Добавил:
Sekretar
kiopkiopkiop18@yandex.ru
t.me/Prokururor I Вовсе не секретарь, но почту проверяю
Опубликованный материал нарушает ваши авторские права? Сообщите нам.
Вуз:
Предмет:
Файл:Ординатура / Хирургия / Библиотека им академика М.И. Перельмана / Книга_921_Библиотеки_им_академика_М_И_Перельмана
.pdf
Chapter 14
Control Options for Upper Limb Externally
Powered Components
Peter Kyberd, BSc, MSc, PhD Greg Bush, BA, CP(C) Ali Hussaini, BASc, MScE
Abstract
e control of externally powered arm prostheses requires inputs from the body to be converted into electrical signals that can be interpreted by an electronic controller. e role of the
clinical team is to match the control strategy of the prosthesis to the capabilities and needs of
the individual user. ere are many types of input forms (electromyography, linear potentiometers, force-sensing resistors and servos) and many types of control strategies (single-site,
dual-site, and switching) available to meet the individualized needs of prosthesis users. Newer
forms of input and control, such as implantable electrodes and the recognition of patterns of
muscle activity, have the potential to expand the capabilities of computer-based controllers.
Keywords: control; electromyographic signal; myoelectric control;
power; prosthetic arm; upper limb prosthesis
Introduction
The control of the unimpaired body is
accomplished by a complex set of interconnected systems. The central nervous system coordinates these systems,
adapting them to specific tasks. Competence in coordinated movements is
achieved through repetition and practice, beginning at the earliest stages of
human development. With full or partial limb loss or absence, the prosthetic
replacement device is designed to replicate lost function; however, it cannot
accomplish these functions as easily or
as effectively as a natural limb.
To control a modern prosthesis,
inputs must be derived from signals
or movements of the body and/or the
residual limb that can be captured
and easily used. For body-powered
devices, the control input and the
power of motion are derived from cable
excursion and force. For individuals
None of the following authors nor any immediate family member has received anything of value
from or has stock or stock options held in a commercial company or institution related directly or
indirectly to the subject of this chapter: Dr. Kyberd, Mr. Bush, and Mr. Hussaini.
who are unable to generate sufficient
body-powered input control because
of inadequate limb length or limitations in strength or range of motion,
or for those users who choose not to
use these methods, externally powered
control (such as battery power) can be
provided. Externally powered control
reduces the force and movement required to activate a control input. In
the most common application, myoelectric control eliminates the need for
both force and movement. The role of
the prosthetics team is to identify usable inputs and capture them to allow
easy and unambiguous control of the
prosthesis. The choice of control inputs
are affected by the many practicalities
of creating a reliable and easily usable
device. Practicality may limit the choice
of solutions, with the preclusion of devices that are difficult to operate or less
reliable.
Kinesiology of the
Upper Limb
The arm is used to place the hand in
the correct position and orientation to
manipulate an object, and the hand is
shaped to perform the manipulation
task. Both acquired amputation and
congenital limb absence eliminate several of the degrees of freedom from the
upper limb, which would otherwise be
used in positioning and manipulating
the hand. In prosthetic replacement,
the movements of the prosthesis and
its governing control inputs must come
from the remaining motions or signals
of the body. The level of limb absence
determines the extent of the required
substitutive prosthetic motions. This
creates a paradox because the shorter
the length of the residual limb, the fewer
the number of available control inputs;
however, there is a greater number of
joints that must be controlled by the
remaining control inputs. The reduction in the number of control input
options generally results in the need
to reduce the number of actively controlled prosthetic joint motions and/or
provide shared control of the remaining
prosthetic joint motions (for example,
using the same control inputs to govern
both prehension and wrist rotation). In
such instances, the simultaneous control
exerted in a physiologically sound upper limb is replaced by a prosthetic arm
that may require a series of sequential
single-degree-of-freedom actions, with
the operator switching active control between different prosthetic actions. This
operation is slower than the parallel, simultaneous motions of an able-bodied
© 2016 American Academy of Orthopaedic Surgeons Atlas of Amputations and Limb Deciencies, Fourth Edition
193
Section 2: Upper Limb
individual. As a result, the prosthesis
user may, at times, choose to neglect the
use of sequential prosthetic motions and
compensate with increased motions of
the sound limb, the body, or the proximal joints of the affected upper limb. An
example is the use of compensatory humeral abduction to functionally replace
wrist rotation.1 However, although such
compensatory motions may be quicker
and easier to use, they may also lead to
overuse injuries because they require a
greater range of motion, higher forces,
or more repetitions.2 The clinical team
should be aware of such compensatory
strategies and caution the prosthesis
user to guard against them to the extent possible.
