Life Science Data Archives

Capturing More Than Physiology: Multi-Camera and Multimodal Research

In the early 20th century, Cubist painters like Pablo Picasso and Georges Braque argued that traditional linear perspective on a subject was an illusion. Something was always hidden from the viewer, distorted, or lost altogether. Just as a Cubist painter might fracture their subject to reveal its true shape, a physiology lab uses multiple synchronized camera angles to bypass a single lens’ limitations.

The same principle applies to modern physiological and psychophysiological research. Physiological signals such as electrocardiogram (ECG), electroencephalogram (EEG), electrodermal activity (EDA), respiration, and blood flow provide valuable insight into how the body responds to stimuli, environments, and social interactions. Yet physiological data alone often leaves important questions unanswered. What was the participant doing? What was happening in the environment? Did social interaction, movement, or behavioral events coincide with a change in the recorded signal?

To answer these questions, many studies now combine physiological recordings with multiple video streams, eye tracking, audio, environmental monitoring, and other forms of media capture. This multimodal approach lets investigators examine physiological measurements alongside the events occurring around them, revealing a richer, more complete picture of human and animal behavior. As these data streams multiply, so does the need to capture, synchronize, and review them together.

Researchers at Macquarie University in Australia and collaborating institutions recently described a multimodal laboratory designed to study face-to-face communication and social interaction. The platform centered on a BIOPAC data acquisition system, amplifiers, and amplifier input module that acquired ECG, EDA, photoplethysmography (PPG), respiration, and skin temperature. The researchers combined physiological measurements with a Tobii eye tracker, wearable sensors, audio recording, motion analysis systems, and six video cameras positioned throughout the laboratory. The project showed that adding more recording sources often complicates data collection coordination, and that integrating multiple acquisition systems requires careful synchronization and workflow design. The camera system played a particularly important role. They used multiple viewing angles for behavioral coding, gesture analysis, participant observation, and synchronization verification. Rather than serving only as a record of the experiment, the video data became an important part of the analysis itself. For researchers studying communication, teamwork, education, or human-computer interaction, the work illustrates how behavioral observations can enhance interpretation of physiological measurements.

A team from the Swedish University of Agricultural Sciences (SLU) explored similar ideas outside the traditional laboratory by developing the SLU Multisensory Outdoor Laboratory (SENSOLA). The researchers used BIOPAC data acquisition and analysis systems with AcqKnowledge software and BioNomadix wireless devices to collect respiration and PPG measurements as participants moved through natural and built environments. Their platform combined those recordings with eye tracking, stimulation, video, audio, GPS data, participant feedback, and environmental measurements. One key observation was that physiological measurements become much more insightful when paired with information about a participant’s surroundings and experiences. Video proved especially valuable because it documented environmental conditions, participant behavior, and unexpected events that might otherwise be difficult to identify during later analysis. As physiological research moves beyond controlled laboratory settings, projects such as SENSOLA demonstrate the value of capturing physiological and observational data together.

Preclinical research is increasingly applying the same principles. In a recent toxicology study from Japan, investigators developed the ToxQb platform around a BIOPAC data acquisition system and AcqKnowledge software with NDT to collect EEG and ECG data from laboratory rats. The physiological measurements were integrated with overhead, front, and side-view cameras, along with thermal imaging systems. The goal was to monitor behavioral and physiological changes simultaneously over extended periods. By reviewing camera footage alongside EEG and ECG recordings, researchers could relate changes in movement, posture, and activity to physiological events. The authors concluded that combining these diverse data streams provided deeper insight than any single measurement could. The study demonstrates that multimodal acquisition extends beyond human research, across a wide range of life-science applications.

Although these studies span communication research, environmental psychology, and toxicology, they point to a common trend: researchers are capturing much more than physiology. Like the artists who challenged the limitations of a single viewpoint, today’s researchers increasingly rely on multiple synchronized perspectives to reveal a more complete picture of physiology, behavior, and environment. Multiple cameras, video recordings, eye tracking, environmental sensors, and behavioral observations can provide valuable context for interpreting physiological measurements. Learn how using BIOPAC’s MultiCapture feature in AcqKnowledge 6 to integrates multi-camera video and other media into research via our webinar on the topic.

Are you planning to integrate multiple camera perspectives in your next study? Our sales team can help find the right equipment and show you how to leverage AcqKnowledge‘s MultiCapture feature to achieve the best possible results.

No Pain, All Gain: How EMG and Other Physiological Signals Aid Injury Avoidance

It can happen anywhere, anytime: on the pickleball court, during a pristine nature hike, or even while stepping off the front porch on the way to work. An ankle turns, a knee buckles, and suddenly you’re on the ground wondering what just happened. While such injuries often seem random, researchers who study human movement know they are rarely without warning.

Kinesiologists, scientists who study the mechanics and physiology of movement, have found that subtle changes in muscle activation, fatigue, coordination, balance, and neuromuscular control often emerge long before a strain, sprain, or overuse injury becomes apparent. To better understand these hidden danger signs, researchers increasingly rely on physiological measurements that reveal how the body’s muscular, nervous, cardiovascular, and biomechanical systems respond to activity. Such insights help identify injury risk factors and guide strategies designed to keep people moving safely and effectively.

Among the many tools used in kinesiology research, electromyography (EMG) is one of the most common because it reveals when and how muscles activate during movement. However, EMG is only one part of the story. Researchers also study force production, joint motion, movement acceleration, cardiovascular activity, respiration, muscle oxygenation, and neural activity to better understand how the body adapts to physical demands. Together, these measures provide a more complete picture of movement and help uncover patterns that observation alone may miss.

The applications of this work extend far beyond sports. Physiological monitoring helps clinicians evaluate rehabilitation progress, guide return-to-activity decisions, support fall-prevention efforts among older adults, and help design safer workplaces and training programs. Increasingly, researchers are shifting from simply treating injuries to identifying and addressing the factors that contribute to them before they occur.

Researchers in India conducted a cross-sectional study comparing elite and recreational university badminton athletes to explore whether physiological and neuromuscular characteristics could serve as injury-risk markers. The investigators collected a range of performance and neuromuscular measurements, including surface EMG recordings, to examine differences between competitive levels and establish preliminary benchmarks for injury-risk stratification. Surface muscle activity was recorded using a BIOPAC two-channel data acquisition system as part of the neuromuscular assessment protocol. The study found that elite athletes exhibited distinct physiological and neuromuscular profiles compared to recreational players, suggesting that objective physiological markers may help identify movement patterns and performance characteristics associated with increased injury vulnerability. These conclusions support the growing use of physiological profiling to identify athletes who may benefit from targeted injury-prevention strategies before injuries occur.

