Life Science Hardware and Software

As technology improves and increases the likelihood of teams with humans and (semi-)autonomous artificial agents (e.g., virtual or robotic agents), studying potential agent capabilities becomes increasingly meaningful. Studies on organizational science focus on how members of teams communicate effectively. Team members must be able to understand each other’s goals, equipment necessary, and shared information about a given task. Shared mental models (SMMx) have been shown to efficiently expedite this information and allow team members to track each others’ progress.

Matthias Scheutz, Scott DeLoach and Julie A. Adam propose the first formal and computational frameworks for shared organizational mental models for human-robot (H-R) teams by monitoring team members physiological responses. The researchers broke down shared mental models between two key elements; data representations, capturing information and sharing between team members, and computational process, how data representations are shared and maintained. Data representations were broken down into five key component areas; agent capabilities, agent and task states, obligations, activity and equipment types, and functional agent roles. These were all given assigned algorithms to create a formal mathematical model to show how the data representation is maintained. Human Performance Factors (HPF) were also established to potentially provide a means for predicting human behavior and how their performances are affected by various internal, external, organizational and task factors. With the formal framework established, Scheutz, et al. established a computational framework for recording physiological measures to provide what they call “Workload Channel Estimation” that calculates estimates for workloads.
Researchers propose using BIOPAC’s wearable BioHarness monitor that would provide wireless physiological feedback to auditory, tactile, or motor stimuli. These measures would then inform the workload estimation and provide data for the computational framework on how physiological factors maintain the shared mental model. Scheutz, et al’s frameworks can provide new insight into what organizational strategies are most effective in communicating task information and potentially provide a measurement for team members’ most effective workload.

One of the foundational concepts making virtual reality (VR) video games of high interest is the game’s ability to transport the user to a flow state. The visual and auditory stimuli presented are highly immersive, leading the user to focus entirely on the game, often losing track of time. Flow states are characterized by this lack of time awareness, as participants are able to match their abilities with the demands of the game (i.e., the game is not too easy or too hard). But what qualities reflect a flow state as it is happening in the moment? Researchers from Shandong University tested five first-level physiological functions to determine their efficacy in reflecting a flow state, including EMG, EDA, EEG, respiratory rate, and cardiovascular activity. Thirty-six students participated in a VR game while having their physiological responses monitored. Prior to the experiment, the researchers placed BIOPAC’s wearable dual-signal BioNomadix transmitters with appropriate electrodes on the participants to wirelessly record Respiration and ECG data. Participants were then seated in the designated gaming chair for five minutes to record baseline responses. After this, they played the game for six minutes, followed by a questionnaire about flow experience. The results showed that the five physiological functions, as a whole, indicated flow state, though respiratory rate was most effective. The authors note that, as a physiologic arousal marker, respiratory rate best predicted flow state.

Having physiologic indicators of a flow state not only assists future research, but also provides a method for real-time feedback on the efficacy of the game. The authors note that with better biometric data comes the opportunity to provide a better gaming experience, with real-time adjustments. If the physiologic responses and adjustments could be integrated with the gaming software, games would be far more realistic.

I think I’ll go to the gym…

Scientists have long used the power of physiological signals to make inferences about cognitive processes. To bridge the gap between physiology and psychology, exercise scientists often find it interesting to look at a person’s encephalographic brain frequencies (EEG) during settings of physical stress, or namely, exercise. Several studies in the past have aimed to evaluate how the mind operates during strenuous training, but what happens when someone just thinks about exercising?

Researchers Berk et al. have recently performed a study in which various athletes were asked to simply sit, close their eyes, and visualize themselves in a state of rest while their brains were monitored for EEG activity. Participants then were asked to visualize themselves in a state of heavy exercise or physical training. The researchers monitored the athletes’ brain EEG signals using a B-Alert X10 Telemetry system. What they found was a significant difference in brain state, primarily shown by the disparity in gamma wave frequency between visualizations of exercise and rest settings. These results suggest that mental visualization of complex physical tasks may support the construction of functional neural networks in the brain necessary for performing them. This study opens the door to subsequent research in order to understand more about the psychology of physical activity. BIOPAC Systems offers the wireless B-Alert X10 EEG system as well as other wearable and wireless solutions for psychophysiological and exercise research. These options include Mobita 32 channel wearable EEG and biopotential systems and the BioNomadix line of wireless biopotential and transducer amplifiers. These products have been consistently proven to provide accurate, reliable data whether the person wearing them is on the field training, or sitting at home just thinking about it.

