Life Science Hardware and Software

Ensemble analysis averages raw waveform signals through lining up their peaks, allowing researchers to mitigate noise or potential outside artifacts. Researchers Cieslak et al. (2017) from University of California, Santa Barbara, identified and assessed a new open source tool that conducts ensemble analysis of cardiovascular data. The moving ensemble analysis pipeline (MEAP) builds on classic collection and analysis tools; not only in detecting cardiovascular state during an experiment, but also in measuring how cardiovascular cycles change overtime.
Cardiovascular measurements are typically averaged to reduce noise, but traditional measurement methods made capturing changes in cardiovascular cycles restricted to a select window of time. This makes it difficult to assess fast changes with traditional cardiovascular ICG data. With MEAP, variability is better analyzed, allowing it to become a more accurate dimension of assessment.
In assessing MEAP’s viability, researchers measured two participants as they completed four different tasks. The experiment began and ended with a random dot kinetogram task allowing for a baseline control of cardiovascular activity. This was followed by the “cold presser” and “Valsalva,” two tasks that were expected to induce strong physiological reactions. Another task included a video game, seen as having less predictive effects.
Two subjects were measured for ECG and other physiological signals as they completed the four physical and cognitive tasks. BIOPAC’s research solutions included ECG100C utilized for ECG, NICO100C-MRI to collect ICG signals, and NIBP100D CNAP Monitor 500 to record blood pressure. Data was gathered and measured with MP Research System with AcqKnowledge software.
The results pointed to changes typical cardiovascular measures wouldn’t be able to describe. This was seen during the Valsalva maneuver, where rapid baroflex changes occurred. It was also found cardiovascular data varied immensely while performing repetitive tasks.
The paper recognizes MEAP’s potential for rapidly advancing findings that use cardiovascular data. The authors point to this tool’s potential ability for exploring new areas of study that have been difficult to quantify in the past, such as linking cardiovascular reactivity to motivation. In acknowledging the benefits of MEAP, the authors stress the importance of not overstepping smaller aspects of acquisition, such as poorly attached electrodes or imbalanced experiment design. Overall, this paper recognizes, analyzes, and validates this exciting new development in the field of cardiovascular research.

Behavioral inhibition (BI) has proven to be a fundamental risk factor in childhood anxiety psychopathology, arguably the most crucial factor in the development of anxiety. BI is defined as the increased arousal in response to novel stimuli, shyness, and withdrawal even in high-reward situations. The strength of this association varies based on respiratory sinus arrhythmia (RSA) regulation, yet little is known about this function in children with anxiety disorders.

RSA is characterized as the rhythmic fluctuations in heart rate associated with the respiratory cycle regulated by the parasympathetic nervous system. In a “basal,” or low-threat situation, RSA slows down the heart to maintain baseline levels. In a “challenge,” or high-threat situation, RSA is suppressed, which results in an increased heart rate and a fight-or-flight response. Thus, a greater control of the parasympathetic nervous system corresponds with high basal RSA (slowed heart rate) and increased adaptability and composure during threatening situations.

In “Children's behavioral inhibition and anxiety disorder symptom severity: The role of individual differences in respiratory sinus arrhythmia ,” an original research article in tech science journal , Behaviour Research and Therapy, Viana, Andres G., et al. explored the ability of RSA to moderate the association between BI and anxiety disorder symptom severity. They investigated RSA response during both a basal situation and challenge situation in the context of clinical anxiety. Participants consisted of forty-four children between the ages of 8 and 12, and their mothers. The first session involved self-report questionnaires and clinical interviews, and the second session involved an experiment with the children in a challenge situation. Using a BIOPAC MP system, the researchers gathered electrocardiogram (ECG) data with a wireless BioNomadix ECG transmitter and receiver. They also measured changes in the subjects’ thoracic circumference with the wireless BioNomadix respiration transducer, and recorded online through AcqKnowledge.

The data collected were analyzed to find RSA mean scores and revealed a positive association between BI and anxiety disorder symptom severity. Children with high levels of BI and low RSA responses to basal and challenge situations were found to have the highest levels of anxiety disorder symptoms. In addition, among children with high RSA responses to basal and challenge situations, the association with BI was non-significant. These findings support the supposition that higher levels of RSA, and ability to control the parasympathetic nervous system, may function to weaken the relationship between BI and anxiety. Thus, higher RSA may be related to an increased ability to regulate psycho-physiological responses and emotion, and act as a buffer against psychopathology.