A team of researchers in Tunisia investigated how fatigue of the ankle evertor muscles affects force perception and neuromuscular function in healthy adults. Ankle injuries are among the most common musculoskeletal injuries in both athletic and recreational populations, making ankle stability an important area of study. Using surface EMG to measure muscle activity before and after a fatigue protocol, the researchers examined how localized fatigue affected participants’ ability to accurately reproduce force levels. Researchers used a BIOPAC EMG amplifier and data acquisition system to record electrical activity from muscles involved in ankle stabilization. The researchers found that fatigue impaired force perception and altered neuromuscular responses, suggesting that fatigue may reduce the body’s ability to control ankle movements accurately. The study results add to growing evidence that fatigue-related physiological changes can increase injury risk, particularly during prolonged exercise or competition when neuromuscular control begins to decline.

A multi-institutional team of researchers from the United States examined neuromuscular function in individuals who had undergone anterior cruciate ligament (ACL) reconstruction, comparing them with healthy controls. The researchers wanted to better understand whether the relationships between muscle performance, muscle activation, and nervous system function change after ACL surgery. Participants completed a series of strength and neuromuscular assessments, with quadriceps muscle activity recorded using a BIOPAC data acquisition system with AcqKnowledge software and an EMG amplifier. BIOPAC isolated stimulators were also used during testing to help determine how fully participants could activate their quadriceps muscles. The study found that several relationships observed in healthy knees were no longer present after ACL reconstruction, suggesting that changes in neuromuscular control can persist long after surgery and rehabilitation are complete. These findings highlight how physiological monitoring can uncover hidden deficits that may not be apparent during routine recovery assessments, helping clinicians make more informed return-to-sport decisions and potentially reducing the risk of future injury.

As these examples demonstrate, physiological measurements give researchers powerful tools to identify injury risk before injuries occur, understand how fatigue alters movement control, and evaluate recovery following musculoskeletal injury. By revealing the physiological mechanisms that influence human movement, signals such as EMG and related neuromuscular measures help bridge the gap between laboratory research and practical injury-prevention strategies. As kinesiology research continues to evolve, physiological monitoring will likely play an increasingly important role in supporting safer movement, more effective rehabilitation, and improved long-term physical performance.

Are you planning a kinesiology-focused study? BIOPAC local sales representatives have the information you need to design and equip your research project.

The Nose Knows: Brain-Body Research and the Science of Olfactory Cognition

“Smell is a potent wizard that transports you across thousands of miles and all the years you have lived.” — Helen Keller

There is something uniquely intimate about the sense of smell. Unlike vision or hearing, olfactory signals travel a remarkably direct neural route from receptors in the nasal epithelium through the olfactory bulb, and straight into the brain’s limbic system, the seat of emotion and memory. A single scent can transport us instantly to a childhood kitchen, sharpen our alertness, or dissolve stress within seconds. Yet for all its power, olfaction has historically been one of the most understudied human senses. That landscape is changing. A new generation of multimodal brain-body research platforms, capable of simultaneously recording signals from the brain and the body, is giving scientists insight into how smell shapes thought, emotion, and cognition.

The olfactory system is the only sensory system that bypasses the thalamus, the brain’s central relay station, and connects directly to the amygdala and hippocampus, two structures critical to emotional processing (affect) and memory. This anatomical shortcut explains why odors are so potent at triggering emotional memories, often more vividly than visual or auditory cues. Beyond memory, researchers are increasingly interested in how odor exposure alters measurable physiological and neurological states in real time, ranging from modulating cognitive performance and stress to the early detection of neurodegenerative disease, in which olfactory dysfunction often appears years before other symptoms emerge.

What makes this research technically challenging is also what makes it scientifically rich: the olfactory experience simultaneously engages the central nervous system and the autonomic nervous system, meaning that studying it well requires capturing signals from both brain and body at once. Electroencephalography (EEG) provides direct data on the brain’s electrical activity with millisecond-level temporal resolution, making it well-suited to detecting rapid shifts in cognition and arousal following odor exposure. Functional near-infrared spectroscopy (fNIRS) offers a complementary picture, using near-infrared light to detect changes in cortical oxygenation, a measure of the brain’s metabolic response to stimulation. Wearable and tolerant of movement, fNIRS is particularly well-suited to naturalistic experimental designs. Electrodermal activity (EDA), or skin conductance, captures the autonomic nervous system’s arousal response through sweat gland activity, while electrocardiography (ECG) and heart rate variability (HRV) add a cardiovascular layer that can distinguish sympathetic from parasympathetic activity in fine detail. Today’s lab setups use a range of sophisticated scent delivery systems to integrate precise, controllable olfactory stimuli into experiments. The real power of modern multimodal platforms lies in their ability to synchronize all these channels within a single setup, time-locking each physiological response to a specific odor event and revealing the full brain-body picture that no single signal could show alone.

A research team at the All India Institute of Medical Sciences in Jodhpur investigated whether citrus odor could buffer the cognitive and physiological impact of working memory load. Thirty participants completed a demanding working memory test under both control and citrus-odor conditions, with the odor delivered via an aroma diffuser. ECG, photoplethysmography (PPG), and EDA were recorded using a BIOPAC data acquisition system with AcqKnowledge software for analysis, and dual-signal BioNomadix wireless EDA and PPG module. For EDA recording, disposable silver/silver chloride disc electrodes were applied to the hypothenar and thenar eminences, and the PPG sensor was placed on the index finger. Citrus odor significantly improved task accuracy while suppressing the rise in skin conductance typically associated with cognitive load. HRV measures, including pNN50, RMSSD, and HF power, shifted toward parasympathetic dominance, indicating a calmer, more regulated physiological state. The findings, published in the Annals of Neurosciences, suggest that citrus odor acts as a cognitive stress buffer and point to practical applications in educational, occupational, and clinical settings with high sustained cognitive demands.

A counterintuitive question motivated a study at Nagaoka University of Technology in Japan: could black pepper, widely known as a stimulant, actually calm the body’s stress response? A group of university students performed a 30-minute arithmetic calculation task under three aroma conditions: black pepper, ginger, and a scentless control. Scents were delivered at precise, reproducible intervals through an olfactometer. A BIOPAC data acquisition system recorded continuous ECG and skin conductance level (SCL) at 200 Hz with 16-bit resolution, with high-frequency HRV (HF-HRV) derived as a measure of cardiac parasympathetic activity. Electrodes were placed beneath the right clavicle and on the lower left abdomen following the Lead II placement protocol for ECG measurements using multi-lead ECG cables. SCL was recorded using skin conductance sensors placed on the palmar side of the middle phalanx of the index and ring fingers of the participant’s non-dominant hand. The results, published in the Journal of Physiological Anthropology, found that black pepper aroma reduced the stress-induced rise in heart rate by 38.9% compared to the scentless control, attenuated the decline in HRV by 32.9%, and blunted the increase in SCL compared to ginger. Crucially, subjective stress ratings did not differ across conditions, demonstrating that the body can respond to olfactory stimuli at a physiological level even when conscious perception does not register a difference. These findings have meaningful implications for workplace wellness and aromatherapy research.

