This winter break project served as both exploratory research and creative development for my Program II senior capstone, The Somatic Script: How Performance Writes Itself on the Body. For my capstone project, I’m studying how different modes of performance art affect physiological responses in the body. Specifically, I compare live performance to recorded video and virtual reality.
Over winter break, I obtained the technology needed to collect physiological data. I worked with the BITalino (r)evolution board kit, a biosensing system that can record several biological signals, including:
- EEG (electrical activity in the brain)
- ECG/EKG (electrical activity in the heart)
- EMG (electrical activity in muscles)
- EDA (skin conductance, which reflects physiological arousal)
The BITalino board and input ports used to collect EEG, ECG, EMG, and EDA.
Learning the Equipment and the Limits of Distance
After learning how the board works (what each port does, how to connect to the software, and how to assemble the lead cables and electrodes), my first step was to map out electrode placement on the body. This is where I ran into a practical problem: distance.
I ordered the longest lead cables available because I anticipated that placements would be spread out across the body (for example, EEG on the head and EDA on the palms). However, the cables were still too short to support these two measures at the same time in a way that was stable and realistic for a performance setting. This forced a decision about which signals were most essential for the project.
Why I Dropped EEG Instead of EDA
If I had to remove one measure, I would remove EEG rather than EDA.
EEG measures electrical activity in the brain. While EEG can be very informative, it is also highly sensitive to movement, shifting electrodes, and muscle activity. That makes it difficult to obtain reliable data in a project where motion is central, especially in a performance context. This issue becomes even more relevant in the virtual reality condition, where participants must wear a headset, introducing additional movement and contact that can further disrupt EEG recording.
In contrast, EDA is a more reliable and practical measure in this context. EDA measures changes in skin conductance driven by activation of sweat glands, which is controlled by the sympathetic nervous system. In plain terms: EDA is one way to track physiological arousal and intensity of response, including states like excitement, stress, or heightened engagement. That makes it a strong fit for a study focused on how performance registers in the body.
Defending the Trio: EDA + ECG + EMG
After dropping EEG, I moved forward with a trio of EDA, ECG, and EMG, which provides a strong and complementary physiological framework.
- EDA measures physiological arousal through changes in skin conductance (sympathetic activation).
- ECG measures heart activity, allowing me to track changes in heart rate and broader cardiovascular responses tied to arousal and regulation.
- EMG measures muscle activation, which is especially important in a performance context because it helps quantify physical effort rather than treating movement as “background noise.”
Together, these measures help distinguish between two overlapping components of physiological response:
- autonomic arousal (how the nervous system responds internally), and
- physical exertion (how much the body is working).
That distinction matters in this project because different performance modes may produce different levels of movement or effort, and it is important not to confuse “emotionally engaged” with “physically active.”
Electrode placements used for EEG, EDA, ECG, and EMG.
Learning Curve and At-Home Testing
I began this pilot work with very little experience collecting physiological data. While I have some familiarity with ECG through my EMT background and experience with neuroscience coursework (including fMRI), biosensing technology was new to me and involved a significant learning curve.
To build baseline skills, I used at-home lab guides created by the manufacturer. These guides were extremely helpful in learning how to set up sensors, connect the system properly, and record data. I ran several trials on myself, mainly while watching video stimuli, in order to practice signal acquisition and understand what the recordings look like under relatively controlled conditions.
I also used these trials to test the movement limitations of the system: how much movement creates unusable or noisy data, and what kinds of motion cause the most disruption. This was important because the project relies on performance, and performance necessarily involves movement.
Manufacturer-provided lab guides used to learn signal setup and data recording.
At this stage, I am still working on interpretation. I am now confident in my ability to set up the system and record data, but I will continue learning how to analyze and interpret signals more deeply as the project progresses. I plan to consult professors and use additional resources to strengthen this part of the work.
Studio Work: Reblocking for 360 Recording and VR
When I returned to the studio, I began reblocking the choreography to accommodate 360 recording for the virtual reality condition. Participants will experience the performance through a VR headset, and for that to be possible I need to record each piece using a 360-degree camera.
This required me to rethink how the choreography is oriented in space. Traditional choreography for a live audience is usually structured around a front-facing perspective, since the audience sits in one general direction. With 360 video, that framing changes. The viewer can look anywhere, and “front” becomes less fixed.
To work with this, I began using circular pathways and spatial patterns that guide the viewer’s attention. Some group sections were adjusted to more intentionally direct focus, while solo material was reblocked to travel in a circular pattern that the viewer can follow. I also incorporated moments where dancers move directly toward the camera, including one section where a dancer briefly covers the camera and interacts with it, which changes the viewer’s relationship to the space.
Studio rehearsal and reblocking for 360 recording.
Next Steps
Overall, winter break was a productive pilot period. I gained foundational experience using biosensing technology, clarified technical limitations (especially related to movement), and made design decisions that will directly shape the study moving forward. I am still waiting on the rest of the biosensing boards to arrive, and I will continue refining the setup as the full equipment shipment is completed.
At the same time, I have been extensively planning the live performance condition of the experiment, which is scheduled for January 16.
