Blood volume pulse (BVP), in sharp contrast, is a rapid (phasic)
index of change in arteriole blood flow. There is a 0.5- to 2-second time lag between a stressor and reduction in BVP. These measures
complement each other.
Temperature indexes average blood flow, while
blood volume pulse tracks sudden changes.
The photoplethysmograph (PPG) and electrocardiograph (ECG) are two
methods of detecting heart rate (HR) and heart rate variability (HRV), consisting of beat-to-beat changes in the heart rhythm.
Consumer wearable devices like the Elite HRV CoreSense ®, Polar bands, and Institute of HeartMath Inner Balance ® have become increasingly popular for recreation and
self-regulation.
BCIA Blueprint Coverage
This unit addresses Descriptions of the most commonly employed biofeedback modalities: Temperature, blood volume pulse, EKG and HR (III-A),
Sources of artifact (III-B), and Structure and function of the autonomic nervous system (V-A).
This unit covers the Feedback Thermometer, Infrared Thermometers, Photoplethysmograph, Electrocardiograph, Heart Rate Variability Metrics, and Drug Effects.
Please click on the podcast icon below to hear a full-length lecture.
Feedback Thermometer
Thermistors
We detect temperature using a thermistor, a transducer that
converts temperature into a resistance value.
Thermistors are
temperature-sensitive resistors. They function like valves that adjust the flow of electricity from a feedback thermometer in response to changes in skin temperature. As warming skin heats a probe, the valve opens, and more current flows. As cooling skin chills the probe, the valve closes, reducing the current (Peek, 2016). Thermistors exhibit a negative temperature coefficient (resistance to current flow drops with rising
temperature).
A thermistor is typically enclosed in an epoxy bead. The
smaller the bead's mass, the faster the thermistor's responsiveness to
changes in arteriole blood flow. For an analogy, a smaller pot of water boils more quickly than a larger pot. A Mind Media thermistor is shown below.
There is a time lag between a change in arteriole diameter and a feedback
thermometer's display of the new temperature. This phenomenon, called
thermal lag, consists of physiological and hardware components. Capillary
response and skin storage of heat may slow response for several seconds.
Thermistor sluggishness may add a 1-second delay. By the time blood volume
change registers as a change in temperature, it has been significantly "averaged" (Peek, 2016).
A thermistor's speed is specified by its time constant. A time constant
is the period required for the thermistor to reach 63.2% of a final
value.
You're sitting in a 74°F (23.3° C) room. How long should a thermistor
with a 1-second time constant take to register a hand temperature of 92° F (33.3° C)?
Answer: A thermistor
will reach 99.8% of your hand temperature
in 5 time constants, or 5 seconds.
Time constants of 1 second or faster are
recommended in clinical work to minimize the time lag between the
temperature display and changes in blood vessel diameter.
Thermistor Attachment
Four precautions should be taken when attaching a thermistor. First, you
should securely attach the first 3-5 inches (76-127 mm) of the thermistor to your
client's skin using porous tape on the index finger. Taping ensures the thermistor bead's secure attachment to the skin.
The existence of a stem effect in which body temperature is averaged with air temperature has been challenged (Zerr et al., 2015).
Second, when a thermistor is placed on a digit like a finger, the tape
should be applied over the bead and cable (following the cable), not
around the circumference of the digit, which could reduce blood flow and
falsely lower readings.
Third, you should use only one tape layer since overwrapping could trap heat and artificially raise temperature via a blanketing effect of nearly 1°F (Zerr et al., 2015).
Finally, you should tape the thermistor cable down to your client's
shirt or blouse (and possibly a reclining chair) with adequate slack to
prevent movement artifact (sensor decoupling from the skin and signals
produced by cable vibration).
Thermistor Placement
A thermistor should be attached using Velcro ® or Coban™ self-adhering tape to a site on the hand or foot that is
well-supplied with blood vessels. The digits of the hand and web dorsum,
located on the back of
the hand (between the thumb and index finger), are two of many acceptable sites.
Velcro ®
Coban tape™
Thermography (infrared imaging) has shown that no single
site is most responsive to stressors or relaxation exercises across most individuals. Monitor several sites simultaneously for widespread vasodilation and autonomic change. Warming can be confined to the digit you are monitoring. A client's feet can remain cold while the hands are warm.
Room Conditions
When measuring temperature, the room should be around 74° F(23° C). Rooms
below 68° F (20° C) may produce a downward temperature drift. A client
should be protected from drafts and cool surfaces and seated with
good neck and knee support. Plants may be used to diffuse drafts.
Conversely, warm rooms may elevate temperatures. A corpse's hand
temperature will be 90° F (32° C) in a 90° F (32° C) room.
Thermistors attached to the hand should be heart-level or lower since
temperature may drop if you place the hand above the heart.
Checking Thermistor Accuracy
Use an alcohol or mercury thermometer as your reference to test feedback
thermometer accuracy.
A feedback thermometer should be accurate to within ± 1 degree F.
Place the thermistor next to the mercury
thermometer and compare room temperature values. If they are within 1° F, the thermistor's accuracy is acceptable.
The most common cause of a malfunction is a damaged thermistor. If the
feedback thermometer varies from your reference thermometer by more than
1° F or fails a tracking test, start your troubleshooting by
replacing the thermistor.
Tracking Test
You can determine whether a temperature display mirrors a thermistor's
temperature by performing a tracking test
during which you gently blow on the thermistor bead to warm it.
The
temperature signal should increase within 20-30 seconds after blowing warm air over it. The temperature will decrease after
you stop.