A French consortium of researchers from the Université Bourgogne Franche-Comté and the Université Grenoble Alpes tested whether music, lavender odor, or their combination would accelerate autonomic recovery following acute cognitive stress. Ninety-nine participants completed a battery of cognitively demanding tasks. They were then randomly assigned to one of four 30-minute recovery conditions: silence, relaxing classical music, lavender essential oil, or music and lavender together. A data acquisition system running AcqKnowledge continuously recorded ECG and EDA using Ag-AgCl finger electrodes, with HF-HRV as an index of parasympathetic activity and EDA as a measure of sympathetic arousal. Published in Psychophysiology, the study found that both music and lavender independently facilitated autonomic recovery. The surprising finding, however, was the absence of any multisensory advantage: combining the two stimuli produced no greater benefit than either alone, suggesting that when multiple sensory channels converge on the same relaxation goal, they may share rather than combine their neural resources. The study underscores both the value of multimodal physiological recording in parsing the mechanisms of stress recovery and the importance of rigorously testing assumptions about how the senses work together.

These studies illustrate how much remains to be discovered at the intersection of smell, brain, and body, and how essential it is to measure all three at once. As synchronized multimodal platforms continue to evolve, the science of olfactory cognition continues to shape our fundamental understanding of how the brain works and the development of practical tools to support cognitive health and wellbeing. To learn more about the convergence of olfaction with brain-body research, be sure to check out our webinar on how scents influence cognition.

If you are planning a brain-body study that integrates multimodal data collection with stimulus presentation like scent delivery, our expert staff is ready to help find everything you need to get started.

Muscles in Motion: Electromyography in Physiological Research

When we think about the human muscular system, movement often comes to mind. Activities such as running, lifting, and maintaining posture all rely on coordinated skeletal muscle activity, while cardiac muscle drives circulation and smooth muscle supports essential functions like digestion. Yet muscles do more than move us from point A to B; they also reflect what is happening inside the body. Patterns of muscle activation can reveal information about physical effort, fatigue, coordination, and recovery, as well as emotional expression, stress, and cognitive engagement. Electromyography (EMG) is a widely used technique for measuring the electrical signals generated by muscles during contraction, providing researchers with a direct and objective means to study both physiological function and the links among the nervous system, behavior, and mental state. By capturing muscle activity that may be too subtle to observe visually, EMG enables precise investigation of processes ranging from motor control and performance to emotional and stress-related responses.

There are several types of EMG, each suited to different research needs. Surface EMG (sEMG) uses small sensors placed on the skin to detect activity from nearby muscles and is the most common approach in behavioral and human performance studies. Intramuscular EMG involves inserting a fine-needle electrode directly into a muscle to record activity from specific muscle fibers, often used in clinical or specialized research settings. Facial EMG (fEMG), a form of surface EMG, focuses on facial muscles. By measuring muscle activity associated with smiling or frowning, fEMG allows researchers to study emotional responses, even when those responses are subtle or not consciously expressed.

One of the key strengths of EMG is its ease of integration with other physiological measurements. In many studies, EMG is recorded alongside electrocardiography (ECG), which measures heart activity; electroencephalography (EEG), which records electrical activity in the brain; functional near-infrared spectroscopy (fNIRS), which tracks changes in brain oxygenation; and eye tracking, which monitors visual attention and gaze patterns. By synchronizing these signals in time, researchers can better understand how different systems in the body work together. For example, combining EMG with EEG can reveal how brain activity leads to muscle movement, while pairing EMG with ECG can show how physical effort relates to heart responses during stress or exercise. This multimodal approach is central to advancing research in areas such as emotion, cognition, and human performance.

EMG also has important real-world applications. In rehabilitation, it helps clinicians monitor muscle recovery after injury. In ergonomics, it provides objective data about muscle strain in the workplace. In sports science, EMG helps optimize training and performance by identifying how and when muscles are activated. Increasingly, EMG is also used in human–machine interfaces, such as systems that allow people to control prosthetic limbs using their muscle signals. Its ability to detect fine-grained changes in muscle activity makes EMG a valuable tool across both research and applied settings.

Best practices for EMG data quality begin with careful electrode placement and attention to potential sources of noise. For sEMG and fEMG, electrodes should be placed over the “belly” of the target muscle, aligned with the muscle fibers, and spaced consistently to capture clean, interpretable signals. Gently cleaning the skin and, when appropriate, lightly abrading the surface helps reduce impedance and improve signal quality. In fEMG studies, precise and repeatable placement over well-defined facial muscles is critical, as these muscles are small and closely spaced. To minimize noise and artifacts, researchers should secure electrodes and cables to prevent movement, ask participants to limit unnecessary body motion, and ensure proper grounding of the recording system. Electrical interference from nearby equipment, power lines, or poor cable management can also contaminate EMG signals, so shielded cables and a controlled recording environment are recommended. Finally, synchronizing EMG with other physiological signals using a common acquisition system helps prevent timing errors and reduces the need for later corrections, resulting in cleaner data and more reliable conclusions.

Recent studies demonstrate how EMG continues to expand into new and innovative areas. In a study published in Results in Engineering, a team of researchers from China developed a low-computational method for recognizing hand gestures from EMG signals to improve prosthetic device control. The researchers extracted key features from EMG recordings and used a lightweight machine-learning model, a multilayer perceptron (MLP), to classify gestures in real time. EMG data were collected using a four-channel BIOPAC data acquisition system running Biopac Student Lab (BSL) software. Surface Ag/AgCl electrodes were placed on four forearm muscles to capture relevant muscular activity. The study showed that accurate gesture recognition can be achieved without heavy computational requirements, making the system more practical for everyday use. This work highlights how EMG can support the development of more responsive, accessible assistive technologies.

Another study, conducted by a team of researchers from Mahidol University in Thailand and presented in the Institute of Electrical and Electronics Engineers (IEEE) proceedings, explored how combining EMG with motion sensors can improve ergonomic assessments. Focusing on occupational health, the study integrated surface EMG with data from an inertial measurement unit (IMU), a sensor that tracks movement and orientation. The researchers used the IMU to calculate Rapid Upper Limb Assessment (RULA) scores—a common method for evaluating postural risk—while EMG data collected via a BIOPAC four-channel research system provided insight into muscle activity. By combining these measures, the team found that posture alone did not always reflect actual muscle strain. The inclusion of EMG revealed additional muscle stress that might otherwise go unnoticed, suggesting that multimodal approaches can lead to more accurate workplace assessments and better injury-prevention strategies.