Whether the limb absence is the result of amputation or a congenital abnormality, the musculoskeletal structure
of the residual limb is an important determinant of the choice of control options. The type of prosthesis and form
of control depend on the capabilities of
the user. Prior to fitting the prosthesis, the clinical team should assess the
ability of the user to generate different
control signals. It is important to consider which signals can be easily and
progressively generated and those that
are separable from other control signals.
Inputs that do not create incidental, unintended signals during other activities
(such as when the individual wishes to
use the prosthesis to carry an object or
extend the prosthetic limb away from
his or her body) should be established.
For example, in a prosthesis using myoelectric signals of the biceps to control
a powered elbow joint, unwanted elbow motion may result from incidental
movement of the humerus within the
socket, requiring refinement of electrode
site selection and settings. Ultimately,
the control strategy of an upper limb
prosthesis should be able to position the
prosthetic joint without creating inadvertent motion of the prosthesis.
The general philosophy behind the
control of a joint is the same irrespective
of the input sources. Across the major
joint systems of the upper limb (elbow,
wrist, and hand), traditional control
of externally powered prosthetic joint
motions uses two inputs to control the
movements in opposing directions, often termed dual-site control. Examples
include using two opposing input signals to open and close a hand, flex and
extend an elbow, or pronate and supinate a wrist. When possible, the two
input sources tend to be in opposition,
such as using electromyographic signaling of flexor and extensor muscles of
the forearm to control prehension of a
terminal device. This antagonistic type
of control is physiologically very natural
and intuitive for the patient to learn.
When control of a second mechanical
joint motion is required (for example,
prosthetic wrist rotation), a common
control strategy is to switch the active
control of the input signals between the
different joint motions. Common switching strategies include the following: (1)
using simultaneous co-contractions of
the two command muscles, (2) the use
of four-channel multistate myoelectric
control systems, or (3) the addition of
a third distinct electrical switch to cycle control between the different joints.
In the first mentioned strategy, the user
would need to quickly and simultaneously co-contract the command muscles to select the wrist rotator function
and preposition the hand in the correct
amount of pronation and supination
before co-contracting the command
muscles a second time to return to hand
function. In the second strategy using a
four-channel control system, the state of
the active control of the prosthesis (for
example, wrist rotation or hand prehension) is determined by the amplitude and
the rate of the input muscle contractions;
this strategy may improve the speed of
sequential control. The third strategy of
using a distinct electrical switch requires
an additional body motion to engage the
switch and alter which joint or component is under active control.
In addition to the delays associated
with sequential prosthetic control, the
provision of additional prosthetic movements using active, externally powered
control requires extra motors, adding
to the weight of the prosthesis. A common compromise is to choose only the
most effective actively controlled devices
or components and allow the user to
compensate in achieving other movements through other body motions,
passive positioning of the prosthesis,
or an increased reliance on the contralateral limb.
Myoelectric Control
Options
The most common input for powered
prostheses is myoelectric signals. These
signals are associated with muscular
contractions and are appealing as a
source of control information because
they eliminate the need for a control harness and expand the functional working
envelope of the prosthesis. To generate
the input signal, the user is required to
contract a specific muscle. If the muscle
is physiologically associated with the
movement of the joint being replaced,
there is a native association between the
intent and the action controlled.
Myoelectric Signal
Muscles are composed of many individual fibers.3 Signals from the nerves
cause the muscle fibers to contract and
produce a small twitch. A continuous
smooth contraction is created by many
fibers firing asynchronously through
the body of the muscle. To increase the
force of the contraction, fibers can fire
more often and more fibers can fire at
the same time. When the muscle fibers
twitch, they generate a small spike of
electrical activity that can be detected
by external electrodes. If an electrode
is placed against the skin over the belly
of the muscle, it can detect the electrical
spikes from many fibers throughout the
muscle. The intervening tissues tend to
attenuate some of the electrical signal
Atlas of Amputations and Limb Deciencies, Fourth Edition © 2016 American Academy of Orthopaedic Surgeons
194
Chapter 14: Control Options for Upper Limb Externally Powered Components
Figure 1
Both devices provide the same functions, and the packages have similar overall dimensions. The
level of amplication is adjusted with the slot on the right side.
and will affect the time that the signal
takes to travel from the muscle fiber to
the electrode. Thus, the input signal ultimately detected by a surface electrode is
the sum of numerous electrical impulses
over both time and distance. The result
is a noisy, low-frequency signal in which
the amplitude of the signal is approximately proportional to the level of the
muscle contraction.
The devices used in prosthetic applications are generally referred to as
electromyographic electrodes, but they
are more correctly identified as electrodes, amplifiers, and filters.4 The myoelectrodes currently used in prostheses
generally include electrodes, amplifiers,
and filters in a small package. Most manufactured electrode packages have the
same overall dimensions (Figure 1).