A tracking test checks the integrity of the entire signal chain from the
thermistor to the encoder and the correct software selection of input
channels. A tracking test ensures that a
thermistor is intact, snugly inserted into the correct encoder
input and that you have chosen the right channel for display.
Baselines
For research purposes, a baseline period should allow temperature to
stabilize within 0.5° F (0.28° C) for 5 minutes. Baseline length
will vary
with each subject between 15 and 45 minutes in a 74° F (23° C) room. Exposure to cold outdoor temperature can delay stabilization by 20 minutes (Khazan, 2013).
Due to practical concerns, clinical baselines are often as brief as 5
minutes during training sessions. If a client hasn't stabilized before
the training session starts, warming during the session may reflect
an adjustment to the room environment instead of self-regulation.
Typical finger temperatures exceed 88° F (31° C), and toe temperatures reach about 85° F (29° C).
Clinicians can up-train finger temperature to 95° F (35° C) and toe temperature to 93° F (34° C) in a 74° F (23° C) room (Khazan, 2013, pp. 45, 159).
How a Feedback Thermometer Works
A feedback thermometer detects temperature indirectly.
This device passes
a DC signal through a thermistor and back to a voltmeter. The voltmeter
measures the return voltage, which is referenced to absolute temperature.
For example, if a temperature module's output voltage were +4 VDC (volts
DC), this might correspond to a temperature of 100° F (38° C).
Feedback thermometers use operational amplifiers to boost and process DC
voltages. A basic operational amplifier is a high-gain DC amplifier that
uses external feedback to add, subtract, or average thermistor signals.
Feedback thermometers use operational amplifiers to calculate absolute
temperature, average temperature, derivative temperature, and
differential temperature.
The DC signal that leaves the operational amplifier is filtered above 1
Hz to prevent contamination by 50/60Hz and radio frequency (RF)
interference. A low-pass filter selects signals below the 1-Hz cutoff
frequency for processing by an integrator.
The filtered DC signal is not rectified since it is already DC.
Rectification converts AC signals into DC signals to allow the measurement of
signal strength. This voltage is then sent to an integrator for quantification like a rectified EMG signal.
Next, a level detector checks whether the integrated voltage matches a
predetermined threshold value to control the feedback display. The
training threshold can be adjusted automatically by software or manually
by a clinician to shape patient performance progressively.
Feedback Thermometer Accuracy
A feedback thermometer should be accurate to within ± 1° F (0.56°
C) when
monitoring temperatures from 65 to 100° F (18-38° C). A feedback display
should have a resolution (should display change) of at least 0.1° F (0.1° C) for clinical applications (Peek, 2016).
Smartphones can now function as feedback thermometers with specially designed hardware and apps like
Mindfield's eSense Temperature.
Drug Effects
The reviewed references describe effects on peripheral blood flow. Vasodilation may result in increased BVP and skin temperature. No studies directly measured skin temperature. As with all side effects, the change and its magnitude will vary across the population.
Infrared Thermometers
Peper and Olesen (1985) recommended that clinicians use a portable infrared thermometer to rapidly scan multiple sites on the same person or different individuals, monitor and provide temperature feedback from sites that a thermistor should not touch, and monitor temperature covertly.
An infrared thermometer may require ~ 0.5 seconds to measure the temperature of a single site on the hand. This speed permits a clinician to
sequentially scan 10 different locations on the same patient in 5 seconds. Using a thermistor with a 1-second time constant, a clinician can only measure the temperature of a single
site in the same 5 seconds.
When a clinician is more concerned about the relative
temperatures of multiple sites than their absolute values, an infrared
thermometer's accuracy of ±
1 to 2° C (1.79 to 3.58° F) favorably compares with the ±
1° C
(1.79° F) accuracy of clinical-grade thermistors. A Fluke infrared
thermometer is shown below.
Photoplethysmograph
Blood Volume Pulse (BVP)
Blood volume is the amount of blood contained in an area. This measure
mainly reflects venous tone.
Blood volume pulse (BVP) indexes rapid changes in blood flow. It is calculated
as the vertical distance between the minimum value of one pulse wave and
the maximum value of the next. This measure mainly reflects blood flow
and arteriolar tone (Peper, Shaffer, & Lin, 2010). Below is a BioGraph ® Infiniti BVP display.
PPG Sensor
Blood volume pulse is detected using a photoplethysmograph (PPG). This
device measures the relative amount of blood flow through tissue using a
photoelectric transducer.
An infrared (7000-9000o A) light source is transmitted through or
reflected off the tissue. The transmission technique places the light source and photodetector on the opposite sides of a digit.
The reflection technique places both light
source and photodetector on the same side of the tissue. In both methods, the intensity of the light reaching the
sensor varies with momentary shifts in blood volume (Shaffer & Combatalade, 2013).
The interval between successive peaks (A) is called the interbeat interval (IBI). The peak-to-trough difference (B) shows the relative blood flow (Matto, 2018).
A photodetector detects and converts light into a positive DC signal in both transmission and reflectance modes.
Blood appears red because it reflects red wavelengths. More light is reflected, and the BVP signal increases when the volume of blood increases. (1) As blood surges, more light is reflected, and the BVP signal peaks as the volume of blood increases. (2) As the pulse wave travels through the vascular tree, it is reflected by the lower body and appears as a second smaller peak. (3) The dicrotic notch is the gap between the direct and reflected waves.
The ear is less prone to artifact than the finger due to less movement, stronger signal, and less risk of vasoconstriction due to temperature. Since the ear is closer to the heart than is the finger, there is less opportunity for the vascular tone rhythm to contaminate HRV frequency-domain measurements in the VLF, LF, and HF ranges (Lehrer, 2018b).
