What you need to know to perform biofeedback effectively
Article 4: Why you need to know how biofeedback devices work
By Richard A. Sherman, Ph.D.
Research has shown that practitioners who possess an adequate
technical understanding of how their biofeedback instrumentation works
have more successful outcomes. Fundamental to effective biofeedback is
accurate and valid electrophysiological measurement that produces signals
that are as free of artifact as possible. When instruments produce feedback
that is an accurate reflection of that which is taking place within the body,
learning, which is the goal of biofeedback and neurofeedback training, is
made possible.
The topics below are essential to a sufficiently inclusive course in
biofeedback instrumentation:
1. Ohm’s law (the relationship between resistance to the flow of
current, amount of current, and voltage / signal magnitude) –
how it effects SEMG, EEG, and especially, SCL / GSR signals.
2. Use of the (a) offset, (b) averaging / integration, (c) gain /
amplification, and (d) sweep speed (time it takes the signal to
cross the screen) to produce an optimal feedback signal from
which patients can learn. For example, having your device set
these automatically may make learning difficult or impossible?
3. The overwhelming effect of bandwidth / filters on whether the
signal has been recorded relative to its power spectrum.
4. How to properly attach the sensors for each physiological
parameter so movement artifacts are minimized and the signal
rather than noise is recorded. Placement of reference sensors is
included.
5. How to easily test each signal before beginning a session to
insure that it is recording properly and that the signal changes
with changes in the subject’s physiology.
6. How to recognize noise and interference from other signals
during a recording.
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7. How to reset the equipment as a session progresses so you can
use shaping techniques to teach patients physiological control by
properly setting the feedback display.
8. How to protect your patient from electrical shock when using
typical biofeedback devices.
9. Understanding the display when you record:
a. Muscle Tension
b. Heart Rate / heart rate variability
c. Sweating in response to stress / GSR / SCL
d. Respiration
e. Temperature (for blood flow)
f. Electroencephalogram (EEG)?
10. Understanding how these signals are actually generated to
avoid common mistakes such as recording across rather than
along a muscle?
11. Understanding the relationships between changes in
sweating and changes in GSR signals such as conductance and
resistance or the relationships between conductance and
resistance?
12. Understanding the effect of different devices on the magnitudes
of the signals you see?
The following pages include a more in-depth view of the kind of
information biofeedback practitioners need to understand in order to perform
biofeedback effectively.
Bandwidth
The amplifiers on most biofeedback and psychophysiological recording
devices can be set to a variety of frequencies. The basic idea is to set the
amplifier to receive the relevant frequencies produced by the physiological
signal being recorded (such as sEMG from a muscle) while filtering out
frequencies produced by unwanted sources such as the lights in the room,
other physiological signals, etc.
The window of frequencies an amplifier is set to record is referred to
as its bandwidth. An example would be 90 – 500 Hz. No significant amount
of the signals picked up by the sensors that are produced by frequencies
above or below the bandwidth are amplified, so they don’t appear in the
recording. Any power from 0 – 89 Hz and above 500 Hz is never seen.
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Power Spectrum
When examining a raw sEMG signal, many different frequencies are
represented. The total amount of the muscle’s electricity produced at any
particular level of tension is unevenly divided between the various
frequencies. A muscle’s power spectrum refers to the amount of electrical
potential in each of the frequencies of waves occurring at a particular level of
tension.
When a muscle is relaxed, most of the power may be in lowerfrequency waves. This may change as the muscle tenses so that more of the
power is in higher-frequency waves. A muscle’s power tends to decrease in
frequency with fatigue, so the power spectrum changes during recordings in
which the subject is trying to control the muscle’s activity.
All principles of the power spectrum apply to the EEG as well. When
you look at a raw EEG signal, many different frequencies are represented.
The total amount of electricity recorded by surface EEG sensors is unevenly
divided between the various frequencies. In the case of the EEG, power
spectrum refers to the amount of electrical potential in each of the
frequencies of waves recorded from a particular part of the brain at any
moment in time.
Improperly Set Amplifiers
In order to record power properly, it is necessary to set the bandwidth
to include the frequencies containing most of the muscle’s power and at
various levels of tension.
This is illustrated on the next page as follows: Part “a” of the following
figure illustrates the effect of changing the amplifier’s bandwidth on how
much of the signal actually gets recorded. Note that as the bandwidth is
narrowed from 90 – 1,000 Hz (cycles per second) through 250 Hz down to
150 Hz, much of the signal’s characteristics disappear as the more rapid
deflections are cut out. This reduces the overall amount of power recorded.
Part “b” shows you just how much power much power will be lost.
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reduction.