Researchers from Louisiana State University and the Pennington Biomedical Research Center in Baton Rouge, Louisiana, examined how training experience influences muscle activation and fatigue during resistance exercise performed with and without blood flow restriction (BFR) in young men. The study, published in Physiological Reports, compared trained and untrained participants while they completed knee extension exercises under low-, medium-, and high-load conditions. The team used sEMG to measure muscle excitation and total muscle activation in the vastus lateralis, with participants fitted with a portable BIOPAC BioNomadix Wireless EMG system. EMG signals were sampled at 2000 Hz and analyzed using a data acquisition system with AcqKnowledge software, allowing the researchers to quantify both peak muscle excitation and overall activation across repetitions. The results showed that low-load exercise with blood flow restriction produced lower peak muscle excitation but substantially greater total muscle activation compared to traditional high-load exercise, regardless of training status. These findings suggest that low-load BFR training may provide an effective alternative for stimulating muscle adaptations while reducing mechanical stress, with potential applications in rehabilitation and strength training programs.

Taken together, these examples illustrate the versatility and effectiveness of EMG in neuroscience, psychophysiological research, and beyond. Whether used to study emotion, improve physical training and workplace safety, or develop assistive technologies, EMG provides a direct link between muscle activity and human behavior. When combined with other physiological measures, it offers a more comprehensive understanding of how the brain and body interact. As research tools and techniques continue to advance, EMG will remain an essential method for exploring brain-body connections. For additional information on how to design studies around EMG, best practices for gathering EMG data, and how to integrate EMG with other signals, check out our webinar on EMG acquisition and analysis.

If EMG will be part of your next physiological or psychophysiological research project, reach out to our knowledgeable staff, who are standing by to help you with each stage of the planning and design process.

Virtual Phobia: How VR is Transforming Anxiety and Fear Research

“Do the thing you fear and the death of fear is certain.”

These words by American poet and philosopher Ralph Waldo Emerson assert a head-on approach to overcoming life’s anxieties and phobias. It’s a strategy backed by the latest research methodology, which, thanks to technology, can leverage the relative safety of virtual environments to study how participants react to and manage anxiety.

Anxiety disorders are among the most prevalent mental health conditions and are often maintained through avoidance of fear‑provoking situations. A cornerstone of evidence‑based treatment is exposure therapy, in which individuals gradually and safely confront feared experiences to reduce anxiety over time. In recent decades, virtual reality (VR) has emerged as an effective way to deliver exposure therapy and to study anxiety under controlled conditions. Virtual reality exposure therapy (VRET) uses immersive, computer‑generated environments to recreate anxiety‑triggering situations, such as public speaking, social interaction, or medical procedures, while allowing researchers and clinicians to control intensity, pacing, and repetition.

Research shows that VRET can be as effective as traditional, real‑world exposure for many anxiety‑related conditions, including specific phobias, social anxiety, panic disorder, and symptoms of post‑traumatic stress disorder (PTSD). One of VR’s key advantages is its balance between realism and experimental control. Environments can be standardized across participants, exposure levels can be adjusted in small steps, and scenarios can be repeated across sessions without the logistical challenges of invivo exposure. At the same time, well‑designed VR experiences reliably evoke emotional and stress responses, making them valuable for both treatment and research.

The scientific impact of VR is amplified when immersive environments are combined with multimodal psychophysiological measurements—such as electrocardiography (ECG), electroencephalography (EEG), functional near‑infrared spectroscopy (fNIRS), respiration, electrodermal activity (EDA), and eye tracking. In multimodal studies, researchers gain a deeper, objective understanding of how the brain and body respond to emotional challenges. By synchronizing VR events with physiological data, researchers can observe how the body responds moment by moment as fear is triggered, maintained, and eventually reduced.

Researchers at the University of Cyprus investigated whether a single session of VR exposure could meaningfully reduce public speaking anxiety in university students. Participants were placed in a virtual auditorium and asked to give a speech in front of realistic virtual audiences. The researchers could adjust audience size and behavior, allowing them to gradually increase the social challenge while maintaining full experimental control. To capture objective stress responses, heart activity was recorded using a Lead I electrocardiogram configuration, with two disposable silver/silver‑chloride electrodes placed on the forearms. Signals were amplified with a BIOPAC ECG100C bio‑amplifier, acquired using a MP data acquisition system with AcqKnowledge software for recording and analysis. This setup enabled precise measurement of heart rate and heart rate variability (HRV) throughout the task. The virtual environment was created using the Vizard Virtual Reality Toolkit, which was integrated with the BIOPAC system so that physiological data could be synchronized with key moments in the VR experience, such as the start of the speech. Results showed significant reductions in both self‑reported anxiety and physiological arousal following a single VR exposure session, demonstrating how VR and physiological monitoring can be combined to assess rapid emotional change.

Researchers at the University of Macau examined how social rewards and emotional cues influence anxiety during interpersonal interaction. Participants engaged in a virtual reality social interaction game designed to mimic real social exchanges while allowing researchers to control feedback and outcomes. During the task, heart activity was recorded using ECG with an MP data acquisition system. By synchronizing physiological data with events in the virtual environment, the research team could examine how anxiety‑related responses evolved as social interactions unfolded. The findings suggested that anxiety responses were more strongly related to sensitivity to others’ emotional cues than to reward outcomes themselves. This study highlights how immersive VR combined with synchronized physiological recording can provide insight into the subtle emotional dynamics of social anxiety, processes that are difficult to capture using self‑report measures alone.

In a multi‑institutional effort led by researchers at the University of Toledo, researchers developed a study protocol to better understand how dental fear develops and how early exposure might help prevent it. The study uses a virtual reality dental clinic to expose participants to dental‑related sights and sounds across multiple sessions and contexts. The virtual environment was programmed using Vizard software, and participants interacted with it using an HTC Vive Pro headset and handheld controllers, allowing natural movement and exploration. Skin conductance responses (SCR) were recorded using a BIOPAC MP system paired with a wireless BioNomadix EDA transmitter, enabling participants to move freely while skin conductance and other signals are collected. This wireless, immersive setup is especially well suited for fear‑learning research, where comfort and natural movement are critical. Although the publication focuses on study design rather than completed outcomes, it demonstrates how VR combined with physiological monitoring can support translational research aimed at understanding and preventing the development of fears and anxiety.

These studies show how VR and synchronized physiological measurement are expanding the study of anxiety, stress, and fear. VR provides immersive, repeatable experiences that reflect real‑world challenges, while physiological signals reveal how the body responds beneath conscious awareness. For additional information on how to integrate VR into multimodal research, visit our Webinar page for instructive trainings on this topic and others.

If you are planning to integrate VR into your next multimodal study, reach out to our skilled sales staff who can assist you through each step of the process.