The thumb is an excellent site when a client's fingers are too small or have insufficient blood
flow to detect a strong pulse (Peper, Shaffer, & Lin, 2010). In the Flir infrared image below, the thumb is brighter than adjacent digits because of its greater perfusion with blood.
Smartphone cameras can now detect instantaneous heart rate from a digit (e.g., Instant Heart Rate) or the face (e.g., What's
My Heart Rate).
When inspecting the raw blood volume pulse signal, a
strong signal is a wave with a "sharp upswing and a longer downswing"
(Garber, 1986). The peak should be slightly rounded. Measurement units are arbitrary and proportional to the
sensor's voltage
output. The sensor's DC output is boosted by an operational amplifier.
The DC signal is then routed to an integrator for quantification.
Each heartbeat briefly increases blood volume in the arteries and capillary beds. The blood volume pulse signal
can be used to calculate HR (beats per minute) by measuring the
interbeat interval (the period between successive heartbeats). Divide the time
interval between peaks by 60 seconds to calculate HR (Peper, Harvey, Lin, Tylova, & Moss, 2007).
Caption:Heart rate is derived from blood volume measures by measuring the interbeat interval and then transforming this information into beats per minute. For example, the interbeat interval of 0.80 seconds is equal to a HR of 75 beats per minute, whereas the interbeat interval of 0.93 seconds is equal to a HR of 64.5.
Clinicians may simultaneously monitor blood volume pulse, blood volume amplitude (relative volume of blood),
HR, and respiration during training to increase HRV, as shown in the display
below from Peper, Harvey, Lin, Tylova, and Moss (2007).
Caption: The data represent an average respiration rate of 7 breaths per minute with a corresponding HR of 73 beats per minute with a standard deviation of 10.1 beats
Limitations to Photoplethysmography
There are two main limitations to blood volume pulse. First,this blood flow index
only describes blood volume under the sensor. The blood volume in
another area can be vastly different than in another.
Second, blood volume pulse measurements are relative. Absolute values
cannot be compared across different individuals as with hand temperature.
However, values can be compared across a training session, and relative
measures can be compared across individuals (Peper, Shaffer, & Lin, 2010).
The BVP and ECG methods may yield different HRV values with marked sympathetic activation. ECG values will be more accurate since they are not affected by vasoconstriction.
Advantages to Photoplethysmography
A photoplethysmograph can provide high-resolution feedback when
temperature feedback shows minimal change. A PPG sensor
is more sensitive to rapid blood volume changes. Blood volume pulse could quickly drop 50-60% in a patient who is a vascular responder (fingers cool when challenged by stressors). When a client plateaus (ceases to warm), a clinician could switch to blood volume pulse
biofeedback to increase hand-warming if the monitored hand is not significantly vasoconstricted.
Skin Preparation
Unlike the ECG recording, minimal skin preparation is required since the PPG sensor detects infrared light instead of an electrical potential.
Ask your clients to wash their hands so that dirt won’t occlude the sensor’s transducer window (Shaffer & Combatalade, 2013).
For PPG sensors that pass infrared light through the finger, instruct clients to avoid dark fingernail polish, which will block light transmission.
Sensor Attachment
Photoplethysmograph (PPG) sensor attachment is critical since readings
are sensitive to limb position, 50/60Hz artifact, ambient light, movement,
and pressure.
For finger placements, attach the PPG sensor using a Velcro ® band or Coban™ tape to the palmar side of a larger finger (or thumb) and confine the sensor to only one finger segment.
Use the thumb when the fingers are
small, or blood flow is compromised, such as when clients have cold hands (Peper, Shaffer, & Lin, 2010).
For
temporal artery placement, lightly press your first or second finger to
detect a pulse between the corner of the eye and eyebrow (near the
hairline). When you display the raw signal, the best location will produce the highest amplitudes and cleanest signals. A Mind Media BVP sensor is shown below.
Limb Position
Sensor position relative to the heart strongly affects blood volume
pulse. If the PPG sensor is placed on a limb below the heart, BVP signal amplitude increases. We can take advantage of this phenomenon when signal amplitudes are weak (Lehrer, 2018b).
If the limb is placed above the heart, the signal amplitude decreases.
These changes appear to reflect venous filling (Peper, Shaffer, & Lin, 2010).
BVP Artifacts
Artifacts are false values produced by the client's body (ectopic beats) and actions (movement), the environment (line current), and hardware limitations (light leakage).
Short-term values are proxies of 24-hour values. Never compare the short-term values shown below with 24-hour norms. Twenty-four-hour values are typically greater and can predict morbidity and mortality, while most short-term values cannot.
Cardiac Conduction Artifacts
Cardiac conduction artifacts include atrial fibrillation, premature atrial contractions,
and premature ventricular contractions.
Atrial fibrillation is a form of supraventricular arrhythmia, with HRs reaching 160 beats per minute (Tortora & Derrickson, 2021).
Cardiac conduction is chaotic in clients who experience this disorder.
Atrial fibrillation appears as a low-amplitude BVP signal (see the left side of the enlarged view) with a faster HR.
Premature atrial contractions (PACs) involve early atrial contraction, are characterized by abnormally-shaped P-waves and result in calculating extra beats (Lehrer, 2018b).
Premature ventricular contractions (PVCs) can result in an extra heartbeat followed by a full compensatory pause (Clinical ECG Interpretation, 2018).
