Electromyograms (EMG):
Call for Data and Announcement of Yearly Award

An electromyogram (EMG) is a common clinical test used to assess function of muscles and the nerves that control them. EMG studies are used to help in the diagnosis and management of disorders such as the muscular dystrophies and neuropathies. Nerve conduction studies that measure how well and how fast the nerves conduct impulses are often performed in conjunction with EMG studies.

Examples of EMG studies (courtesy of Seward Rutkove, MD, Department of Neurology, Beth Israel Deaconess Medical Center/Harvard Medical School) are illustrated below. The original data are available here.

Despite the importance of EMG tests to clinicians and researchers, no freely available, large-scale collections of such studies are available on the Internet (aside from EMG signals recorded during sleep studies). Open-source datasets are important because they help promote better diagnosis and also foster the definition and refinement of standards for test performance and evaluation.

Posting of data in digital form may, indeed, lead to new approaches to diagnosis by affording access to communities (e.g., applied mathematicians, engineers, physicists, physiologists) with expertise in signal analysis but no means to explore physiologic data of this type and to propel new hypotheses worthy of future study.

Motivated by these goals, the Margret and H.A. Rey Institute for Nonlinear Dynamics in Medicine, in conjunction with the NIH-sponsored Research Resource for Complex Physiologic Signals (PhysioNet), announces a call for digital datasets from EMG and nerve conduction studies. Guidelines for contribution of anonymized data obtained with informed consent, are given here.

To encourage work in this field, the Rey Institute is also offering a $500.00 (USD) award for the best contribution of EMG data, to be determined by a peer-reviewed committee and announced at the Reylab and PhysioNet websites on March 1 of each year, beginning in 2010. To qualify, datasets need to be submitted by January 1 of that year.

For further information about making data available and this Reylab/PhysioNet EMG Award, please contact Dr. Ary Goldberger (agoldber at bidmc dot harvard dot edu).

Examples of EMG studies

Data were collected with a Medelec Synergy N2 EMG Monitoring System (Oxford Instruments Medical, Old Woking, United Kingdom). A 25mm concentric needle electrode was placed into the tibialis anterior muscle of each subject. The patient was then asked to dorsiflex the foot gently against resistance. The needle electrode was repositioned until motor unit potentials with a rapid rise time were identified. Data were then collected for several seconds, at which point the patient was asked to relax and the needle removed.

The figure shows three examples of EMG data from: 1) a 44 year old man without history of neuromuscular disease; 2) a 62 year old man with chronic low back pain and neuropathy due to a right L5 radiculopathy; and 3) a 57 year old man with myopathy due to longstanding history of polymyositis, treated effectively with steroids and low-dose methotrexate. The data were recorded at 50 KHz and then downsampled to 4 KHz. During the recording process two analog filters were used: a 20 Hz high-pass filter and a 5K Hz low-pass filter.

Suggested readings about EMG:

Kimura J. Electrodiagnosis in Diseases of Nerve and Muscle: Principles and Practice, 3rd Edition. New York, Oxford University Press, 2001.

Reaz MBI, Hussain MS and Mohd-Yasin F. Techniques of EMG signal analysis: detection, processing, classification and applications. Biol. Proced. Online 2006; 8(1): 11-35.