The electrodes read the signal from the
underlying muscle, filter out the interference, and amplify the signal before
determining the average amplitude and
passing it on to the controller. The resultant output signal is a single, simple,
slowly varying voltage that can be used
to control the speed or position of the
prosthesis.
The signal detected from a single
electrode contact has a great deal of
associated electrical noise (interference), which can originate from various external sources, including power
lines, lighting sources, motors, and
Photograph of two commercially available electromyographic amplier/processors.
generators. The electromyographic
amplifier/processor removes this interference by determining the difference between signals received from two
closely positioned contacts. After the
electrical signals common to both contacts (the noise) is removed, the remaining difference in the signals represents
the user-generated signals from the
3
muscle. Because these remaining signals are quite small, they require substantial amplification ( approximately
1,000 times). This underscores the
clinical importance of keeping both
of the paired electrode contacts of the
myoelectrode in contact with the underlying skin.
In addition to contained electrode
packages, remote electrodes also can
be used, often in conjunction with a
silicone liner. These electrodes are
metal contact domes that are wired
to a remote amplifier/processor unit
(Figure 2). However, separating the
circuitry that filters the signal from the
electrode contacts makes it more likely
that the connection wires will pick up
stray external signals. This potentially
results in control signals that are more
prone to interference because any electromyographic electrode/amplifier combination can pick up external electrical
interference. Therefore, careful consideration and construction of the definitive prosthesis is necessary.
Figure 2
graphic amplier/processor with remote electrode contac ts. The three lower cab les attach to
dome elec trodes, and the upper cable attaches
to the controller.
Photograph of an electromyo-
Myoelectric Control Variables
The ultimate level of the myoelectric
input signal depends on the strength
of the muscle (varying with the level
of muscle fatigue), location of the electrode relative to the muscle (variable,
in some instances, because the socket
moves on the remnant limb), and interface between the skin and the electrode
(variable because increased moisture
associated with sweat improves contact
and makes the signal larger).
Dual-Input Myoelectric
Control Strategies
In its most common applications, a pair
of opposed muscles is used to control
the movement pattern of a prosthetic
joint because this results in the most
physiologically natural control. If a
pair of myoelectric signals is used, the
input signals generally originate from
antagonistic muscle bellies positioned in
opposition across a joint. For example,
the flexor and extensor muscles of the
absent wrist are often used to control
the opening and closing of the hand.
With adequate training, many users can
generate two discrete electromyographic
control signals. The term direct control
is increasingly used to describe the clear
association between the activation of a
target muscle as a control input for a
desired movement. Pattern recognition,
which is described later in this chapter,
© 2016 American Academy of Orthopaedic Surgeons Atlas of Amputations and Limb Deciencies, Fourth Edition
195
Section 2: Upper Limb
represents an alternative option to direct
control in which this clear association is
no longer present. In addition, the conscious activation of both muscles simultaneously (termed co-contraction) is a
learned skill that can be used to switch
between different prosthetic functions
as previously described.
In the earliest versions of amplifier/
processor electrodes, there was a threshold on the amplitude signal, and only
“on” (above threshold) or “off” (below
threshold) signals could be generated.
These so-called digital electrodes could
only control prosthetic componentry at
a single speed. Although infrequently
used, these digital systems are still a
commercially available option for patients who are incapable of generating
myoelectric signals high enough to benefit from proportionately controlled systems. As improved and more compact
electronics have been developed, this
approach has been steadily replaced by
proportionally controlled analog amplifiers and processors in which the output
voltage is proportional to the amplitude
of the input electromyographic signal.
5
Some prosthetic device users are
unable to consistently generate distinct
single-muscle input signals in dual-site
control strategies without incidental,
unintended co-contractions. In such
instances, alternative programming
strategies can be used to augment the
reliability of the signal inputs. In the
“first-come-first-serve” or “first over”
strategy, the processor responds to the
first input signal that crosses its “on”
threshold, ignoring any signals subsequently generated by the other muscle
signal. In “differential control,” the processor is governed by the difference in
amplitude between the two muscle input signals, even if both have exceeded
their respective thresholds.
When two joints are to be controlled with a dual-site strategy, each
input signal can be used to control
multiple available movements. This is
seen in multistate, rate-sensitive control
strategies. In the most common example
of four-channel processing (also termed
fast access), dual-site electrodes each
govern three rate-dependent “states” of
prosthetic control. The prosthesis is in
its resting state when the amplitudes of
the input signals remain below their
“on” thresholds. When the input signals
exceed their thresholds, the prosthesis
goes into one of two remaining states
based on the rate of the increasing input
signal. In its most common application,
dual-site, low-rate input signals control
the opening and closing of the hand,
whereas dual-site, high-rate input signals control pronation and supination
of the wrist.