The following illustration shows what you see on biofeedback meter
displays as the frequency block containing most of a muscle’s power shifts
from low to high frequencies as the muscle’s tension changes. Two meters
are shown in each part of the figure. The upper meter shows the reading of
relative tension when recording the wide bandwidth of 8 – 500 Hz (cycles
per second) while the lower meter shows the reading you see when
The illustration above shows the biofeedback meter display as the
frequency block containing most of a muscle’s power shifts from low to high
frequencies as the muscle tension changes. Two meters are shown in each
part of the figure. The upper meter shows the reading of relative tension
when recording the wide bandwidth of 8-500 HZ (cycles per second) while
the lower meter shows the reading seen when recording only a narrow
bandwidth of 100 – 200 Hz within the wider bandwidth. The heavy, dark line
represents how much power the muscle being recording is putting out at
each frequency.
The top part of the figure shows the situation when most of the power
is in lower frequencies so the biofeedback displays for both wide and narrow
bandwidth show low readings (needle off to the left) as there is little total
tension and most of the power is outside the area recorded by the narrow
bandwidth – so it misses most of what is going on.
The middle part of the figure shows what happens when tension has
changed so that most of the power is in the middle of the frequency
spectrum centered at about 200 Hz. Thus, both meters go up. The problem
with using a narrow bandwidth becomes evident in the lower part of the
figure, which shows the situation when most of the power has shifted to
higher bandwidths. The total amount of tension in the muscle has gone up
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so the top meter shows a higher reading. However, the meter recording only
the narrow bandwidth goes down because little power is in the 100 to 200
Hz range.
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100 200
500
Power Spectra For Two Muscles
The power spectrum put out by muscles is different 1) for different
muscles at the same level of tension and 2) the same muscle at different
levels of tension. Power tends to decrease with fatigue, so incorrectly set
filters are likely to give less and less accurate readings as fatigue sets in.
The following figure shows the tremendous differences in patterns of
power in two muscles. The three-dimensional graphs show the power
spectra of two muscles as their tension changes over time. The one on the
left is in blue and the one on the right is in red. Power (amount of electricity)
is on the vertical axis, time goes from front to back, and frequency changes
from left to right. This is an illustration of differing spectra further explained
in the next figure.
Muscle 1
Muscle 2
Time
Power
0
60
500
0
60
500
Frequencies recorded for each muscle (Hz)
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This is an example of the power spectra of three muscles recorded at
about the same level of tension. If the recording used only a narrow
bandwidth of 100 – 200 Hz, the meter displays would look very different as
different amounts of power for each muscle happen to be within the 100 –
200 Hz range.
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Signal Control
A signal can be controlled best if it can be displayed properly. The
display should be set so the signal is 1) the right size to provide enough
information to learn from, 2) entirely in view on the monitor, and 3) present
for sufficient time before the screen refreshes itself so you can see changes.
To make an optimally effective display, control the
(1) gain (amplification),
(2) offset, and
(3) sweep speed (horizontal deflection speed).
A signal’s gain is the amount of amplification (volume). In the
following figure, the gain is initially set so low that important changes in the
signal can’t be detected.
Here’s a situation in which the gain needs to be lowered to use
the signal appropriately. The screen’s viewable area is shown by the red box.
HIGH GAIN
LOWER GAIN
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Initially, an important part of the signal is off the viewable area of the
monitor, so the size of the signal needs to be reduced.
The offset controls the vertical position of the signal on the screen. It
does not change the gain (size/magnitude) of the signal. The screen’s
viewable area is shown as a red box.
INCORRECT
CORRECT
Initially, an important part of the signal is off the top of the monitor’s
viewable area, so the vertical position of the signal needs to be lowered in
order for the entire signal to be seen.
The deflection time or the rate at which the signal moves across the
monitor’s screen from left to right is called the sweep speed. This has to be
controlled so you can see enough of the signal’s history to make sense of
what is happening.
When the signal reaches the right edge of the screen, the display
resets itself, so everything that was on the screen disappears, and the signal
starts over at the left edge. If the signal is set so it moves across the screen
too quickly, too little of the history is available on the screen to tell what
happened throughout a series of actions. If it is too slow, the changes can’t
be seen because they pile up on each other.
For example, if you ask a patient to tense a muscle, hold it for 10 seconds
and then relax, you want to see the entire sequence. This event is shown by
the blue arrow.Setting the speed so the signal moves across the screen in
five seconds would mean that you might see the first part of the movement
but not the entire sequence.
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5 sec
Setting it at 10 minutes would make the changes pile up, so you couldn’t tell
them apart.
600 sec
Setting it at 30 seconds is about right to see the entire sequence.
30 sec
What’s next?
This article was intended to provide you with some valuable
information to use in improving your biofeedback recordings and displays. If
there are any topics discussed in this paper that you don’t truly understand,
it is recommended that you take the instrumentation portion of a BCIA
approved biofeedback course. See the provider training sections on BCIA
and AAPB’s websites. AAPB frequently offers a biofeedback instrumentation
course during its annual conference. These courses teach the concepts but
are not tied to one specific type of equipment.
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