two issues that have a fundamental bearing on the successful outcome of any investigation that employs the use of the surface EMG signal (sEMG). The first is the design of the sensor for recording the sEMG signal, and the second is the methodology required to obtain signals with minimal contamination from extraneous noise sources. If the sEMG signal is contaminated with noise, which is any signal unrelated to the one you are attempting to detect, its fidelity will be compromised. The noise sources may be indistinguishable from that of the sEMG signal; thus, attempts at improving the quality and fidelity of the signal by subsequent signal processing techniques may not be effective. At times, the contaminants may have similar characteristics as the signal and the investigator may not even be aware of the contamination, leading to false interpretations of the sEMG signal.

If you use information from the sEMG signal - either for research or especially for clinical purposes - you must know how to record an sEMG signal so that it reliably represents the activity of the muscle of interest. The literature is replete with unfounded advice and seemingly erroneous interpretations of the content of the signal. Even if your application of sEMG is straightforward and you believe it to be relatively insensitive to error, you will still benefit from the use of proper technology and proper methodology. This “best practice” will allow you to review the collected signals at a later time and glean different information from them.

The workshop will discuss the design characteristics of sensors that reduce the noise contamination. We will also provide recommendations for reducing the contamination of the sEMG signal, justified with empirical evidence. Additionally, we will describe and explain “best practice” methodologies for recording sEMG signals and present a hands-on demonstration of these techniques in practice.

This workshop is designed for researchers at the early stage of their EMG usage. However, the intermediate and advanced EMG user should find the workshop to provide a convenient refresher.

Light snacks, coffee/tea, and lunch will be provided.

Dr. Carlo J. De Luca
Delsys Inc., Boston USA
NeuroMuscular Research Center, Boston University, Boston USA

Dr. Carlo J. De Luca is the Director, NeuroMuscular Research Center, Professor of Biomedical Engineering, Research Professor of Neurology, Boston University, Boston, MA.

Dr. De Luca focuses on the application of engineering principles to the understanding of motor control and the development of objective patient treatment procedures. Specifically, he is interested in:

• Using innovative technology to identify motor unit action potentials from the surface EMG signal to explore the control scheme that regulates their activation and firing in the healthy neuromuscular system. This is a continuation of work that Dr. De Luca has done over the past four decades.
• Leading a team developing algorithms for identifying dysfunctional movements in neurologically impaired patients for the purpose of providing clinicians with high-resolution reports on mobility and medication-effect for improving patient management.
• Developing a physiologically-based mathematical model describing the generation of muscle force that allows for hypothesis testing of the influence of firing characteristics and muscle fiber mechanics.
• Exploring the development of technology for detecting and analyzing surface EMG signals for the purpose of facilitating and expanding the use of the EMG signal in clinical, movement science, sport science, and ergonomics environments.

Dr. James Richards
University of Central Lancashire, Lancashire UK

Dr. Jim Richards worked for 10 years as a senior lecturer at University of Salford, and has taught biomechanics to prosthetists/orthotists, podiatrist, physiotherapists and sport therapists.

Dr. Richards was appointed Professor in Biomechanics in the Department of Allied Health Professions at University of Central Lancashire in 2004. Dr. Richards has considerable experience in conducting clinical research including: clinical application of biomechanics, development of new assessment tools for chronic diseases, conservative and surgical management of orthopaedic and neurological conditions, and development of evidence based approaches for improving clinical management and rehabilitation.

The current focus of Dr. Richards’s work is to encourage inter-professional research and to develop direct parallels with research to the ‘real world’ of allied health work and sports medicine. Professor Richards is also a visiting Professor to the Department of Orthopaedics and Traumatology at the University of Perugia and holds Honorary Research Fellowships at several hospitals.

Dr. Richards has authored many research papers and written and edited a number of textbooks, including Biomechanics in Clinic and Research (2008) and the forthcoming 5th edition of Whittle’s Gait Analysis. He has also contributed to Tidy’s Physiotherapy (2003, 2008, 2011) and the 10th edition of Mercer’s Orthopaedic Surgery (2010).

For a complete listing of publications click here.

Basmajian JV and De Luca CJ.  Muscles Alive (5th edition), Williams and Wilkins, Baltimore, MD, 1985.