Single-Input Myoelectric
Control Strategies
Less frequently, a patient may only have
a single viable muscle belly for myoelectric control. There are a number of
single-input control strategies for such
scenarios. One variant is seen in the
single-input single-level control strategy,
commonly referred to as a cookie crusher. In this approach, the state of the hand
is determined by the level of the input
signal relative to an adjustable threshold.
When the signal exceeds the threshold,
an open signal is sent to the hand by the
processor. When the signal falls below
this threshold, the processor closes the
hand to a preprogrammed grip strength.
Such systems are also described using
the semantics of body-powered control
as voluntary-opening control strategies.
An associated drawback to this strategy
is an inability to regulate the grip force
of the closing hand.
A related variation is seen in a
single-input, alternating control strategy.
Under this control paradigm, proportional input signals are generated when
they exceed a programmable threshold
level. The initial signal will open the ter
minal device until the signal falls below
threshold. Once the input signal falls below threshold (and an adjustable latency
period has been satisfied), control of the
terminal device cycles from opening to
closing. Thus, when the input signal
next exceeds the threshold, it will provide a proportional close signal to the
hand. Each time the signal falls below
the threshold and an adequate latency
period occurs, control will alternate between the two desired motions, such as
opening and closing a terminal device or
flexing and extending an elbow.
A novel variation of single-input, alternating control is seen in the Force
Limiting Auto Grasp (FLAG; Motion
Control) feature for prosthetic hands.
In this strategy, when the single-input
signal exceeds the threshold, the terminal device opens. If this input signal
is sustained with the terminal device
open, the FLAG feature is enabled. The
next input signal will close the terminal device to approximately 2 lb of
grip strength. Subsequent brief input
signals will successively increase the
grip strength of the terminal device
in 2-lb increments, providing the user
with some regulation of his or her grip
strength in a single-input control system. A very long signal (2 to 3 seconds)
will disable the FLAG feature and return
the system to alternating control.
The University of New Brunswick
three-state controller represents another
control strategy and was designed for individuals who can generate only one reliable electromyographic signal.
approach, the range of perceivable input
signals is divided into three levels, with
the lowest-level signal being “off,” a range
of smaller signals providing a “close” input, and a range of larger signals producing an “open” input (Figure 3).
Other Proportionally
Controlled Input Sources
In addition to electromyographic input
signals, other proportional signals can
-
be derived from body motions. Most of
these inputs are configured so that they
can feed directly into the controllers
using the same receptacles as the electromyographic inputs on the controller
6,7
In this
Atlas of Amputations and Limb Deciencies, Fourth Edition © 2016 American Academy of Orthopaedic Surgeons
196
packages and can directly substitute for
them.
Potentiometers
A linear potentiometer captures motions in a straight line. Similar to bodypowered devices, these devices capture
relative gross body motion such as scapular abduction. However, the electronic components can amplify relatively
modest movements for individuals
who cannot generate the excursions or
forces necessary for a more traditional
body-powered device. Linear potentiometer can be arranged with a return
spring so that excursion will cause one
motion, whereas the retraction that occurs when the user relaxes will cause
another motion (Figure 4).
Chapter 14: Control Options for Upper Limb Externally Powered Components
Figure 3
graphic control. If only a single muscle is available, three states are used to control the hand in two
directions. Switch levels are set by consideration of the noise (interference) in the signals.
Schematic diagram of the Universit y of New Brunswick single-channel electromyo-
Force Transducers (Servos)
As with linear potentiometers, force
transducers (also called servos) can be
placed within a harness and activated
using the same control motions associated with body-powered prosthetic
control. The excursion required to activate such transducers is minimal. Like
linear potentiometers and in contrast
to pull switches, these transducers produce signal inputs proportional to the
strain placed through the harness. The
drawback to such transducers is that
they require a sleep mode because their
activation requirements are so minimal
that they would otherwise frequently
activate inadvertently.
Force-Sensing Resistors
Force-sensing resistors are input devices
that can measure a continuous force
(providing proportional control) or can
function as an input switch when used
with a force threshold. These resistors
are made of thin plastic with an area of
conductive ink on the plastic. They work
by exploiting the change in electrical
resistance in the ink as force is applied.
The sensors can be arranged to provide
a change in voltage as they are compressed. The resistors have a very low
Figure 4
by a xture (right side) and across a joint via a cab le (left side). B, Photograph of a linear p otentiometer that is built into a harness.
profile and require low activation forces.