Hands-on Learning: How Real‑Time Physiological Data Deepens Clinical Education

Physicist Albert Einstein noted, “The only source of knowledge is experience.” This principle is particularly relevant in healthcare education, where hands-on learning is vital for cultivating the skills needed to care for patients effectively. The practice of recording and analyzing physiological signals in the learning lab serves as a powerful teaching tool, enabling students to immerse themselves in real-world scenarios and reveal autonomic responses, cardiovascular patterns, and emotional states that are often hidden from view.

For students in nursing, dentistry, and pharmacology, engaging with these signals transforms abstract concepts into concrete, measurable experiences. By analyzing heart activity, visual attention, stress markers, and pharmacodynamic effects, students not only enhance their critical thinking skills but also prepare themselves for clinical challenges with greater confidence.

Physiological signals across the health sciences teach learners to interpret subtle features embedded in physiological waveforms. Modern teaching laboratories increasingly incorporate multimodal systems to help students better understand the complexity of human physiology.

Nursing programs emphasize accurate patient monitoring and interpretation of vital signs, including electrocardiograms (ECG) and heartrate variability (HRV). A 2025 study published in Sensors evaluated the validity of Apple Watch Series 6 HRV data against laboratory‑grade ECG recordings using a BIOPAC 3‑lead ECG system to provide a comparative baseline for measurement. By synchronizing event markers between the Apple Watch and BIOPAC timeline, researchers ensured precise temporal alignment for comparing R‑R intervals and HRV indices. The results showed near-perfect agreement in R-R interval timing under resting conditions, indicating that such wearable devices can serve as a reasonable tool for certain wellness-oriented assessments. At the same time, the BIOPAC system remains the gold standard for precise physiological analysis.

For nursing students, this study demonstrated that consumer wearables must be validated against clinical-grade systems before being relied upon for assessment or decision-making. By examining the comparative data, students can explore how artifacts, sampling frequencies, and sensor placement influence the fidelity of HRV measurements. Moreover, because HRV relates directly to autonomic balance and stress physiology, the study provides a meaningful touchpoint for nursing courses in pathophysiology and patient assessment. Through hands‑on lab sessions using BIOPAC ECG amplifiers, students can visualize waveform morphology, measure beat‑to‑beat variability, and learn how cardiovascular signals reflect underlying homeostatic regulation.

Dental students should understand not only the mechanics of clinical procedures but also the emotional and perceptual experiences of their patients, especially children. A 2025 cross-sectional pilot study in the European Archives of Paediatric Dentistry used an eye tracking and data acquisition and analysis system from BIOPAC to measure children’s gaze behavior and physiological stress when viewing images of dentists, dental chairs, and operatory designs.

Using eye-tracking metrics such as mean dwell time, fixation count, time to first fixation, and total fixation time, researchers found that study participants stared longer at dentists wearing white coats, indicating a perception of compitance and safety, but also indimidation. In addition, gender matching mattered, as children showed longer fixation on dentists of the same gender. The study also found that warm‑colored dental chairs (especially yellow) attracted greater visual attention, particularly among younger children. Simultaneously, HRV and ECG signals recorded with the BIOPAC system revealed that younger children exhibited greater autonomic arousal than older peers when exposed to dental images.

These findings offer dental students actionable insights into clinic design, caregiver attire, and emotional perception, all of which influence pediatric patient comfort. The study demonstrates how combining eye tracking with physiological monitoring can reveal otherwise hidden psychological responses. For dental educators, integrating such physiological signal analysis into coursework helps students develop empathetic, patient‑centered care strategies.

In pharmacology courses, students learn how drugs influence physiological systems. A study published in Brain Sciences investigated the lingering cardiovascular effects of caffeine, challenging the assumption that its effects dissipate within six hours. Using BIOPAC respiratory transducers, noninvasive blood pressure modules, bioimpedance amplifiers, and ECG amplifiers connected to a data acquisition and analysis system researchers monitored participants before and after consumption of caffeinated and decaffeinated coffee. Results showed measurable changes in heart rate, respiratory patterns, and thoracic impedance well beyond the expected metabolic window, suggesting caffeine’s physiological effects outlast its pharmacokinetic half‑life.

For pharmacy students, these findings reinforce critical distinctions between pharmacokinetics (drug metabolism) and pharmacodynamics (physiological response). By analyzing real‑world signal data, learners gain a more nuanced understanding of how stimulants affect autonomic regulation. Such insights prepare future pharmacists to counsel patients on medication timing, drug interactions, and individual responses to common agents such as caffeine.

Across nursing, dentistry, and pharmacy, physiological signals provide potent educational value. They bridge the gap between theory and clinical application by giving students concrete, measurable access to physiological processes such as autonomic reactivity, cardiovascular regulation, and perceptual attention. Using both research and education-based lab systems, learners can visualize real-time physiological data, develop analytical skills, and cultivate a deeper understanding of the human body under stress, stimulation, and clinical observation.

As healthcare grows more data‑driven, integrating hands-on experience with signal acquisition into professional training helps future clinicians interpret complex physiological information with confidence. Whether validating wearable devices, improving pediatric patient experiences, or exploring drug‑induced autonomic effects, physiological signals empower students to connect scientific principles with evidence‑based, care. Check out our webinar, Advancing Practical Learning: Biosignal Essentials, to learn more.

If you’re exploring ways to incorporate physiological signals into your curriculum or simulation lab, our team is ready to help identify the best tools and workflows for your program.

Tick, Tock: Pulse Transit Time Offers Noninvasive Physiological Insights

A split second can reveal much about the cardiovascular system and the other physiological systems it influences. Pulse Transit Time (PTT) captures one of those critical moments, the brief interval it takes for the pressure wave generated by contraction of the left ventricle to travel from the heart to a peripheral site in the body. That tiny stretch of time tells us something important about the arteries—namely, how stiff or flexible they are in that moment. When blood pressure rises and the vessel walls tighten, the pulse wave travels more quickly, so PTT gets shorter. When the vessels are relaxed and more elastic, the wave slows down, and PTT becomes longer. Because of this back-and-forth relationship, PTT gives researchers a simple, noninvasive way to track changes in vascular tone, blood flow dynamics, and autonomic nervous system activity.

PTT is determined by measuring the volume or pressure pulse at a proximal artery (such as the carotid or brachial) and at a distal artery (such as the finger or toe). To prevent confusion in PTT nomenclature across different methods, some researchers use labels formed from the first one or two letters of the starting and arrival signals. PTT-PP refers to PTT recorded using PPG between a proximal and a distal artery, PTT-EP refers to PTT measured between electrocardiogram (ECG) proximally and photoplethysmogram (PPG) distally and PTT-IP refers to PTT recorded between Impedance Cardiogram proximally and PPG distally.

