848 IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, VOL. 50, NO. 7, JULY 2003
A Robust, Real-Time Control Scheme for
Multifunction Myoelectric Control
Kevin Englehart*, Member, IEEE, and Bernard Hudgins, Senior Member, IEEE
Abstract—This paper represents an ongoing investigation of
dexterous and natural control of upper extremity prostheses using
the myoelectric signal (MES). The scheme described within uses
pattern recognition to process four channels of MES, with the
task of discriminating multiple classes of limb movement. The
method does not require segmentation of the MES data, allowing a
continuous stream of class decisions to be delivered to a prosthetic
device. It is shown in this paper that, by exploiting the processing
power inherent in current computing systems, substantial gains
in classifier accuracy and response time are possible. Other
important characteristics for prosthetic control systems are met as
well. Due to the fact that the classifier learns the muscle activation
patterns for each desired class for each individual, a natural
control actuation results. The continuous decision stream allows
complex sequences of manipulation involving multiple joints
to be performed without interruption. Finally, minimal storage
capacity is required, which is an important factor in embedded
control systems.
Index Terms—Classification, embedded system, EMG, myoelec-
tric, pattern recognition, prostheses.
I. INTRODUCTION
T
HE surface myoelectric signal (MES) is an effective and
important system input for the control of powered pros-
theses. This controlapproach, referred to as myoelectric control,
has found widespread use for individuals with amputations or
congenitally deficient upper limbs. Clinical evaluations of my-
oelectrically controlled prostheses indicate that the three major
factors that determine the acceptance rates by the users are: the
type of prosthesis, the degree of user training, and the control
strategy. It is the third factor that we consider here. It has been
observed [1] that low acceptance rates result when the user per-
ceives an inadequate controllability—specifically a lack of intu-
itive and dexterous control. A myoelectric control system is de-
scribed that offers exceptional performance with regard to three
important aspects of controllability: the accuracy of movement
selection, the intuitivenessof actuating control, and the response
time of the control system.
• Accuracy is essential to faithful realization of a user’s in-
tent. Accuracy must be as high as possible, although it is
Manuscript received May 15, 2002; revised December 27, 2002. This work
was supported by the Natural Sciences and Engineering Research Council of
Canada under Discovery Grant 217354 and Discovery Grant 171368. Asterisk
indicates corresponding author.
*K. Englehart is with the Department of Biomedical Engineering, University
of New Brunswick (UNB), 25 Dineen Drive, Fredericton, NB E3B5A3, Canada
(e-mail: kengleha@unb.ca).
B. Hudgins is with the University of New Brunswick (UNB), Fredericton,
NB E3B5A3, Canada.
Digital Object Identifier 10.1109/TBME.2003.813539
difficult to define the threshold of acceptability, as no de-
finitive clinical trials have addressed this issue.
• An intuitive interface to the control system relieves the
mental burden of the user. In this regard, a control system
should be capable of “learning” the muscle activation pat-
terns chosen as the most “natural” by an individual to
actuate motion.
• The response time of a control system should not intro-
duce a delay that is perceivable by the user. This threshold
is generally regarded to be roughly 300 ms. This places
a real-time constraint on the control system’s tasks of ac-
quiring and processing myoelectric data.
II. B
ACKGROUND
The concept of myoelectric control was introduced in the
1940s [2]; however, the technology of the day was not ade-
quate to make the clinical application viable. It was with the
development of semiconductor device technology, and the as-
sociated decrease in device size and power requirements that
clinical application saw promise, and research and development
increased dramatically. Significant progress was made interna-
tionally in the 1960s [3]–[8], but it was in the 1970s that myo-
electric prostheses began to make a significant clinical impact.
Powered prostheses with myoelectric controllers were routinely
fitted to upper limb deficient clients, and clinical evaluations of
the functional benefits carried out [9].
Electrically powered prostheses with myoelectric control
have several advantages over other types of prostheses: the user
is freed of straps and harnesses required of body powered and
mechanical switch control; the MES is noninvasively detected
on the surface of the skin; the controller can be adapted to
proportional control with relative ease; and muscle activity
required to provide control signals is relatively small and can
resemble the effort required of an intact limb.
Many myoelectric control systems are currently availablethat
are capable of controlling a single device in a prosthetic limb,
such as a hand, an elbow, or a wrist. These systems extract con-
trol information from the MES based on an estimate of the am-
plitude [10] or the rate of change [11] of the MES. Although
these systems have been very successful, they do not provide
sufficient information to reliably control more than one func-
tion (or device) [12]; the extension to controlling multiple func-
tions is a much more difficult problem. Unfortunately, these
are the requirements of those with high-level (above the elbow)
limb deficiencies, and these are the individuals who could stand
to benefit most from a functional replacement of their absent
limbs.
0018-9294/03$17.00 © 2003 IEEE