PVC artifacts are extra heartbeats that originate in the ventricles instead of the S-A node of the heart and can distort the BVP signal (Elgendi, 2012). Clinical Tips to Minimize Cardiac Conduction Artifacts
Since
atrial fibrillation, PAC, and PVC artifacts
cannot be prevented, they must be eliminated
by artifacting.
Cold Artifact
Cold artifact, produced by cold exposure or sympathetically-mediated vasoconstriction, can reduce or eliminate a pulse wave. Cold artifact may result in missed beats, resulting in artifactually-lengthened interbeat intervals (Shaffer & Combatalade, 2013).
You won't see it if your data acquisition system filters out the high-frequency component of the raw BVP signal before displaying it. The graphic below from Elgendi shows a 50-Hz peak and 100-Hz harmonic (left) and contamination of the raw BVP signal (right).
Movement Artifact
Sensor movement artifact is the leading cause of BVP signal distortion and can eliminate the signal or result in
extra or missed beats (Elgendi, 2012; Shaffer & Combatalade, 2013).
Sensor movement can interfere with infrared light transmission by the PPG
sensor or allow contamination by ambient light.
Movement artifacts are colored red in this graphic by Couceiro et al. (2014).
Inspection of the raw BVP can detect movement artifacts. Below is a BioGraph ® Infiniti BVP display of
movement artifacts. Note the appearance of ripples and distortion in the shape of the waveform.
Movement
artifacts can distort the BVP waveform in different ways.
Standing and sitting can produce blood
pressure-mediated upward and downward drifts. Arm movement above or below the heart can also generate drifts.
Repeated movements like finger tapping can create waveforms with ripples that resemble multiple notches.
The display may show sudden changes in the raw BVP signal and HR.
Below is a close-up view of sudden HR increases.
Pressure Artifact
Pressure artifact can be caused by wrapping a restraining band too tightly.
Patients may report throbbing when a
Velcro ® band is wrapped too tightly around a finger. Pressure can reduce raw signal amplitude, resulting
in smaller values or a flat line, and may prevent detecting the peak of the pressure wave. Missed beats can cause artifactually longer IBIs and slower HRs (Shaffer &
Combatalade, 2013).
Excessive pressure can also be caused by resting too much weight (e.g., hand pressing sensor against a knee or table) on the PPG sensor. Pressure artifact reduces
the amplitude of the raw signal resulting in smaller values (Peper, Shaffer, & Lin, 2010).
The graphic below from Elgendi (2012) shows multiple artifacts, including arrhythmia, EMG, low-amplitude, and movement, which can render an epoch unusable.
Tracking Test
You can determine whether the ECG or BVP signals respond to your client's breathing by observing whether their instantaneous HR speeds during inhalation and slows during exhalation.
The reviewed references describe effects on peripheral blood flow. Vasodilation may result in increased BVP and skin temperature. No studies directly measured BVP. As with all side effects, the change and its magnitude will vary across the population.
What should you do if the BVP signal is too weak to detect the peak of the pressure
wave?
Shift the PPG sensor to the thumb or earlobe from a finger. If you cannot record from the thumb
because it is vasoconstricted, allow your client to warm the digit using relaxation, dipping the hands in a warm
basin of water, or placing them in front of a space heater. If none of these options work, use the ECG method.
Normal Values
Please click on the podcast icon below to hear a full-length lecture.
Normal resting HR values range from 60-80 beats per minute.
Following a stressor, clinicians may measure elevations above baseline and the time required to recover to baseline values (Khazan, 2013, p. 46).
Heart Rate Variability
Clinicians use PPG or ECG sensors to detect interbeat intervals. PPG sensors use the peak of the pressure wave, and ECG sensors use the R-spike to determine when a heartbeat has occurred.
ECG sensors measure HR more accurately than PPG sensors, but their placement requires skin preparation, more
time, and the use of disposable supplies and may involve the partial removal of clothing. The PPG method is more straightforward and achieves acceptable accuracy for clinical work, but it is especially vulnerable to movement artifact and vasoconstriction of the digits.
Sensor Placement
Three- or four-lead electrode assemblies are sufficient to record the ECG signal. There is no universal color-coding system for ECG electrodes (Lehrer, 2018b).
ECG sensors can be identical to EMG sensors. Standard lead cables
have snap buttons onto which the electrodes are affixed. A Mind Media EXG sensor is shown below.
Dry or gelled electrodes can be used. Pre-gelled disposable ECG electrodes save preparation time and reduce the
risk of infection.
Six standard ECG electrode placements can be used. These include the wrist, wrist-to-ankle, forearm, lower torso, and chest (upper chest/xiphoid; heart level).
These placements differ in vulnerability to skeletal muscle (EMG) or movement artifact, speed of application, and
degree of client comfort.
A wrist placement requires electrode straps instead of adhesive electrodes. One strap is used to attach an active electrode to the right wrist, the other to secure the reference and the second active electrode to the left wrist. While the easiest, most socially comfortable, and quickest ECG electrode placement is highly vulnerable to arm EMG artifact and movement artifact.
Wrist-to-Ankle Placement
Place the active (+) electrodes on the left wrist and ankle and the reference (-) electrode on the right wrist.
A forearm placement locates an active electrode on the right forearm and the reference and second active electrodes on the left forearm. Select an area with minimal or no hair. This placement is more vulnerable to arm and chest EMG artifact and movement artifact contamination.
Lower Torso Placement
A lower torso placement suggested by Peper (2010) centers the reference electrode over the angle of the sternum and the active electrodes about 5 centimeters above the navel and 10 centimeters to the left and right of the midline. This placement provides an alternative for clients who are uncomfortable exposing their chests (they can
lift their blouse or shirt) and is less vulnerable to arm EMG artifact and movement artifact.