Cognitive behavioral therapy (CBT) is a common treatment for people who suffer mental health disorders, such as depression and post-traumatic stress disorder. The goal of this treatment is to help reduce many of the symptoms surrounding the patients’ difficulties, including stress, anxiety, and anger. One issue with cognitive behavioral therapy is the subjective nature of the treatment, which often results in high patient dropout rates. Researchers Winslow, et al., proposed an increase in objective, wearable data used during the therapy process in order to lower participant dropout rates. By recording real-time, mobile health data during and after the scheduled sessions, both patient and clinician can monitor mental health symptoms as they occur.

Testing

To test this, the researchers recruited 24 male participants who qualified for the study by completing several response-based tests measuring the psychiatric symptoms that characterize mental health disorders. Participants then began an 8-10 week CBT program that included a 60-minute session once a week, a personal log of daily activities, the use of a mobile phone app to indicate stress and set daily reminders, and recorded PPG and EDA data. BIOPAC wireless BioNomadix devices were used to record PPG and EDA data by fitting the devices to participants’ fingers.

Despite nine total participants dropping out of the study, researchers determined the amount of therapy sessions completed before drop out by the experimental group was significantly greater than the control group. A similar trend was found in the quantitative physiological data. Stress and other psychiatric factors, measured by heart rate and EDA data, were significantly reduced in the experimental group. Presented with this data, it is realistic to see tangible results in mental health by using mobile health applications and data recording to improve the success of cognitive behavioral therapy. The authors also noted other applications for mobile health data methods. Real-time physiologic data could help military or medical training instructors monitor their trainees’ response to live stimulus sessions. The impact of this improvement may result in tailored lesson plans that increase appropriate resilience training programs before cognitive behavioral therapy is needed.

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.

Very little is known about the origins of cardiovascular risk factors like obesity and altered glucose metabolism and their development during childhood. Adolescence is a time when individuals develop their own health behaviors while gaining increasing autonomy from their parents and this development has an effect on their cardiovascular health later in life. The RIGHT Track Health Study is a longitudinal study that followed participants from age two through young adulthood in an effort to understand how self-regulatory behavior throughout childhood alters the trajectory of various cardiovascular risk factors during late adolescence via health behaviors. For this study, individuals in the RIGHT Track program were re-contacted and invited to participate in adolescent data collection in an effort to gain insight into the origins of behavior that could contribute to an increase in cardiovascular risk factors later in life. This information could be valuable to helping researchers and public health policy administrators target intervention efforts in early childhood, when preventing chronic diseases is most cost-effective and behavior is more malleable.

The researchers used an orthostatic challenge to assess autonomic function, via changes in participant’s heart rate variability (HRV), to a mild physiological stressor. This physical stressor was used as a way of comparing the autonomic function to the physiological stressor paradigms that participants underwent during their early developmental years as part of the RIGHT Track program. HRV measurements provided complementary information regarding the role of autonomic nervous system as a regulator of cardiac control. ECG and respiration recorded using a BioNomadix wireless amplifier set with wearable transmitter to collect HRV at rest. Physiological signals were sent to a BIOPAC MP150 Research System with AcqKnowledge software for collecting and exporting the data in real time.

Data from the RIGHT Track Health Study will provide valuable information for youth healthcare about how health behaviors developed during an individual’s adolescence—such as diet, physical activity, sleep and substance abuse—can later affect cardiovascular health and potentially indicate critical times for reducing certain cardiovascular risk factors by assessing their trajectories.

Psychophysiological Monitoring of Fear Extinction

An estimated 10% of the general population experiences fear of flying (FOF) and 25% of the population that flies experiences distress during the flight. The most effective psychological technique for the treatment of phobias is in vivo exposure. Using planes in real flights, however, takes a large amount of time and money that is not easily accessible. Virtual Reality Exposure Treatment (VRET) of FOF is now well established but generalization of such treatment in clinical settings is still rare.
Researchers from INSERM Centre of Psychiatry and Neurosciences presented a case report of a 31-year-old woman who was chosen for treatment because of her FOF. She attended a demonstration of the new VR equipment and disclosed her FOF. Researcher’s proposed a VRET as she had to fly in a few months and anticipated high anxiety during the scheduled flight. The woman received six sessions of VRET, delivered with standard BIOPAC VR setup, using the included Virtual Environment (VE) of an aircraft with minor adaptations. The woman was seated in an aircraft chair that vibrated during takeoff and turbulences. Researchers used a standard BIOPAC VR Ultimate system, a high-resolution stereoscopic head-mounted display providing a monocular field of view of 60°, a tracking device in order to adapt the field of view to head movements, connected to a MP150 physiological responses amplifier. Skin Conductance Level and Heart Rate were recorded with BIOPAC’s BioNomadix wireless transmitter-receiver modules connected to electrodes. Results showed evidence of a progressive reduction of the subject’s anxiety in the reactivity to takeoffs and turbulences. A Flight Anxiety Situations questionnaire showed a reduction of anticipation anxiety. The woman succeeded in flying alone three months after completion of VRET. Physiological monitoring may provide indexes predictive of outcome; further research is required. Full immersion rather than the graphical quality of VE is the main driver of the sense of reality experiences by the subject.