Cardiovascular risk factors (obesity, metabolism, hypertension, etc.) can significantly impact a person’s lifespan. While obesity rates are currently stagnant, they still remain very high. Cardiovascular risk factors have thus become the focus of health research to understand what behaviors might contribute to increased risk. The majority of these studies have been aimed specifically at adults, but little is understood about the origins of these risk factors in childhood. Laurie Wideman, et al thus sought to create a longitudinal study that investigated social and emotional development, called the RIGHT Track Health Study. The RIGHT track study followed participants from infancy to young adult to understand how their self-regulation and increased autonomy via their health behaviors might contribute to cardiovascular risks factors. Participants were measured at five ages: two, four, five, seven, and ten. Participants performed a variety of assessments including body composition, fitness tests, orthostatic challenge (while having heart rate variability recorded), 7-day accelerometry for physical activity and sleep, 24-hour dietary recalls, and blood analysis for various related biomarkers. Researchers also had participants complete extensive self-report measures related to diet, sleep, physical activity, and medical history. Heart rate variability (HRV) was measured using BIOPAC’s dual-channel BioNomadix wireless ECG and Respiration transmitter while participants performed the orthostatic challenge. Heart rate variability measured from the orthostatic challenge was compared to HRV collected during the early years of the study where the infants underwent psychological stressors. Through their RIGHT track health study, the researchers were able to provide valuable about the influence of childhood regulatory abilities on youth healthcare. The researchers hope that their findings will help illuminate potential critical “windows,” or specific points in childhood where people may be more at risk. Assessing when these windows occur could help greatly reduce certain risk factors and help our understanding of how to prevent chronic disease earlier in life.

The negative effects of stress on the body have been widely studied. Stress can be defined as a situation that is causing the current state, or homeostasis, under pressure to change. The human body’s nervous system reacts to stress by changing the amount produced of certain biomarkers. For example, when heart rate elevates, blood pressure rises and the human body reacts and secretes hormones (epinephrine, cortisol, etc.). Experimenters tested the change in the production of specific biomarkers of people with different training backgrounds to understand how acute psychological stress affects their physiological responses. The three group classifications were sedentary subjects, endurance athletes, and strength athletes.
 
EDA (skin conductance), ECG (EKG), and breathing frequency were measured continuously; BP and cortisol were measured after each experiment segment. EDA, ECG, and breathing frequency were measured during the acute psychological stress test using the BIOPAC MP150 data acquisition unit connected to wireless biopotential amplifiers and recorded on BIOPAC’s AcqKnowledge software.

Psychological stress was induced in participants using a Stroop color-word test and math problems. These problems were presented in a slide show where the subjects had a limited amount of time to solve for the correct answers. The researchers found numerous differences in changes in the biomarkers measured in response to the acute psychological stress activities between the three groups. On average, athletes’ cortisol levels changed differently when compared to the sedentary group. Also, skin conductance was shown to have higher levels in the sedentary group than in the athletes. The athletes also had a higher recovery level for systolic blood pressure, which was observed to decrease over the test for the sedentary group.
 
The participants reported to have experienced psychological stress over the course of the activities and this was reinforced by the change in values of the biomarkers measured. This experiment showed that people with different training backgrounds had different responses to psychological stress for related biomarkers. The experimenters concluded that people with different training backgrounds react differently in their changes of certain biomarkers to psychological stress.