Chest Placement
A chest placement locates active and reference electrodes over the right and left coracoid processes, respectively, and a second active electrode over the xiphoid process. This placement reduces the risk of arm muscle artifact but exposes the chest area, which can be uncomfortable for female clients (Shaffer & Combatalade, 2013).
An alternative chest placement locates all three electrodes in a row at heart level. This sensor arrangement can detect the largest-amplitude R-spikes (Lehrer, 2018b).
Placement Summary
Wrist or forearm placements offer greater client comfort and quicker application speeds where EMG and movement artifacts don't contaminate your recordings. The lower torso placement may be best for research when these artifacts are present.
Sensor placement on the upper chest and abdomen requires client/participant education and written informed consent.
ECG/EKG Artifacts
ECG recording is vulnerable to diverse artifacts. Missing or extra beats, 50/60Hz
noise, EMG, respiration, movement, DC offset, electromagnetic (EMI), and electrode polarity produce the most important artifacts.
Missed and Extra Beats
HRV software determines the interbeat interval (IBI) by detecting adjacent
beats and measuring the time between R-spikes.
After detecting the first beat, the software starts counting and calculates the first IBI in milliseconds. This process is repeated until the end of the epoch
or data collection period. Graphic adapted from Dr. Richard Gevirtz.
IBI measurements are the basis of statistical calculations of time-domain (pNN50, RMSSD, and SDNN), frequency-domain (VLF, LF, and HF), and nonlinear measurements.
HRV artifacts can be produced by physiological events like atrial fibrillation and premature ventricular contractions (PVCs) or signal distortion.
When prevention fails and artifacts contaminate your recordings, clean-up is critical because a single artifactual IBI value in a 2-minute epoch can markedly distort time- and frequency-domain measurements (Berntson et al., 1997).
Discard a segment when more than 5% of IBI values are corrupted. Depending on the frequency of conduction abnormalities, you may not be able to analyze a contaminated data record.
When distortion prevents software from detecting a heartbeat, this results in a missed beat and a prolonged interbeat interval (IBI) calculation. On the graph below, a missed beat generated the circled IBI (1500 ms).
Conversely, when distortion causes the software to detect an extra beat, this produces an artifactually short interbeat interval (IBI). As emphasized earlier, missed and extra beats also affect PPG recording (Elgendi, 2012).
Inspect the raw ECG signal for line interference, EMG, movement, DC offset, electromagnetic interference, radiofrequency, and polarity artifacts.
Line Interference (50/60 Hz) Artifact
Line interference artifact is the most frequent source of ECG signal
contamination.
It doesn’t affect the BVP signal significantly because it is based on back-scattered or transmitted infrared light. Primary sources of this artifact include computers, computer monitors, fluorescent lights, and power outlets. The line interference
artifact looks fuzzy because high-frequency fluctuations are superimposed on the signal (Shaffer &
Combatalade, 2013).
EMG Artifact
Frequencies generated by the depolarization of skeletal muscles overlap with the ECG spectrum and produce EMG artifacts.
The surface EMG ranges from 1-1,000 Hz (Stern, Ray, & Quigley, 2001), while the ECG extends from 0.1-1,000 Hz (Langner & Geselowitz, 1960). Muscle action potentials from large muscle groups travel to ECG sensors via the process of volume
conduction (Shaffer & Neblett, 2010).
Contraction of muscles in the arm can cause the software to "see" many extra beats and calculate shorter IBIs (Shaffer & Combatalade, 2013).
While EMG artifact affects ECG recordings, it does not contaminate the BVP signal since we detect it using infrared light.
Movement Artifact
Client movement can pull the electrode cable so that the electrode partially (or completely) loses
contact with the skin.
Movement artifact consists of high-amplitude signal fluctuations that cause the software to "see many extra beats and calculate shorter IBIs as with EMG artifact."
Below is a BioGraph ® Infiniti ECG display of movement artifact. The ECG
(also called EKG) waveform abruptly shifts upward after the sixth heartbeat and then returns to normal.
Respiration Artifact
Respiration artifacts can result from dried gel and inadequate skin preparation.
The ECG signal may drift up or down, causing extra or missed beats.
Electromagnetic Interference (EMI) Artifacts
Electromagnetic interference (EMI) artifacts are generated by cell phones when they are less than 6 ft (2 m) from ECG sensors or encoder boxes (Peper & Lin, 2010).
Computer monitors and television screens generate EMI artifacts. These are also called radiofrequency (RF) artifact. High-frequency energy expands outward from a monitor like a cone (Montgomery, 2004).
Also, watch out for audiovisual systems and high-voltage equipment like centrifuges, elevators, and x-ray machines (Lehrer, 2018b).
Polarity Artifact
Polarity artifact occurs when the active electrodes (yellow and blue for Thought Technology) are misaligned with
respect to the heart’s axis.
A low-amplitude downward-oriented R-spike can cause the software to miss beats and
lengthen the IBI.
Software packages can automatically correct for polarity artifact (Lehrer, 2018b).
Tracking Test
Using a respirometer, you can determine whether the ECG signal responds to your client's breathing by observing whether instantaneous
HR speeds during inhalation and slows during exhalation (gray line) (Nederend et al., 2016).
The BioGraph ® Infiniti display below shows that instantaneous HR (pink) speeds and slows as the
abdominal strain gauge (purple) rhythmically expands and contracts.