Roy SH, De Luca CJ, Emley M, Classification of back muscle impairment based on the surface electromyographic signal.  Journal of Rehabilitation Research and Development, 34:  405-414, 1997.

De Luca CJ.  The use of surface electromyography in biomechanics.  Journal of Applied Biomechanics, 13: 135-163, 1997.

Roy SH, De Luca G, Cheng S, Johansson A, Gilmore LD, and De Luca CJ. Electro-Mechanical stability of surface EMG sensors.  Medical & Biological Engineering & Computing, 45: 447-457, 2007.

Roy SH, Cheng MS, Chang SS, Moore J, De Luca G, Nawab SH, and De Luca CJ.  A combined sEMG and accelerometer system for monitoring functional activity in stroke.  IEEE Transactions on Neural Systems and Rehabilitation Engineering, 17 (6): 585-594, 2009.

De Luca CJ, Gilmore LD, and Roy SH.  Filtering the Surface EMG signal: Movement artifact and baseline noise contamination.  Journal of Biomechanics – in press 2010.

Richards J, P Holler, B Bockstahler, B Dale, M Mueller, J Burston, J Selfe, D Levine. A comparison of human and canine kinematics during level walking, stair ascent, and stair descent. Veterinary Medicine Austria, Special Issue on Movement Science in Animals, 2010.

Selfe J, Richards J, Thewlis D, Kilmurray S. The Biomechanics of Step Descent under Different Treatment Modalities used in Patellofemoral Pain. Gait and Posture, 2008.

Richards J, Thewlis D, Selfe J, Cunningham A, Hayes C. The biomechanics of single limb squats at different decline angles. Journal of Athletic Training, 2008.

Thewlis D, Richards J, Bower J. Discrepancies in Knee Joint Moments Using Common Anatomical Frames Defined by Different Palpable Landmarks. Journal of applied biomechanics, 2008.

Thewlis D, Richards J, Hobbs SJ. The Appropriateness Of Methods Used To Calculate Joint Kinematics. Journal of Biomechanics, 2008.

Goals: The workshop will discuss and provide live demonstration of the features and benefits a novel EMG decomposition technology that can directly measure changes in the firing behavior of motor units as a consequence of training, exercise, skill, and aging.
Who should attend? Anyone interested in muscle physiology, motor unit recruitment, muscle fatigue, or strength training.

The workshop will discuss a new technology, called Precision Decomposition of sEMG signal (PDsEMG), that is capable of automatically decomposing the sEMG signal into the constituent motor unit action potentials. This novel technology provides a host of parameters related to the firing behavior of motor units such as: firing interval statistics, firing rate, recruitment and de-recruitment force thresholds, and the shape of the action potential.

For nearly a century, the surface EMG (sEMG) signal has been used as a metric for muscle performance. Sport scientists, other researchers, and clinicians have used the amplitude of the sEMG signal to measure the force produced by a muscle, the presence and absence of the sEMG signal to determine the activation timing of a muscle, the amount of co-activation of multiple muscles, as well as the shift in the frequency spectrum of the sEMG signal for assessing muscle fatigue. For over five decades, new EMG parameters have not surfaced.

The PDsEMG system typically extracts 25 to 40 motor unit action potential trains from the sEMG signal collected during a single isometric contraction sustained for 20 to 30 seconds. In rare cases it has provided up to 50 trains. The average accuracy of the firing instances has been measured to be 92.5% in isometric contractions up to maximal force level. In some cases the accuracy reached 97%.

For sport scientists, these parameters enable investigations on muscle performance that directly measure changes in the firing behavior of motor units as a consequence of training, exercise, skill, and aging.

The workshop will explore the concepts behind the technology and a demonstration of the device will be provided. Depending on time constraints, participants may be able to test the system on themselves.

Light snacks, coffee/tea, and lunch will be provided.

Dr. Carlo J. De Luca
Delsys Inc., Boston USA
NeuroMuscular Research Center, Boston University, Boston USA

Dr. Carlo J. De Luca is the Director, NeuroMuscular Research Center, Professor of Biomedical Engineering, Research Professor of Neurology, Boston University, Boston, MA.