Muscle mechanical energy expenditure shows the neuromotor strategies used by the nervous system to analyze human locomotion tasks and is directly related to its efficiency. Kaur, Shilpi, Bhatia, and Joshi investigated the impact of gender on the activity of agonist-antagonist muscles during maximum knee and ankle contraction in males and females. Twenty right leg dominant male and female adult volunteers were recruited in the study. Limb dominance was determined according to which leg the individual chooses and relies on to carry out the activities. Movements of knee and ankle used for the maximum contractions were knee flexion and extension, and ankle plantar flexion and dorsiflexion. EMG Signals were recorded wirelessly from the selected ipsilateral and contralateral muscles of both the dominant and non-dominant lower limbs of all subjects. Recordings used BIOPAC multi-channel Wireless EMG and the collected data was stored using AcqKnowledge software included with the data recording system. Results showed that there is no significant influence of gender on agonist-antagonist muscle energy expenditure during maximum knee contraction. For ankle contractions, gender has significant influence on energy expenditure during maximum ankle dorsiflexion. Researchers found that these results are helpful in understanding gender related differences in the energy expenditure of selected muscles during maximum knee and ankle contractions. The wireless BioNomadix modules used by the researchers permitted free movement for the knee and ankle movements required of the study. The Dynamometry-EMG BioNomadix Pair has matched transmitter and receiver module specifically designed to measure one or both signals. These units interface with the MP150 and data acquisition and AcqKnowledge software, allowing advanced analysis for multiple applications and supporting acquisition of a broad range of signals and measurements. Both channels have extremely high-resolution EMG and Dynamometry waveforms at the receiver’s output. The pair emulates a “wired” connection from the computer to subject, in terms of quality, but with all the benefits of a fully-wireless recording system.

There is a major concern growing in the medical community that the ratio of health workers to population size is decreasing. This means that the number of available doctors and medical professionals is starting to become too small to handle the number of people needing medical help. Technologies are therefore being created to help bridge the gap that is being created. These “Quality of Life Technologies” (QoLTs) have been developed to help monitor the health of people. While these technologies have been able to provide physiological support to individuals, the same could not be said for mental symptoms. If QoLTs could move into the realm of psychology and self-therapy, they could help improve the mood and quality of life for patients. A group of researchers from the Polytechnic University of Bucharest and the University of Lincoln recently published a paper that presents a machine learning approach for stress detection using wearable physiological amplifiers. To induce stress in participants, the researchers had them perform both a public speaking and cognitive task, which according to previous research these tasks caused the highest increase in measurable signals.

For their experimental setup, they used a BIOPAC BioNomadix BN-PPGED wireless transducer, hooked up to an MP150 data acquisition system, to record both EDA and PPG signals. They then used AcqKnowledge 4 software to extract both the PPG autocorrelation signal and Heart Rate Variability (HRV). Their results provided accurate stress detection in individuals. Their analysis marks a good starting point toward real-time mood detection, which could lead to people improving their quality of life. One way they could improve their experimental setup however, would be to use the BioNomadix Logger. This device allows for up to 24 hours of high quality data logging allowing the researchers to analyze a subject’s data from when they encountered stressful situations outside the lab.

Social fear learning seems like a fairly straightforward subject. A person observes another reacting or expressing through either verbal or nonverbal cues that a stimulus makes them fearful or afraid. Surprisingly though, little is known about how individuals modulate their perception of the threat. Researchers hypothesized that understanding and shared emotional experiences with others (empathy) play key roles in this, but there are a few investigations that support it. Thus Andreas Olsson, Kibby McMahon, Goran Papenberg, Jamil Zak, Niall Bolger, & Kevin N. Ochsner sought to study the role that empathy plays in social fear learning. The experiment was set up across two stages; one that tested manipulating empathy appraisals and the other individual variability of trait empathy. Researchers enlisted a final sample of 47 men and 53 women who attended Columbia University. The first stage had participants receiving standard instructions that enhanced or decreased empathy and underwent a fear learning procedure; the second had individuals undergoing two observational learning procedures seeing whether the participants expected to undergo the same learning as a demonstrator. During the test stage, conditioned fear response was assessed through skin conductance response (SCR) which was recorded from a BIOPAC MP150 system with an EDA100C amplifier that monitors SCL and SCR data—BioNomadix wireless EDA or Data Logger with EDA transmitter are viable setup alternatives. SCR waveforms were analyzed with AcqKnowledge software for off-line analysis. The study found that subjects enhancing their empathy had the strongest vicarious fear learning over the other groups. The results showed that—especially in the strongly empathetic groups—a demonstrator’s expression during the experiment tasks could serve as social unconditioned stimuli for individuals to vicariously learn fear. Social fear learning thus depends on both a person’s empathetic appraisal and their stable traits. Thus an individual’s ability to learn fear from a social situation comes from not only their inherent emotional state but also from their appraisal of how others around them are reacting to the social stimuli.