PTT-EP is recorded by simultaneously recording ECG and PPG. PPG is usually recorded at the finger using a small infrared light to detect changes in blood flow with each heartbeat. As blood pulses into the area, the amount of light absorbed changes, creating a waveform with a clear rise and peak. To calculate PTT-EP, researchers measure the time between the ECG spike and a specific point on the PPG wave, typically the point at which the wave first rises or reaches its peak. Strictly speaking PTT-EP is not a true PTT as it includes pre-ejection period, a short delay between electrical activation of the ventricles and actual ejection of blood. For that reason, it is sometimes referred to as Pulse Arrival Time (PAT). Even so, the ECG-to-PPG approach remains widely used because it is noninvasive, reliable, relatively inexpensive, and straightforward to implement across a range of study designs.

Typical lab configurations focus on integrated, multimodal data acquisition systems that allow researchers to record ECG and PPG signals simultaneously using dedicated amplifier modules, with analysis performed via software. These systems enable precise channel synchronization, automated waveform feature detection, beat-by-beat PTT computation, and data export for statistical analysis. In some studies, researchers also integrate noninvasive blood pressure (NIBP) modules to directly examine the relationship between PTT and systolic or mean arterial pressure, strengthening the interpretation of vascular changes.

Obtaining high-quality PTT data requires attention to detail and careful planning. Participants should rest in a quiet, temperature-controlled room, since vascular tone can be affected by stress, ambient temperature, and sympathetic activation. Avoid testing immediately after meals or the consumption of caffeine or nicotine, which can alter cardiovascular dynamics. Proper sensor placement and stable contact pressure are critical for minimizing motion artifacts and waveform distortion. Consistent measurement timing, accounting for diurnal variation, helps ensure consistent data quality across sessions. Signal processing choices also matter. Careful filtering (see example study below), accurate event marking, and careful peak or foot detection are essential to ensure that the measured interval truly reflects physiological timing rather than processing artifacts.

When these best practices are followed, PTT becomes a versatile research tool. It has been used to study stress reactivity, autonomic regulation, arterial stiffness, posture-related hemodynamics, exercise physiology, sleep physiology, and the development of cuffless blood pressure estimation technologies. Recent studies illustrate both the promise and the practical considerations of PTT measurement.

At the Georgia Institute of Technology, researchers explored whether noninvasive nerve stimulation applied at the ear, neck, or wrist could reduce acute stress responses in healthy young adults. During laboratory sessions that included mental arithmetic and cold exposure tasks, cardiovascular signals were recorded using a BIOPAC MP data acquisition unit and a PPG100C to capture ECG and fingertip PPG. PTT served as a key marker of sympathetic (“fight-or-flight”) activation. The research team found that stimulation at the ear and wrist significantly reduced stress-related cardiovascular changes compared to a sham condition, supporting the potential for wearable systems that integrate neuromodulation and real-time cardiovascular monitoring.

In another study published in Nature, researchers at Columbia University tackled a common problem in cuffless blood pressure monitoring: when wearable sensors sit above or below heart level, changes in arm position create hydrostatic pressure errors that skew estimates based on PTT. Cuffless systems frequently use PTT to estimate blood pressure, but arm movements can distort that timing and reduce accuracy. To investigate this, the team collected synchronized physiological data using a BIOPAC data acquisition system to record high-resolution ECG signals via a BIOPAC ECG amplifier and fingertip PPG signals via BIOPAC PPG100C, while a BIOPAC NIBP module measured reference blood pressure using upper-arm and finger cuffs. Participants also wore wrist and upper-arm inertial sensors (IMUs) to track how the arm was positioned relative to the heart. The research team then developed a method called IMU-Track, which uses motion data and deep learning to correct PTT for arm height effects, improving the accuracy of blood pressure predictions across different postures. Their findings showed that accounting for sensor position dramatically reduced errors in cuffless blood pressure estimation, suggesting that combining motion tracking with PTT measurements could make wearable BP monitoring more reliable in everyday use.

When applied correctly, PTT provides a potent, noninvasive tool for assessing cardiovascular function—one measured in milliseconds but capable of revealing meaningful physiological change. For more information on integrating PTT into research, see our PTT webinar.

If you are planning to use PTT in your next study, don’t hesitate to reach out for our highly capable team of experts for assistance in identifying the equipment and procedures to ensure your success.

TREV Q&A: Unpacking Trans-radial Electrical Bioimpedance Velocimetry

As researchers look for cleaner, more direct ways to capture sympathetic nervous system (SNS) activity, Trans-radial Electrical Bioimpedance Velocimetry (TREV) has emerged as a powerful new approach for measuring beat-by-beat changes in cardiac contractility to index sympathetic drive. To explain how the technique works and where it fits alongside more established measures, we sat down with Viktoriya Babenko, PhD, BIOPAC’s in-house TREV expert and research specialist. Babenko helps researchers implement advanced cardiovascular and autonomic measurements, combining her extensive hands-on experience with bioimpedance technologies and a strong grounding in the interpretation of physiological signals. In the Q&A below, she describes the physiological principles behind TREV, how it differs from traditional electrodermal activity (EDA), electrocardiogram (ECG), and impedance cardiography (ICG) approaches, and why it offers a uniquely direct and practical window into sympathetic drive for both laboratory and neuroimaging research.

At a high level, what is Trans-radial Electrical Bioimpedance Velocimetry (TREV), and what does it measure?

TREV is a noninvasive method for estimating cardiac contractility as a continuous, beat-by-beat index of SNS activity. Rather than measuring bioimpedance across the chest like traditional ICG, TREV measures impedance changes across the radial and ulnar arteries of the forearm.

As the heart contracts, it generates a pressure wave that travels through the arterial system and causes red blood cells to momentarily align. This alignment reduces electrical resistance in the blood, which TREV continuously tracks. The impedance signal measured by TREV provides velocity, acceleration, and ultimately a contractility index, where stronger contractions reflect greater sympathetic drive.

Why is cardiac contractility such a useful index of SNS activity?

Cardiac contractility reflects the vigor with which the heart contracts during each heartbeat and is strongly modulated by sympathetic tone, either through direct neural innervation or circulating catecholamines like epinephrine. Increased sympathetic activation leads to stronger, faster contractions, while reduced sympathetic drive results in weaker contractile force.

Because of this close physiological relationship, contractility is considered one of the most direct and objective noninvasive measures of SNS activity. Unlike heart rate alone, which reflects both sympathetic and parasympathetic influences, contractility provides a more targeted window into sympathetic drive specifically.

How does TREV differ from traditional ICG- or ECG-based approaches?

Traditional approaches for indexing sympathetic drive, such as combining ECG and thoracic ICG to extract the pre-ejection period (PEP), are powerful but complex. They typically require 10 electrodes placed across the neck, chest, and torso, along with careful preprocessing and time-based feature extraction between both ICG and ECG to get PEP.

