In physiology and life sciences, researchers rely on a wide range of signals to gather data from humans and animals. These signals provide critical insight into how complex organisms function under a myriad of conditions. However, this wealth of potential data sources can also present a challenge for researchers: choosing the right signals on which to focus their data gathering. For those lacking a background in the disciplines and mechanisms behind these signals, sifting through the available methodology can be overwhelming. The best place to begin is by considering one or a combination of the “Big Three” physiological signals: ECG, EDA, and respiration.
One from the Heart
Changes in heart rate can provide information on both the physiological and psychological state of a research participant. Electrocardiography (ECG or EKG) is a biopotential measurement that provides direct metrics on electrical voltage changes in the heart. With the help of simple hardware and software, it is possible to record these voltage variations as waveforms to track how the heart responds to stimuli. Additional data can be provided by creating reoccurring reference points in the waveform, measuring the intervals between beats, and calculating heart rate variability to track changes over time or in response to stimuli.
Skin Deep
Electrodermal Activity (EDA) provides one of the best measurements of how the body responds to psychological stress and anxiety. It can be simply understood as a measure of changes in the electrical conductance of the skin in relation to the production of sweat. The physiological process of EDA comprises two components, skin conductance level (SCL) and skin conductance response (SCR). SCL is a tonic level that slowly changes over time, measuring the period for response to a stimulus to occur, from its onset to its peak. SCR reflects the phasic response to an arousing stimulus that is shown in faster changes of the skin conductance level. As an example of the application of EDA and ECG measurements in psycho-physiological research, a recent study applied both signals in measuring the cognitive states of gamers during human-computer interaction (HCI).
Breathe Easy
As with changes in heart rate, variations in breathing cycle reveal how subjects respond to a wide range of stimuli and conditions. The signal produced by the respiratory cycle is a transduced physiological signal. As such we can apply mechanisms to create a voltage potential to measure phases of inhalation and exhalation in this cycle. This data can be represented in waveforms, providing data on respiratory rate, amplitude, and respiratory sinus arrhythmia (RSA). The latter combines respiratory data with ECG signal data to show changes in heart rate in response phases in the respiratory cycle. A 2020 machine learning study for the development of virtual reality applications combined respiration, EDA, and ECG signals to measure participant’s fear response to spiders, an example of how all three signals can be simultaneously utilized in psychophysiology research.
Choosing the right signal shouldn’t be the biggest hurdle to designing your next research project. Applying one or more of these “Big Three” can cover a wide range of data gathering goals.
For additional assistance, consult BIOPACS online resources on Life Science and Physiological Signals or contact your local BIOPAC representative.
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