These properties make force-sensing resistors suitable for individuals who can
move distal parts of their residual limb
but cannot generate a large enough force
to control body-powered devices. The
sensors are made in a range of sizes and
shapes, can be used anywhere in a prosthetic socket, and are available from several manufacturers (Figure 5). Unlike
electromyographic devices, which detect signals derived from muscle activity,
force-sensing resistors directly capture
the force of the limb against the resistor. For example, force-sensing resistors
can be used inside the shoulder cap of a
shoulder disarticulation prosthesis. The
amputee’s mobile acromion can touch
different points to trigger different motions (Figure 6). More commonly, they
are used at the partial hand level where
their low-profile build height is greatly
appreciated. Even small movements of
the residual digits can be utilized with
force-sensing resistors to provide useful
control of electric digit systems.
A, Photograph of a linear p otentiometer, which is attached to o ne part of the socket
Nonproportional Electric Switches
In contrast to the inputs described thus
far that provide proportional control
inputs to the externally powered prosthesis, there are a number of electric
switches that can be used to provide
additional control signals. Switch control is seldom used as a primary input
source because it requires gross body
motions for activation and only produces constant, nonproportional (digital) control. The use of a rocker switch
to control wrist rotation at a single speed
is a common exception to this generality. Switches are more frequently used
as a secondary signal source, acting as
a mode switch between the activation
of different prosthetic components or
controlling an elbow lock.
Pull switches can be placed in
the harness of the prosthesis so that
relative motion (such as scapular abduction) can be used to switch modes
(for example, from hand to elbow). In
a common variation (the four-stage
pull switch), progressive excursion of
© 2016 American Academy of Orthopaedic Surgeons Atlas of Amputations and Limb Deciencies, Fourth Edition
197
Section 2: Upper Limb
Figure 5
together or purchased loose from various manufacturers to allow dierent positioning options.
the pull switch cycles the prosthesis
from dormancy to active control of one
motion to dormancy to active control
of a second motion. These switches
should be arranged so they are easily triggered when needed but do not
trigger inadvertently.
Push switches can also be placed on
the humeral section of a transhumeral
prosthesis so that bringing the arm
against the torso can trigger the switch
(bump switch). Similarly, for high-level
(bilateral) limb absences, push switches
can be close to the face and within reach
of the chin.
Photographs of s everal types of f orce-sensing re sistors. The devi ces can be package d
triggers, user-dependent controllable variables include how long the
co- contraction must be maintained,
whether both muscle signals have to rise
together, and the required speed of the
signal rise. For hold-at-a-limit triggers
(generally at the extension limit), when
the hand is fully open, the user holds
it open longer to trigger a new grip. In
addition, double and triple impulse triggers require two or three impulse contractions to be applied in succession to
trigger alternative grip patterns. These
may require that there be no signal on
the contralateral muscle during this
time, which may be difficult for some
Control Strategies for
Multiarticulated Hands
The recent addition of multiple separately controlled fingers has changed how
prosthetic hands can be used.8 It is now
possible to drive different fingers to different positions, allowing the execution
of a range of grip patterns, including
precision, power, lateral, tips, and point.
However, the user must be able to select
between these grip forms. In general,
there are more available grip variations
than available input or switch signals
in the prosthesis. Working together, the
prosthesis user and the clinician can determine which grips are most beneficial
and how to select between them.
Selecting between grip variations in
multiarticulating hands is com monly
done through various myoelectric signal “triggers.” In co-contraction–based
users to accomplish.
In general, although more hand positions can be accessible with more input
trigger signals, the greater the number
of input signals used, the more difficult
it is to reliably achieve the signals, especially if the user wants to signal the hand
position to change quickly. As a result,
although technically feasible, multiple
coding schemes and switching strategies
are rarely used in commercially available, multiarticulating hands.
9,10
Other solutions include using external electrical switches, with the simplest
switches located on the prosthesis. The
Bebionic Hand (Steeper) has a switch in
the middle of its dorsal surface, which
can be programmed to switch in or out
of a particular hand state (defined by the
clinical team). A second switch is built
into the base of the thumb. It detects
Figure 6
resistors used in a prosthetic shoulder cap to
operate two degrees of freedom. The response
of the resistors is improved by placing the pads
over the sensitive area.
Photograph of force-sensing
when the user has moved the thumb
across into lateral grip. This contextual
switch then changes the controller into
a lateral grip mode where it extends the
thumb more than the fingers. Similar
contextual switches have been used in
externally powered elbows to affect the
state of the prosthetic hand.
11
Another switching approach is based
on the technology of radiofrequency
identification (RFID) tags.12 These tags
are used in retail markets to allow the
remote detection of a particular product without an individual (for example,
stock taker or consumer) touching the
object. The same remote detection system can be used to inform a prosthetic
hand controller of the characteristics of
an object in close proximity (and presumably going to be picked up). When
the prosthesis approximates an object
with an RFID tag, the grip position of
the hand is changed to accommodate
the preprogrammed grip position of
the hand for that object. An alternative
solution is for the user to select grip
positions with a menu on a personal
electronic media device (such as a smart
phone) to change the programming of
the prosthetic hand to select the needed
grip.