Dr. De Luca focuses on the application of engineering principles to the understanding of motor control and the development of objective patient treatment procedures. Specifically, he is interested in:

• Using innovative technology to identify motor unit action potentials from the surface EMG signal to explore the control scheme that regulates their activation and firing in the healthy neuromuscular system. This is a continuation of work that Dr. De Luca has done over the past four decades.
• Leading a team developing algorithms for identifying dysfunctional movements in neurologically impaired patients for the purpose of providing clinicians with high-resolution reports on mobility and medication-effect for improving patient management.
• Developing a physiologically-based mathematical model describing the generation of muscle force that allows for hypothesis testing of the influence of firing characteristics and muscle fiber mechanics.
• Exploring the development of technology for detecting and analyzing surface EMG signals for the purpose of facilitating and expanding the use of the EMG signal in clinical, movement science, sport science, and ergonomics environments.

Dr. Paola Contessa
NeuroMuscular Research Center, Boston University, Boston USA

Dr. Paola Contessa received a M.Sc. and a Ph.D. in Biomedical Engineering from University of Padova, Padova, Italy. During her Ph.D., she was appointed as visiting Research Assistant at the NeuroMuscular Research Center, Boston University, Boston, USA.

She is currently a Research Associate at the Neuromuscular Research Center at Boston University, where her research focuses on motor control and muscle force generation strategies.

For a complete listing of publications click here.

Findings

De Luca CJ, LeFever RS, McCue MP, and Xenakis AP. Behavior of human motor units in different muscles during linearly-varying contractions. Journal of  Physiology, 329: 113-128, 1982.

De Luca CJ, LeFever RS, McCue MP, and Xenakis AP. Control scheme governing concurrently active human motor units during voluntary contractions. Journal of Physiology, 329: 129-142, 1982.

De Luca CJ, Foley PJ, and Erim Z.  Motor unit control properties in voluntary isometric isotonic contractions.  Journal of Neurophysiology, 76:  1503-16, 1996.

Adam A, De Luca CJ, Erim Z. Hand dominance and motor unit firing behavior.  Journal of Neurophysiology, 80: 1373-1382, 1998.

Erim Z, Beg MF, Burke DT, and De Luca CJ.  Effects of aging on motor unit control properties. Journal of Neurophysiology, 82: 2081-2091, 1999.

De Luca CJ and Erim Z.  Common drive in motor units of a synergistic muscle pair. Journal of Neurophysiology, 87: 2200-2204, 2002.

Adam A and De Luca CJ. Recruitment order of motor units in human Vastus Lateralis muscle is maintained during fatiguing contractions. Journal of Neurophysiology, 90: 2919-2927, 2003.

Adam A and De Luca CJ. Firing rates of motor units in human vastus lateralis muscle during fatiguing isometric contractions. Journal of Applied Physiology,  99: 268-280, 2005.

De Luca CJ, Adam A, Wotiz R, Gilmore LD, and Nawab SH. Decomposition of surface EMG signals. Journal of Neurophysiology, 96: 1646-1657, 2006.

Nawab SH, Wotiz RP, and De Luca CJ. Decomposition of indwelling EMG signals. Journal of Applied Physiology, 105: 700-710, 2008.

De Luca CJ, Gonzalez-Cueto JA, and Adam A. Motor unit recruitment and proprioceptive feedback decrease the common drive. Journal of Neurophysiology, 101:1620-1628, 2009.

Contessa P, Adam A, and De Luca CJ. Motor unit control and force fluctuation during fatigue. Journal of Applied Physiology, 107: 235-243, 2009.

Technology

De Luca CJ, Adam A, Wotiz R, Gilmore LD, and Nawab SH. Decomposition of surface EMG signals. Journal of Neurophysiology, 96: 1646-1657, 2006.

Nawab SH, Wotiz RP, and De Luca CJ. Decomposition of indwelling EMG signals. Journal of Applied Physiology, 105: 700-710, 2008.

Nawab SH, Chang SS, and De Luca CJ.  High-yield decomposition of surface EMG signals.  Clinical Neurophysiology – in press, DOI # 10.1016/j.clinph.2009.11.092.