 

Focal hand dystonia, also known as “musician’s cramp,” is a movement disorder that causes involuntary flexing in the fingers, or finger cramps, when playing a musical instrument. This disorder poses a huge problem for professional musicians and in some cases can even threaten their careers. Many methods have been attempted to try and alleviate the ailment, but the most effective training method has been the “slow-down exercise” (SDE). This exercise, based on the fact that symptoms disappear when playing at a slow tempo, involves selecting a short passage that triggers the cramps then slowing the tempo down to where the musician can play without involuntary finger flexing. The same passage is then repeated over and over, gradually increasing the speed over time. While this method has helped improve symptoms, it was unclear what aspects of motor skills improved through SDE training.

Michiko Yoshie, Naotaka Sakai, Tatsuyuki Ohtsuki and Kazutoshi Kudo investigated how SDE affected motor performance, muscular activity, and somatosensation in a dystonic pianist. The study entitled “Slow-Down Exercise Reverses Sensorimotor Reorganization in Focal Hand Dystonia: A Case Study of a Pianist” tested a musician over a 12 month period as she underwent SDE training for 30 minutes a day, playing a specific passage that evoked the finger cramps most substantially. During the motor task, the musician’s surface EMG was recorded using EMG amplifiers and a BIOPAC MP Data Acquisition System. Throughout the rehabilitation process the musician improved her speed of key strokes and actually helped recover her normal motor and somatosensory functions. The researchers even found evidence that showed the brain had the capacity to reverse sensorimotor reorganization that was induced by the focal hand dystonia. The findings objectively show that SDE training not only improves effected people’s key strokes but helps to completely recover from the neurological disorder.

Emotional reactions influence, and may help predict, our decisions and offer valuable information for communication and neuromarketing researchers, but emotion is difficult to measure explicitly. Emotional responses are complex phenomena consisting of multiple components, including evaluation/appraisal, subjective feeling, expression, and physiological reaction. This mix of components is difficult to measure. Researchers can interview or survey participants about their feelings—typical measures include traditional Likert-type questions, open-ended questions, or pictorial scales—but self-reporting doesn’t easily convey true or complete emotional response. Self-reporting is further complicated by the fact that participations often choose different terms to describe their feelings or respond that they feel nothing. Blending self-assessment with physiological changes that reflect visceral responses provides an unfiltered representation of emotion.
 

Researchers have long recognized the need for a better tool for Electroencephalogram (EEG) ambulatory monitoring. While many have come up with certain wired solutions, there has not been a valid solution for long term logging or telemetry. BIOPAC Systems, Inc. has now introduced the brand new BioNomadix Logger, a true wireless and wearable ambulatory monitoring device. The Logger allows researchers the option for long term monitoring with its ability to store data for later upload or it can also telemeter back to a computer for live recording in a lab setting. The new BioNomadix logger truly allows you to conduct physiology experiments anywhere and everywhere – you can log up to 24 hours of high-quality data outside the lab and includes ECG, EEG, EMG, EOG, EGG, EDA, Pulse, Respiration, Temperature, Cardiac Output, Heel & Toe Strike, Clench Force, Accelerometer, & Goniometry signals. The device is small in size, only about the size of your hand, making it easy for subjects to take it with them in their everyday activities. 


The BioNomadix Logger fills the void where other more non-accessible devices could not. A study performed by researchers at the University of Minho aimed to create a wireless, wearable EEG ambulatory monitoring solution through a combination of other devices. They tested their tool against other devices (such as BIOPAC’s B-Alert X10) to measure the quality of the EEG signal. Although the researcher’s tool was able to record high quality data, it was bulky and could only be used on subjects in a lab. The BioNomadix Logger thus picks up where this study left off, allowing subjects to log data while performing everyday activities. The Logger’s small size also bypasses the bulky nature of other EEG ambulatory monitoring devices. The BioNomadix Logger thus represents a great step forward in long term wireless, wearable, ambulatory monitoring and data logging devices.