Both options are now being offered
by manufacturers, although both have
some inherent limitations. To use the
RFID tag system, the user must seed his
Atlas of Amputations and Limb Deciencies, Fourth Edition © 2016 American Academy of Orthopaedic Surgeons
198
Chapter 14: Control Options for Upper Limb Externally Powered Components
or her household with the RFID tags in
appropriate places to trigger the desired
grips. This solution is not feasible for
travel away from home or in unfamiliar
environments. Alternatively, the RFID
tags can be placed on an individual’s
clothing to allow him or her to select
a particular grip by waving the hand
close to the tag. Similarly, retrieving a
smartphone to switch hand positions
can be time consuming. However, both
of these methods could be useful for
routine tasks in familiar environments,
such as working in a kitchen or office,
where specific forms of grip may be routinely desired.
Pattern Recognition
In contrast to the direct control strategies already described in this chapter
in which isolated muscle contractions
control discrete movement at individual
prosthetic components, pattern recognition systems use electromyographic
signals obtained from multiple surface
electrodes to map a user’s intended motions. Coordinated grasping motions use
multiple muscles in different proportions
and with different timings. A computer
can be programmed to recognize different signal patterns and cause a prosthesis
to perform specific actions in response to
those recognized signal patterns.13 This
is an attractive idea, because in many amputees certain muscle patterns are well
practiced and stored in their central nervous system. With pattern recognition
systems, the operation of the prosthesis
is not a series of artificial movements but
the same actions that were performed
before the amputation. Multiple (four or
more) electrodes are placed across the
surface of the residual limb, although not
necessarily over the individual muscles.
The signals are collected, and particular mathematical aspects (or features)
of the signals are extracted. The system
is “trained” by the user, with the user
producing and repeating certain muscle activities for various grips of interest.
The computer software is programmed
to recognize those patterns of muscle
activity and perform a specific controlled
response in the hand or arm prosthesis
when a specific muscle activity pattern
is detected.
Pattern recognition systems have several inherent problems and limitations.
Programming a computer to recognize
different muscle activity patterns requires the user to perform and repeat
specific muscle contraction actions several times on cue. However, these subtle
patterns may change depending on the
orientation of the arm.14 Accordingly,
the individual’s limb must be placed in
different orientations during the training process.15 Muscle activity patterns
also change over time as muscles become stronger or weaker or if the user is
fatigued. In addition, an individual will
not always move his or her muscles in
exactly the same way. The system also
relies on the maintenance of a relatively
precise location for the electrodes that
detect the myoelectric signals; a change
in the location of the electrodes will alter
the signals received.
Solutions have been proposed to address some of the problems of pattern
recognition prosthetic control systems.
Lock et al16 suggested that the prosthesis
user initiate a training session, referred
to as prosthesis-guided training, whenever he or she feels that the device is not
working properly. In this impromptu
programming exercise, the prosthesis
performs a series of set motions and
the user copies those motions. Field
studies have shown that the number of
prosthesis- guided training sessions decreases as the user becomes more familiar with a prosthetic arm. This implies
that, in addition to the reprograming
the computer software, users also learn
how to generate repeatable and more
consistent electromyographic signals.
Clinical application of pattern recognition requires a compact com puter system that can make calculations quickly
and does not use too much battery
power. Although clinical application
and integration of this methodology
into viable prosthetic devices continue
to present challenges, meeting these
requirements has become easier in the
past few years, and the technology is
now commercially available.17 Pattern
recognition algorithms have been shown
to be successful in detecting signal patterns, synergies, and user intent.
Targeted Muscle
Innervation
Individuals with higher-level amputation lack the needed number of control
sites. A standard prosthetics dilemma
is that the higher the level of amputation, the more degrees of freedom that
need replacing, whereas the number
of available control sites declines. Targeted muscle innervation offers a surgical solution to this dilemma through
the creation of more control sites by
reinnervating proximal muscle groups
with nerves that previously controlled
distal muscle segments. Although this
creates a source of additional control input signals, the problems of consistent
electrode placement remain.
