Home Pages of Ted Clancy

Edward (Ted) A. Clancy

Department of Electrical and Computer Engineering
Worcester Polytechnic Institute    Tel: (508) 831-5778
Atwater Kent Room 304    Fax: (508) 831-5491
100 Institute Road    e-mail:  ted@wpi.edu
Worcester, MA 01609    web:  users.wpi.edu/~ted

Research Interests

[Link to: 2017 CBS Boston television report by Dr. Mallika Marshall on our prosthetics research]
[Link to: 2006 Lecture that reviews most of my research areas]
(Click Here for More Details on Research Interests)

My research interests are in signal processing, modeling and instrumentation, principally as applied to biomedical engineering.  My major area of specialization has been developing techniques for improving estimates of the amplitude of the surface electromyogram (EMG).  EMG, the electrical activity of skeletal muscle, can be described mathematically as a random (stochastic) process which is amplitude modulated.  When muscular effort is low, the amplitude of EMG is low;  when muscular effort is high, the amplitude of EMG is high.  Thus, better estimates of EMG amplitude improve the ability to determine the activation level of muscles.  Applications of this technology include myoelectrically-controlled powered prosthesis, analysis of gait, non-invasive estimation of torques about a joint and ergonomics.  I have also been involved in needle EMG decomposition in clinical and scientific studies; as well as high-resolution surface EMG, in which arrays of tightly-spaced, small electrodes are placed on the skin surface and used to detect the activity of individual motor units.

I have developed a MATLAB® toolbox which implements the new EMG amplitude estimation algorithims. (Click here to view the "alpha" version User's Manual.)  I also have several related interests in electromyography and biomedical signal processing.

Most students in my laboratory have an electrical engineering background — with a concentration in signal processing (or instrumentation) — and a passion for applying these skills to biomedical problems. Students learn specific biomedical skills as part of their project work, but may also have some prior coursework in biomedical engineering/physiology. In electrical engineering, graduate students should have a background in the basics of stochastic processes (e.g., ECE502) and digital signal processing (e.g., ECE503). Applicable biomedical engineering courses can be located in the Biomedical Engineering Department Graduate Catalog or Undergraduate Catalog.

My laboratory space within the Electrical and Computer Engineering Department is referred to as the "Laboratory for Sensory and Physiologic Signal Processing." This web page also serves as the web page for this laboratory.

Maintained by ted@wpi.edu
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