Which ECG placement would you recommend for HRV training? Why?
Select a wrist or forearm placement when client comfort and preparation time are your primary concerns. If these
placements produce unacceptable movement artifacts, consider Erik Peper's lower torso placement.
Heart Rate Variability Metrics
The BCIA Biofeedback Blueprint does not cover HRV metrics. We briefly cover them to provide more comprehensive coverage. Click on the Read More button to review these measurements.
HRV normative values only apply when clients breathe at average rates. For example, measurements of high-frequency power are invalid when obtained during 6-bpm slow-paced breathing.
This unit explains time- and frequency-domain metrics.
These metrics are derived from the time intervals between successive heartbeats.
HRV Time-Domain Metrics
HRV time-domain indices quantify the amount of HRV observed during monitoring periods ranging from 60 seconds to 24 hours. Three widely-used metrics are the RMSSD, SDNN, and pNN50.
The RMSSD is the root mean square of successive differences between normal heartbeats. The RMSSD reflects rapid beat-to-beat variance in HR and better estimates vagal activity than SDNN (Shaffer, McCraty, & Zerr, 2014). The RMSSD is conceptualized as vagally-mediated HRV (vmHRV; Jarczock et al., 2021).
The RMSSD is the best overall short-term HRV because it is less affected by outliers and artifacts than SDNN (Gevirtz, 2020). A novel ratio of short-term RMSSD and C-reactive protein predicted survival in cancer patients and the general population (Jarczock et al., 2021). The minimum recording period is 5 minutes.
Many HRV apps (Apple Health, Elite HRV, Fitbit) use RMSSD or Ln RMSSD to measure HRV.
Ln means the natural logarithm.
SDNN
The SDNN is the standard deviation of the IBIs of normal sinus beats. The SDNN measures how these intervals vary over time and is expressed in milliseconds. RSA is the primary source of the variation, especially with slow-paced breathing protocols (Shaffer, McCraty, & Zerr, 2014). The minimum recording period is 5 minutes.
pNN50
The pNN50 is the percentage of adjacent NN intervals that differ by more than 50 milliseconds. The pNN50 is closely correlated with PNS activity (Umetani et al., 1998). It correlates with the RMSSD and HF power. The RMSSD typically provides a better assessment of RSA (especially in older subjects), and most researchers prefer it to the pNN50 (Otzenberger et al., 1998). The minimum recording period is 5 minutes.
HRV Frequency Domain Metrics
HRV frequency-domain measurements reveal the sources of physiological changes (Gevirtz, 2020).
The processes that contribute to HRV operate at different speeds and generate different frequencies. Frequency-domain measurements quantify the absolute or relative HRV signal power within each of three frequency bands (very-low-frequency, low-frequency, and high-frequency).
In the graphic below that is courtesy of Dick Gevirtz, very-low-frequency activity is green, low-frequency activity is orange, and high-frequency activity is white.
We express absolute power in ms squared divided by cycles per second (ms2/Hz). Relative power is a frequency band’s percentage of total HRV power. We can express this in normal units (nu) by dividing the absolute power for a specific frequency band by the summed absolute power of the low-frequency (LF) and high-frequency (HF) bands.
While normal units allow us to compare the spectral distribution in two clients directly, they conceal the actual contributions of each frequency band to HRV (Gevirtz, 2020). Journals now prefer the natural logs of LF and HF power.
Very-Low-Frequency Band
The very-low-frequency (VLF) band (0.0033-0.04 Hz) requires a recording period of at least 5 minutes but may be best monitored over 24 hours (Task Force, 1996). There is uncertainty regarding the physiological mechanisms responsible for this band's activity (Kleiger et al., 2005).
In short-term recordings, VLF elevations may signal vagal withdrawal (parasympathetic suppression) due to chronic worry or excessive effort (Gevirtz, 2017). Due to its slow speed, it is not sympathetic. In the left FFT spectral plot, VLF power is colored gray.
Low-Frequency Band
The low-frequency (LF) band (0.04-0.15 Hz) is affected by breathing from ~3-9 bpm (Task Force, 1996). The baroreflex system's resonance falls within the LF band. Use LF band power to assess the success of HRVB while your client breathes from 4.5-7.5 bpm (Shaffer & Ginsberg, 2017). When LF band power increases, VLF- and HF-band power may decrease.
A single high amplitude peak near 0.1 Hz indicates high coherence within the Institute of HeartMath model.
Caption: The Institute of HeartMath display shows instantaneous HR at the top. The bottom left is an HRV spectral display. Note that there are two peaks around 0.1 Hz instead of one. The bottom right are coherence ratios. Note that the individual has only achieved 68% high coherence at the low challenge level.
Coherence is a proprietary HeartMath term that means a "narrow, high-amplitude, easily visualized peak" from 0.09-0.14 Hz (Ginsberg, Berry, & Power, 2010, p. 54).
While there is disagreement regarding this band's activity sources, a sympathetic role during resting measurements appears unlikely (Hayano & Yuda, 2019). The PNS and blood pressure regulation may produce LF power via baroreceptors (Akselrod et al., 1981; Berntson, Quigley, & Lozano, 2007; Lehrer, 2007; Task Force, 1996) or by baroreflex activity alone (Goldstein et al., 2011). Breathing at rates below 8.5 breaths per minute, sighing, and taking deep breaths may contribute to LF activity via the vagus (Shaffer, McCraty, & Zerr, 2014).