TREV dramatically simplifies this process by using just four strip electrodes placed on the forearm. The resulting contractility waveform produces a single sharp peak per heartbeat, where the amplitude directly reflects contractile strength. Analysis is as simple as extracting peak amplitudes, rather than identifying precise timing relationships across ECG and ICG signals, making TREV faster to set up and easier to analyze.

What is the physiological rationale for using the forearm and radial and ulnar arteries as the measurement site?

The radial and ulnar arteries provide a relatively simple and accessible vascular model that is well-suited for bioimpedance measurements. When the heart contracts, a pressure wave propagates rapidly through the arterial tree and reaches the forearm, aligning red blood cells even before bulk blood flow arrives.

This pressure-wave-driven alignment is sufficient to cause measurable drops in impedance, allowing TREV to estimate cardiovascular dynamics without the anatomical and physiological complexity of the thorax. Measuring at the forearm also reduces sensitivity to respiratory and pulmonary effects that complicate thoracic impedance measurements.

What cardiovascular or hemodynamic parameters can be derived from TREV?

TREV provides estimates of blood velocity, acceleration, and the integral of velocity (blood position) derived from the impedance waveform. Most importantly, the second derivative of the impedance signal yields a contractility index (blood flow “jerk”) that reflects sympathetic modulation of the heart on a beat-by-beat basis.

While multiple parameters are available, BIOPAC primarily recommends TREV as a tool for tracking cardiac contractility over time, particularly in studies interested in stress, arousal, motivation, and cognitive or emotional processes linked to sympathetic activation.

What does a typical TREV measurement session look like, from setup to data output?

Once the arm is clean and dry, four hydrogel strip electrodes (EL526) are placed on the forearm and connected via the CBL246 adapter to the NICO100D system. I recommend watching the TREV Webinar titled “A Simple Next-Gen Method for Stress Research: TREV” for step-by-step guidance on electrode placement.

During data collection, the participant’s arm must remain fully supported and relaxed, ideally with the elbow and forearm stabilized through the wrist to minimize muscle activity. When collected under proper conditions, TREV produces a clean, continuous contractility waveform with one peak per heartbeat, allowing for straightforward beat-by-beat analysis of sympathetic drive.

What advantages does TREV offer compared to ECG, EDA, or other stress-related measures?

Many commonly used physiological signals, such as heart rate, blood pressure, or heart rate variability, are influenced by multiple factors, including hydration, temperature, respiration, and both branches of the autonomic nervous system (parasympathetic and sympathetic nervous systems). EDA provides a sympathetic index, but it is relatively slow, delayed, and indirect, reflecting eccrine sweat gland activity modulated by the SNS rather than cardiovascular dynamics.

TREV fills an important gap by offering a fast, dynamic, and more direct measure of sympathetic drive through cardiac contractility. It combines the physiological specificity of ICG-derived measures with a much simpler setup and analysis pipeline, making it especially attractive for experimental and applied research settings

What are the main challenges in acquiring clean, interpretable TREV data?

The primary challenge with TREV is its sensitivity to motion artifact. Muscle activity in the forearm generates electromyography (EMG) signals that are much larger than the impedance changes of interest and can easily overwhelm the TREV signal.

For this reason, careful experimental control is essential. The participant’s arm should be fully supported, relaxed, and free from movement or strain, while other body movements are generally permissible. When these conditions are met, TREV data quality is excellent, but the method does demand attention to posture and comfort.

In what research or applied settings is TREV showing the most promise?

TREV is particularly well-suited for research at the intersection of stress, cognition, emotion, and autonomic physiology. It has been successfully used in laboratory studies examining sympathetic responses to cognitive and emotional stressors, as well as in MRI environments to enable the simultaneous study of neural activity and SNS dynamics.

Across both standard laboratory settings and neuroimaging environments, TREV provides a continuous, beat-by-beat index of sympathetic activity, making it especially valuable for event-related experimental designs where precise timing and dynamic changes in autonomic responses are of interest. In the MRI specifically, this temporal resolution allows researchers to directly link moment-to-moment fluctuations in sympathetic drive with neural processes measured using functional MRI (fMRI), offering a powerful framework for studying how brain activity and cardiovascular sympathetic responses interact during task performance, affective processing, or stress-related appraisals. As with most MRI-based physiological measurements, specific hardware configurations and safety considerations apply, and researchers should contact the BIOPAC support team before data collection to ensure proper setup and compliance.

How does TREV perform in dynamic or real-world conditions, such as movement or exercise?

At present, TREV performs best in controlled conditions where the forearm can remain fully supported and at rest. Simple movements while seated may be permissible, provided that the arm containing the TREV electrodes remains immobile and relaxed. Due to its sensitivity to motion, TREV is not currently recommended for continuous data collection during active movement or exercise.

That said, TREV can still be extremely valuable in movement- or exercise-related research by comparing pre- and post-task states. This approach allows researchers to quantify sympathetic changes associated with physical or psychological challenges without collecting data during movement itself.

Looking ahead, how do you see the TREV method evolving over the next five to ten years?

As validation studies continue and more researchers adopt the method, TREV is likely to become a standard tool for indexing sympathetic drive in both basic and applied research. Ongoing work, including peer-reviewed publications, will further refine interpretation, best practices, and experimental design considerations.

In the longer term, improvements in signal processing, hardware integration, and multimodal data collection may expand TREV’s use into more naturalistic settings, helping bridge the gap between controlled laboratory studies and real-world physiological monitoring.

If you are planning a study and would like to learn more about integrating TREV, our team of experts can help guide you to the right equipment and strategies.

2025: The Year in Review

As 2025 winds to a close, there is much to celebrate both here at BIOPAC and in the ever-expanding frontiers of research that our products engage with every day. Let’s take a quick look at where we have been over the past 12 months and what the future holds.

Popular Posts

Speaking of engagement, this is the time of year when we do a bit of self-assessment and revisit what topics our readers were most inspired by and most interested in. Apparently, many of our readers are closet gamers at heart, because our blog on research on game design and gaming impacts drove more eyes to our site than any other topic this year, followed by posts on cognitive neuroscience and aging and the human impact of isolation.

New Products and Updates

On the heels of the 2024 release of our flagship MP200 data acquisition and analysis system and a significant upgrade to AcqKnowledge software, 2025 concludes with another milestone: the imminent release of AcqKnowledge 6.0.2. This latest version features a host of improvements and additions, including full integration of MedelOpt+, which blends whole-head functional near-infrared spectroscopy (fNIRS) with electroencephalography (EEG) in a single, highly flexible device.

