This guest post was written by Michael Hogan, BIOPAC’s Southeast Regional Representative. Contact him at email@example.com
Even trained psychologists can be daunted by the interdisciplinary applications involved with recording objective physiological data. However, it is not necessary to learn the intricacies of bio-medical engineering, physics, statistics and underlying physiological mechanisms of the body just to incorporate these objective measures into your research. With just a few key signals of interest, and a simple hardware and software setup, a trained researcher can record and interpret the objective physiological responses of participants in a physiology study.
How to get started? Begin with a protocol you are already studying and incorporate “THE BIG 3”
- ECG: Electrocardiography is a biopotential, meaning direct measurement of the electrical voltage potential changes of the heart as it completes its “cardiac cycle.” Since we can record these voltage changes and graphically represent them as a waveform through analog to digital conversion, we are able to identify changes in the behavior of the heart in response to the presented stimulus. We can then establish a recurring reference point in the “R-Peak” of the QRS complex, we are able to measure the distance between these R-Peaks and establish an R-to-R interval, this measure tells us the time in-between cycles or “beats” of the heart. From one beat to the next, we can establish the participant’s heart rate. Once we have established a heart rate, we are able to extract valuable measures, such as Heart Rate Variability: how the heart rate changes over an observed set of time intervals or in response to the correlated stimulus.
- Respiration: The respiration cycle is what is known as a transduced physiological signal. This means we utilize a mechanical apparatus to create a voltage potential in response to the inhalation and exhalation phases of the respiratory cycle. These voltage changes can then be measured and graphically represented as a waveform for further analysis. The respiratory cycle waveform can tell us the following:
- Respiratory rate: the number of cycles that occur within a given time interval or changes in response to a stimulus.
- Amplitude: What is the change in magnitude of the cycle, shallow vs. deep breathing.
- Respiratory Sinus Arrythmia (RSA): When collected along with an ECG signal, this analysis accounts for the changes in the participant’s heart rate as a response to the inhalation and exhalation phases of the respiratory cycle. For example, the heart rate elevates when the participant inhales and decreases when the participant exhales.
- EDA: Electrodermal Activity has been adopted as the newest nomenclature for Galvanic Skin Response “GSR.” To this day EDA is touted as the best measure of sympathetic nervous system “activation.” As a derivative physiological measure, we pass a small, imperceptible current (0.5 V) into the participant’s body and measure the change from this known value as the participant responds.
As the autonomic nervous system responds to stimuli, it stimulates the eccrine glands to produce sweat. The sweat produced lowers the impedance to the current passing into the participant. We can then measure the change and extract meaningful data regarding how the participant responded to the chosen stimulus.
- Skin Conductance Response (SCR): The magnitude of the response that occurred as a result of the stimulus from its onset to its peak.
- Skin Conductance Level (SCL): How long it took for the response to occur following the chosen stimulus from its onset to its peak.
- Recovery time: How long it takes the response to diminish and return to “baseline/normal” values.
With these “BIG 3” physiological measures we can perform hundreds of research protocols and objectively correlate patterns of behavior. Once these measures have been employed, we can integrate other measures for more comprehensive studies, such as:
- EEG and fNIR for cognitive processing and learning metrics
- Non Invasive Blood Pressure (NIBP) for stress and cardiovascular metrics
- Facial EMG, fEMG, or Facial Coding Software for affective emotional states metrics
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