High-Frequency (HF) Band
The high-frequency (HF) or respiratory
band (0.15-0.40 Hz) is influenced by breathing from 9-24 bpm and requires a recording period of at least 1 minute. HF power is highly correlated
with the pNN50 and RMSSD time-domain measures (Kleiger et al., 2005). The HF band reflects parasympathetic activity and is called the respiratory band because it corresponds to the respiratory cycle's HR variations.
Use HF band power and time-domain metrics like RMSSD to assess HRV biofeedback training success during resting baselines (Shaffer & Ginsberg, 2017).
Summary Tables
Summary of Cardiovascular Instrumentation
Drug Effects
Acknowledgment
This unit draws heavily on graphics published in Didier Combatalade’s Basics of Heart Rate Variability Applied to Psychophysiology, published by Thought Technology Ltd. Didier is the Director of Clinical Interface at Thought Technology Ltd and a gifted educator, writer, and generous colleague.
Glossary
absolute power: the magnitude of HRV within a frequency band measured in milliseconds squared divided by cycles per second (ms2/Hz).
atrial fibrillation: a form of supraventricular arrhythmia with a HR of up to 160 beats per minute.
bead thermistor: a temperature sensor that encases the thermistor in an epoxy
bead.
blood volume: the tonic changes in the amount of blood in an arm, leg, or digit.
blood volume pulse (BVP): the phasic change in blood volume with each heartbeat. It is the vertical
distance between the minimum value (trough) of one pulse wave and the maximum value (peak) of the next measured using
a photoplethysmograph (PPG).
breathing harness: a respiration sensorthat changes resistance to a
current as it expands and contracts during the respiratory cycle.
cardiac conduction artifacts: an ECG artifact due to cardiac conduction abnormalities like atrial fibrillation, premature atrial contractions, and premature ventricular contractions.
DC offset artifact: an ECG artifact that lengthens the IBI when differences in
skin-electrode impedance produce signal drift causing the software to miss beats.
electromagnetic interference (EMI) artifact: an ECG artifact generated when cell phones or computer monitors transmit an artifactual voltage.
EMG artifact: an ECG artifact that shortens the IBI when signal contamination by the
EMG causes the software to detect nonexistent beats.
extra beats: an ECG artifact that shortens the IBI when signal distortion causes
the software to detect nonexistent beats.
feedback thermometer: a temperature biofeedback device that passes a DC signal
through a thermistor and back to a voltmeter.
frequency-domain measures: the calculation of the absolute or relative power of the HRV signal within four frequency bands.
HR: the number of heartbeats per minute, also called stroke rate.
heart rate variability (HRV): the beat-to-beat changes in heart rate, including changes in the RR intervals between consecutive heartbeats.
high-frequency (HF) band: an ECG frequency range from 0.15-0.40 Hz that represents the inhibition and activation of the vagus nerve by breathing (respiratory sinus arrhythmia).
HR Max-HR Min: an index of HR variability that calculates the difference between the highest
and lowest HRs during each respiratory cycle.
HRV triangular index: a geometric measure based on 24-hour recordings that divides
the number of NN intervals by the number of NN intervals found within the modal 8-millisecond bin.
impedance: the opposition to AC flow.
interbeat interval (IBI): the time interval between the peaks of successive R-spikes (initial upward
deflection in the QRS complex). The IBI is also called the NN (normal-to-normal) interval.
light artifact: a PPG artifact when light leakage increases BVP amplitude.
line interference artifact: ECG and PPG artifact when 50/60Hz contamination of
signals causes the software to detect nonexistent beats and shorten the IBI.
low-frequency (LF) band: an ECG frequency range of 0.04-0.15 Hz that may represent the
influence of PNS, SNS, and baroreflex activity (when breathing at resonance frequency).
low-pass filter: an electronic device that selects frequencies below a cutoff frequency like 1 Hz in a
feedback thermometer.
missed beats: BVP and ECG artifact that lengthens the IBI when signal distortion
causes the software to overlook a beat and use the next good beat.
movement artifact: ECG and PPG artifact that shortens the IBI when signal
distortion from movement causes the software to detect nonexistent beats.
negative temperature coefficient: the resistance to a DC declines
as temperature rises.
NN50: the number of adjacent NN intervals that differ from each other by
more than 50 milliseconds.
normal units: the division of the absolute power for a specific frequency band by the summed absolute power of the low frequency (LF) and high frequency (HF) bands.
operational amplifier: a high-gain DC amplifier that uses external feedback to add,
subtract, or average thermistor signals.
photoelectric transducer: a phototransistor that detects infrared light transmitted by a PPG sensor and
converts it into a positive DC signal.
photoplethysmographic sensor: a photoelectric transducer that transmits and detects infrared light that
passes through or is reflected off tissue to measure brief changes in blood volume and detect the pulse wave.
plateau: in temperature biofeedback, lack of change in skin temperature.
pNN50: the percentage of adjacent NN intervals that differ from each other by more
than 50 milliseconds.
polarity artifact: an ECG artifact when reversed electrode placement inverts the
direction of the R-spike and causes the software to miss beats and lengthen the IBI.
premature atrial contraction (PAC):
abnormally-shaped P-waves that result in calculating extra beats and and distorting the BVP and ECG signals.
premature ventricular contraction (PVC):
extra heartbeats that originate in the ventricles instead of the S-A node of the heart and can distort the BVP and ECG signals.
reference electrode: a ground (sometimes black) ECG electrode that may be placed on the left upper chest, below the
palmar aspect of the left elbow, or above the palmar aspect of the left wrist.
relative power: the percentage of total HRV.
resolution: degree of detail in a biofeedback display (0.1 millivolts) or the number of
voltage levels that an A/D converter can discriminate (16 bits or discrimination among 65,536 voltage levels).
respiration artifact: an ocean-wave-like distortion of the ECG due to dried gel and inadequate skin preparation.