Internal Electrodes
Maintaining consistent surface electrode
contact over the targeted muscle belly can
be challenging in any myoelectric control strategy. A proposed solution to this
challenge is to place the electrodes within
the muscles rather than on the surface of
the residual limb. Problems of powering
such internal electrodes and the body’s
reaction to a foreign object are still being
investigated. Although this approach is in
experimental stages, it has shown promise. For example, the Alfred Mann Foundation has been working on implantable
myoelectric sensors. These sensors,
which can detect muscle contractions,
are implanted into a patient’s forearm.18
For the patient with a transradial am
putation, this pattern recognition–based
system can provide consistent inputs for
the control of up to three simultaneous
degrees of freedom: forearm rotation,
-
© 2016 American Academy of Orthopaedic Surgeons Atlas of Amputations and Limb Deciencies, Fourth Edition
199
Section 2: Upper Limb
hand opening and closing, and thumb
actuation. The electrical power to drive
the sensors has to be passed through the
skin inductively, which requires antennas
and some power loss.
An alternative approach to im planted
electrodes that uses direct control rather
than pattern recognition has been described by a team at the Sahlgrenska
hospital in Sweden.
19,20
A prosthesis
attached using osseointegration results
in more reproducible prosthesis positioning because the prosthesis locks
rigidly onto the residual limb. In 2013,
the Swedish team reported that the
wiring for indwelling electrodes can be
passed through the distal abutment of
an osseointegrated prosthesis without
increasing the inherent risk of infection
and that this wiring technique could be
used to retrofit previously placed abutments fit by the team. The problem of
supplying power through the skin is
circumvented by this technique, and,
as is the case for other solutions using
indwelling electrodes, it eliminates the
repeatability problem inherent in exter
nal electrodes.
Bus Signal Transmission
With the increased processing power
that is now possible in smaller electrode
packages with lower electrical current
consumption, it will be possible to obtain more information from sensors to
determine the intended muscle actions
of a prosthesis user. A related improvement is seen with the use of a local
network or “bus” technology for electromyographic signal transmission. A bus
system uses a path for signal transmission in which signals are dropped off or
picked up at each device attached along
the transmission path. This type of network allows communication between
microcontrollers and devices without a
host computer. An early example of such
a system was used in the experimental modular ToMPAW prosthesis;21 it is
still being used clinically in the United
Kingdom. The use of a modular bus
transmission system allows components
to be added easily to the system, while
only using a limited number of wires
(often two or three). This decreases the
number of needed wires and potentially
increases reliability. The Michelangelo
Hand (Ottobock) represents another
commercially available upper prosthesis
that benefits from a bus system.
The COAPT pattern recognition
controller (Coapt LLC) allows multiple
electrodes to communicate with both
the controller and multiple joints in
the prosthesis across a limited number
of wires.22 In the ultimate form of this
system, each myoelectrode and other
input device will have its own input microprocessor. This will allow electrodes
to be placed in a single circuit with one
four-wire cable linking the electrodes
and joint controllers and will allow communication between the electrodes and
controllers along the network path.23 A
current limitation in bus technologies
is that manufacturers have not decided
on a single standard for intercomponent
-
communications, thus limiting component compatibility and the choice of
custom-designed prosthetic systems
for patients.
Summary
The range of different control strategies for externally powered upper limb
prostheses are the response to the many
unique presentations of individuals
needing a prosthetic arm. Different input methods depend on the capability
of the user to generate different control
signals. The signals are generated by
detecting input forms such as electromyographic signals, pressure against
sensors, or the creation of movement
between two body segments. When the
user has few inputs or needs multiple
joints to provide function, control of
the prosthesis is slowed by the need to
switch sequentially between the controls
of various prosthetic motions.
Recent developments in electronics have increased processing power,
reduced component package size, and
reduced electrical current consumption. It is now possible to use more information from body sensors to create
independent control of more prosthetic
joints. Pattern recognition of muscle signals is creating more opportunities for
new controllers. In addition, new input
methods such as indwelling electrodes
in the muscles of the residual limb may
allow the development of more sophisticated prostheses.
References
1. Banziger E: Wrist rotation activation
in myoelectric prosthetics: An
innovative approach. JACPOC
1996;30(4):12-14. Available at: ht tp://
www.acpoc.org/newsletters-andjournals/1996_04_012.asp. Accessed
October 1, 2015.
2. Kidd PS, McCoy C, Steenbergen L: Repetitive strain injuries
in youth. J Am Acad Nurse Pract
2000;12(10):413-426. Medline DOI
3. Lovely DF: e origins and nature of
the myoelectric signal, in Muzumdar
A, ed: Powered Upper Limb Prosthet-
ics. Berlin, Germany, Springer, 2004,
pp 17-33. DOI
4. Lovely DF: Signals and signal processing for myoelectric control, in
Muzumdar A, ed: Powered Upper
Limb Prosthetics. Berlin, Germany,
Springer, 2004, pp 35-54. DOI
5. Sears HH, Shaperman J: Proportional myoelectric hand control: An
evaluation. Am J Phys Med Rehabil
1991;70(1):20-28. Medline DOI
6. Parker PA, Stuller JA, Scott
RN: Signal processing for the
multistate myoelectric channel.