BIOPAC in the Lab

Every year, BIOPAC products continue to drive the most exciting research in physiology, psychology, and neurology, and 2025 was no different. Each month, we highlight breakthrough studies in which BIOPAC played a role in gathering and analyzing key data. These are usually centered around a theme and feature research published in the last few years. To close out the year, we like to spotlight a couple of significant studies from 2025 that didn’t get mentioned.

A collaborative study by researchers from the University of Georgia and Beijing Normal University examined how mothers and children coordinate their physiological responses during stressful interactions. Using BIOPAC data acquisition systems coupled with wireless ECG transmitters, the team simultaneously recorded cardiac activity from each participant pair as they completed structured challenge tasks. This setup provided the temporal precision needed to track changes in heart rate and moment-to-moment autonomic synchrony, revealing how caregivers and children influence one another biologically during shared stress. The study found that greater synchrony was linked to both emotional dynamics and regulatory behaviors during the tasks, highlighting the deep coupling between social relationships and physiological responses. The wireless BIOPAC configuration enabled naturalistic interaction while capturing high-quality dyadic data, a persistent challenge in synchrony research.

In its first full year of availability, the MP200 is already making waves in the research community. At Guangdong University of Science and Technology in China, researchers examined how head-shoulder posture and cervical muscle activation differ between college students with chronic neck pain (CNP) and healthy individuals. The team employed surface electromyography (sEMG) recorded with a BIOPAC MP200 data acquisition system and AcqKnowledge software. Researchers placed surface electrodes over targeted neck muscles to record raw EMG signals during various strength tests and physical tasks. Students with CNP demonstrated significantly poorer head and shoulder alignment, reduced neck extensor strength, and altered EMG activity, indicating neuromuscular dysfunction associated with pain. Findings showed the connection between altered posture and impaired muscle function in chronic neck pain. The study demonstrates the effectiveness of surface EMG to support clinical diagnosis and rehabilitation.

For more inspiration as we head into 2026, explore our webinar library for tips, tricks, and methods directly from experts across a range of research fields.

If you are planning to launch a study for 2026, now is the time to reach out to your nearest BIOPAC customer service representative for help finding the right tools to get started.

Healing Hands: EDA and Affective Touch

“Nothing eases suffering like human touch.” — Bobby Fischer

The gentle caress of a mother to her child. A reassuring pat on the shoulder from a friend. The touch of another human is one of the first forms of communication we experience in life, preceding the development of spoken language. Touch can have a remarkable effect on our emotional, psychological, and physiological states. It shapes our relationships with others and helps us build social connections.

The positive effects of touch are primarily associated with affective touch, characterized by comforting, caress-like stroking that activates C-tactile afferent (CT-afferent) neurons in the skin of mammals (including humans). Affective touch has attracted the interest of researchers seeking to decode how the sympathetic nervous system confronts and manages a variety of challenges, including pain regulation, stress management, and social interactions. The subject has drawn attention in the study of neurodevelopmental disorders, such as Autism Spectrum Disorders (ASD), where it is playing an essential role in understanding the sensory and social challenges facing individuals with atypical neurocognitive function.

While studies on touch, and affective touch specifically, utilize a range of physiological signals to gather data, electrodermal activity (EDA) has proven particularly useful in this area. Also referred to as Galvanic Skin Response (GSR), EDA provides a direct window into the sympathetic nervous system, which is responsible for emotional or affect-related arousal. When someone experiences pleasant or meaningful touch (e.g., a gentle stroke or supportive hand), the brain triggers subtle changes in sweat gland activity manifested as shifts in skin conductance. These changes occur when people aren’t fully aware of their emotional response. This makes EDA a sensitive, objective marker of how the body reacts to social and tactile experiences. In studies of affective touch, researchers track EDA to see whether a touch feels calming, engaging, or stressful, and how these responses differ across individuals or clinical groups such as autistic youth. Because EDA reflects genuine physiological arousal tied to emotional processing, it helps scientists understand the underlying autonomic mechanisms that shape how we experience social touch.

Researchers at the University of Tours in France examined how children with ASD respond to gentle, affective touch to determine whether they exhibit physiological patterns that differ from those of their neurotypical peers under the same conditions. The team measured multiple aspects of the autonomic nervous system, including EDA and electrocardiogram (ECG). These signals were collected using a BIOPAC MP36 data acquisition and analysis system to capture subtle changes in sympathetic arousal. Researchers collected EDA data using two 8 mm Ag/AgCl cup electrodes placed on the second phalanges of the index and middle fingers of the right hand. ECG was collected via two disposable vinyl electrodes placed on the sternum and on the right shoulder. The study found that autistic children exhibited atypical EDA responses, showing either blunted or inconsistent autonomic reactions relative to controls, even when their outward behavior appeared typical. These results suggest that affective touch may not regulate internal arousal in autistic children the same way it does in others, providing an essential insight for therapies and sensory-based interventions that rely on touch.

In a similar study, a team from the University of Turin in Italy explored how autistic adults process affective touch by comparing their subjective ratings of pleasantness with their physiological responses. The researchers used a BIOPAC data acquisition research system with an EDA amplifier module to record EDA. At the same time, participants received gentle, slow stroking intended to activate the brain’s affective touch pathways. The goal was to determine whether autistic adults show a mismatch between what they say they feel and how their bodies respond. The findings revealed an apparent dissociation. While autistic participants often rated the touch similarly to neurotypical participants, their EDA responses differed significantly, indicating altered sympathetic arousal. This physiological-subjective mismatch provides compelling evidence that affective touch is processed differently in ASD, which may help explain challenges with social touch and sensory integration in everyday interactions.

Researchers from the University of Liverpool and Manchester Metropolitan University examined how brief, naturalistic social touch alters brain activity, autonomic physiology, and emotion recognition performance. Although this multimodal study did not focus on an autism-only sample, it is relevant to social-touch research more broadly and provides methodological examples that apply to ASD studies. To capture changes in prefrontal cortex function, the team employed a BIOPAC fNIRS imager system, with signals sent to a data acquisition unit. Further analysis of fNIRS signals was handled via fNIRS visualization software. Both EDA and photoplethysmography (PPG) were recorded at 2 kHz, using shielded Ag/AgCl electrodes on the index and fourth fingers and a PPG sensor on the middle finger, and were acquired and analyzed in AcqKnowledge. The results showed that social touch increased prefrontal activation, modulated cardiac and vascular dynamics captured via PPG, and produced measurable changes in sympathetic arousal, as indexed by EDA. Participants also demonstrated improved emotion-recognition accuracy following touch. Together, these findings suggest that social touch engages coordinated central and peripheral systems in ways that may support social cognition and emotional understanding.

These are just a few examples of how EDA is being used in research into affective touch. For additional information on integrating EDA in your study, see our multiple webinars on the subject.

Are you designing a study into affective touch or just planning a research project that will focus on EDA? Our customer service staff can help you streamline the process to produce best possible data.