A flow state typically occurs when a person’s abilities match the level of difficulty for the current task they are completing. During this state, researchers have found that most people who exhibit flow experience changes in blood pressure, muscle activation, and mental focus, among other responses. They also lose self-awareness and subjectively evaluate time as passing more quickly than usual. All of these factors relate to both the sympathetic and parasympathetic nervous systems, suggesting that flow may involve a non-reciprocal coactivation of both systems. Neuroscience and Psychology researchers in Stockholm, Sweden hypothesize that these effects suggest a potential physiological component that differentiates flow from other states of increased mental effort. This indication may provide accurate measurement of deep concentration in a flow state during various activities, including, but not limited to, music, video games, and writing. To test this hypothesis, the researchers had a total of 77 participants play a modified version of the video game Tetris and then complete a questionnaire about their experience. Participants were instructed to play three game difficulties: Easy, Optimal, and Difficult. In the Optimal setting, researchers adjusted the speed of the game to match the participants’ ability, based on initial performance. Speed was then decreased and increased by three stages for Easy and Difficult modes, respectively. Wireless ECG and Respiration data was recorded using the wearable BioNomadix amplifier (BN-RSPEC); surface electrodes were placed on the left and right chest. In addition, mental activity was measured in 35 participants—this was determined by frontal lobe oxygenation, which was recorded by placing the BIOPAC fNIR100 optical brain imaging sensor on the forehead of each participant. After completing all three video game difficulties, subjects were given a questionnaire to indicate their subjective experience with each game level. The results found that while larger respiratory depth was associated with deeper flow, there was no significant correlation between frontal cortex activity and flow.

Data acquisition hardware and software requirements vary widely based on experiment protocol, classroom setup, field studies, etc. BIOPAC data acquisition hardware platforms support wired, wireless, and fMRI setups, for human or animal subjects, with powerful, intuitive data software for research and teaching applications. Use with a variety of amplifiers, stimulators, triggers, transducers, gas analysis modules, and/or electrodes to acquire life science signals, including ECG, EEG, EOG, EMG, EGG, EDA, Respiration, Pulse, Temperature, Impedance Cardiography, Force, Accelerometry, Goniometry, Dynamometry, Gyro, and more. Combine data hardware for multi-subject or multi-parameter protocols.

Research hardware platforms are fully-integrated with AcqKnowledge^® data acquisition software, which provides automated routines for data scoring, measurement, and reporting, and can support multiple hardware units. Teaching platforms include Biopac Student Lab software with media-rich tutorial style guide lessons for specified objectives, plus active learning options for student-designed experiments and advanced analysis.

Wired (tethered) data acquisition hardware platforms include the MP150 and MP36R Research Systems. The MP150 16-channel system with universal amplifier provides high resolution (16 bit), high-speed acquisition (400 kHz aggregate) with16 analog inputs and two analog outputs, digital I/O lines (to automatically control other TTL level equipment), and online calculation channels. The MP36R 4-channel research system with built-in amplifiers provides four analog inputs and one analog output, I/O port for digital devices, calculation channels, trigger port, headphone jack, and electrode impedance checker. The MP36R supports software-controlled amplifiers and calculation channels.

Mobita^® 32-channel wearable wireless systems are ideal for biopotential applications that demand subject mobility and data logging. The Mobita EEG System uses water electrodes—no skin prep or gels required. Record live data into AcqKnowledge or log to an internal storage card for later upload into AcqKnowledge; modes are easily switched to suit specific protocols.

B-Alert X10^® Wireless Systems provide nine channels of high fidelity EEG plus ECG, and data software for cognitive state metrics software is available. The stand-alone system easily interfaces with MP150 Research System to synchronize with other physiological data.

BioHarness^® with AcqKnowledge is a lightweight, non-restrictive data logger and telemetry system to monitor, record, and analyze a variety of physiological parameters, including ECG, respiration, posture, and acceleration.

Stellar^® Small Animal Telemetry Licenses with AcqKnowledge control wireless data acquisition from Stellar Implantable Telemetry Systems. The easy-to-configure Animal Scheduler works for a subset or complete group of conscious, unrestrained small animals for long term recordings. Multiple display modes can be viewed simultaneously, and signal conditioning tools (e.g., filtering and artifact removal) can be applied.


These and other BIOPAC data hardware and software solutions are used in thousands of labs worldwide and cited in thousands of publications. Learn more about research systems and teaching systems.

Neuromarketing and neuroeconomics research use physiological data to examine a participant’s response to a product, service, or decision making task. Researchers combine cognitive, sensorimotor, and affective responses to marketing stimuli from advertisements to political debates.

• Check how the heart responds to exercise (as with a classic treadmill test)
• See if the walls of the heart chambers are hypertrophied
• Discover the cause of specific symptoms of heart disease
• An ECG calculates a wide range of valuable data valuable including:
• Heart Rate
• Heart Rhythm
• Evidence of previous heart attacks
• Possibility of coronary artery disease
• Signs of decreased oxygen to the heart

Detect and Classify Heartbeats