Available at: http://ieeexplore.ieee.
org/xpl/login.jsp?tp=&arnumber=1454814&url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2
Fabs_all.jsp%3Farnumber%3D1454814. Accessed May 18,
2015.
Atlas of Amputations and Limb Deciencies, Fourth Edition © 2016 American Academy of Orthopaedic Surgeons
200
Chapter 14: Control Options for Upper Limb Externally Powered Components
7. Scott RN, Paciga JE, Parker PA:
Operator error in multistate myoelectric control systems. Med Biol
Eng Comput 1978;16(3):296-301.
Medline DOI
8. Kyberd PJ, Mustapha N, Carnegie F,
Chappell PH: A clinical experience
with a hierarchically controlled
myoelectric hand prosthesis with vibro-tactile feedback. Prosthet Orthot
Int 1993;17(1):56-64. Medline DOI
9. Pons JL, Rocon E, Ceres R, Reynaerts
D, Saro B, Levin S, Van Moorleghem
W: e MANUS-HAND dextrous
robotics upper limb prosthesis: Mechanical and manipulation aspects.
Auton Robots 2004;16(2):143-163.
DOI
10. Dalley SA, Varol HA, Goldfarb M:
A method for the control of multigrasp myoelectric prosthetic hands.
IEEE Trans Neural Syst Rehabil Eng
2012;20(1):58-67. Medline DOI
11. Nightingale JM: Microprocessor control of an articial arm. J Microcom-
put Appl 1985;8(10):167-173. DOI
12. Trachtenberg MS, Singhal G, Kaliki
R, Smith RJ, akor NV: Radio frequency identication—an innovative
solution to guide dexterous prosthetic hands. Conf Proc IEEE Eng Med
Biol Soc 2011;2011:3511-3514. Medline
13. Parker PA, Englehart KB, Hudgins
BS: Control of powered upper limb
prostheses, in Merletti R, Parker PJ,
eds: Electromyography: Physiology,
Engineering, and Non-Invasive Applications. Hoboken, NY, Wiley-IEEE
Press, 2004, pp 453-475.
14. Fougner A, Scheme E, Chan AD, Englehart K, Stavdahl O: Resolving the
limb position eect in myoelectric
pattern recognition. IEEE Trans Neu-
ral Syst Rehabil Eng 2011;19(6):644-
651. Medline DOI
15. Radman A: Enhancing the Robustness of Pattern Recognition Based
Myoelectric Control With a Focus on
Dynamic Limb Movements
[PhD thesis]. Fredericton, New
Brunswick, Canada, University of
New Brunswick, 2014.
16. Lock BA, Simon AM, Stubbleeld
K, Hargrove LJ: Prosthesis-guided
Training for Practical Use of Pattern
Recognition Control of Prostheses.
Available at: http://dukespace.lib.
duke.edu/dspace/bitstream/handle/10161/4713/41%20Lock.pdf ?sequence=1. Accessed May 18, 2015.
17. Scheme E, Englehart K: Electromyogram pattern recognition for control
of powered upper-limb prostheses: State of the art and challenges
for clinical use. J Rehabil Res Dev
2011;48(6):643-659. Medline DOI
18. Merrill DR, Lockhart J, Troyk PR,
Weir RF, Hankin DL: Development
of an implantable myoelectric sensor
for advanced prosthesis control.
Artif Organs 2011;35(3):249 -252.
Medline DOI
19. Ortiz-Catalán MJ, Håkansson
B, Brånemark R: Osseointegrated human-machine gateway for
long-term stable sensory feedback
and motor control. Sci Transl Med
2014;6(257):257. Medline DOI
20. Ortiz-Catalán MJ: Towards Natural
Control of Articial Limbs: A Novel
Osseointegrated Human-Machine
Gateway, Neuromuscular Electrodes,
and Pattern Recognition [PhD thesis]. Gothenburg, Sweden, Chalmers
University of Technology, 2014.
21. Kyberd P, Poulton A, Gow D, Sandsjö
L, Jönsson S, Jones B: e ToMPAW
modular prosthesis: A platform for
research in upper limb prosthetics.
J Prosthet Orthot 2007;19(1):15-21.
DOI
22. COAPT complete control website.
Available at: http://www.coaptengi-
neering.com/. Accessed May 18, 2015.
23. Wilson AW, Losier YG, Parker PA,
Lovely DF: A bus-based smart myoelectric electrode/amplier: System
requirements, special section on
medical measurements, and applications. IEEE Trans Instrum Meas
2011;60(11):3290-3299. DOI
© 2016 American Academy of Orthopaedic Surgeons Atlas of Amputations and Limb Deciencies, Fourth Edition
201
Соседние файлы в папке Библиотека им академика М.И. Перельмана