RMSSD: the square root of the mean squared difference of adjacent NN
intervals.
SDANN: the standard deviation of the average 5-minute NN intervals that
estimates HR changes produced by cycles longer than 5 minutes.
SDNN: the standard deviation of the interbeat interval measured in
milliseconds.
SDNN index: the average of 5-minute standard deviations of NN intervals
across 24 hours that measures the contribution of rhythms briefer than 5 minutes to HRV.
SDRR: the standard deviation of the interbeat interval for all sinus beats
measured in milliseconds.
stem effect: the distortion of temperature measurements by ambient temperature when
the first 3-5 inches of a thermistor are not secured against the skin.
thermal lag: the time lag between the change in arteriole diameter and a feedback
thermometer's display of the new temperature.
thermistor: a temperature-sensitive resistor.
time-domain measurements: HRV indices that quantify the variability in interbeat interval measurements (IBI).
tracking tests: checks of whether the biofeedback display mirrors client behavior. BVP amplitude and instantaneous heart
rate detected by BVP and ECG sensors should speed and slow as clients inhale and exhale. For example, temperature should increase as you blow warm air over a thermistor bead.
transmission technique:
the PPG sensor light source and photodetector are placed on opposite sides of a digit.
ultra-low-frequency (ULF) band: an ECG frequency range below 0.0033 Hz represents
very slow-acting biological processes and is too gradual to train using conventional biofeedback.
vascular responder: a response pattern where BVP and skin temperature may
significantly decrease in response to a stressor.
very-low-frequency (VLF): an ECG frequency range of 0.003-0.04 Hz that may represent
temperature regulation, gastric, plasma renin fluctuations, endothelial and physical activity influences, and possible PNS and
SNS contributions.
web dorsum: a temperature monitoring site on the back of the hand between the thumb and index finger.
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Essential Skills
Blood volume pulse
1. Explain the blood volume pulse signal and biofeedback to a client.
2. Explain PPG sensor attachment to a client and obtain permission to monitor her.
3. Explain how to select a placement site and demonstrate how to attach a PPG sensor to minimize light and movement
artifacts.
4. Perform a tracking test by asking your client to raise the monitored hand above the heart and lower it.
5. Identify common artifacts in the raw PPG signal, especially movement, and explain how to control them and
remove them from the raw data.
6. Explain the significant measures of HRV, including HR Max - HR Min, pNN50, SDNN, and SDRR.
7. Explain why we train clients to increase power in the low-frequency band of the ECG and how breathing at 5-7
breaths per minute helps them accomplish this.
8. Demonstrate how to instruct a client to utilize a feedback display.
9. Describe strategies to help clients increase their HRV.
10. Demonstrate an HRV biofeedback training session, including record keeping, goal setting, site selection, baseline
measurement, display and threshold setting, coaching, and debriefing at the end of the session.
11. Demonstrate how to select and assign a practice assignment based on training session results.
12. Evaluate and summarize client/patient progress during a training session.
Heart rate
1. Explain the ECG signal and biofeedback to a client.
2. Explain ECG sensor attachment to a client and obtain permission to monitor her.
3. Explain how to select a placement site and demonstrate how to attach ECG sensors to minimize movement
artifacts.
4. Demonstrate skin preparation.
5. Perform a tracking test by asking your client to inhale slowly and then exhale as you watch the change in heart
rate.
6. Identify movement artifact in the raw ECG signal and explain how to control movement and remove it
from the raw data.
7. Explain the significant measures of HRV, including HR Max - HR Min, pNN50, SDNN, and SDRR.
8. Explain why we train clients to increase power in the low-frequency band of the ECG and how breathing at 5-7
breaths per minute helps them accomplish this.
9. Demonstrate how to instruct a client to utilize a feedback display.
10. Describe strategies to help clients increase their HRV.
11. Demonstrate an HRV biofeedback training session, including record keeping, goal setting, site selection,
baseline measurement, display and threshold setting, coaching, and debriefing at the end of the session.
12. Demonstrate how to select and assign a practice assignment based on training session results.
13. Evaluate and summarize client progress during a training session.
Temperature
1. Explain the temperature signal and biofeedback to a client.
2. Explain thermistor attachment to a client and obtain permission to monitor her.
3. Explain how to select a placement site and demonstrate how to attach a thermistor to minimize blanketing,
movement, and stem artifacts.
4. Perform a tracking test by asking your client to blow on the thermistor bead.
5. Identify common artifacts in the raw temperature signal, including draft and movement, and explain how to control
them and remove them from the raw data.
6. Demonstrate how to instruct a client to utilize a feedback display.
7. Describe strategies to help clients with cold hands who warm very slowly or cool when they attempt to warm their hands.
8. Demonstrate a temperature biofeedback training session, including record keeping, goal setting, site selection,
whether to record bilaterally or unilaterally, baseline measurement, display, threshold setting, coaching, and
debriefing at the end of the session.
9. Demonstrate how to select and assign a practice assignment based on training session results.
10. Evaluate and summarize client progress during a training session.
Assignment
Now that you have completed this unit, explain when blood volume pulse
feedback could complement temperature biofeedback and why. What is an advantage of a wrist ECG sensor placement over a
chest placement in clinical practice?
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PVC artifacts are extra heartbeats that originate in the ventricles instead of the S-A node of the heart and can distort the BVP signal (Elgendi, 2012).
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