Archive for 2017
Team Robot
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.
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.
Mobita Wireless EEG Takes a Glimpse Into the Future-Monitoring Prestimulus EEG Data
New studies examining physiological causality and electroencephalographic (EEG) correlations have provided insight on how the wearable and wireless Mobita Amplifier from BIOPAC is making an impact. A research team at the University of California, Santa Barbara, working with the American Institute of Physics, gathered data consistent with findings to conclude the psychological existence of retrocausality. The group focused on light and sound stimuli identification rates for frontal, central, and occipital parts of the brain.
The test data was divided into a pre-stimulus identification rate as well as a post-stimulus rate, to examine any correlation between standard physics and their hypothesis. No information about the stimulus should be expected to exist prior to stimulus selection. EEG recordings preceding each stimulus are analyzed to find correlations with the future selected stimulus.
During the case study, experimental subjects were fitted with a wireless EEG head cap (BIOPAC MB-32EEG-CAP-A) with 32 electrodes; the wearable BIOPAC Mobita Amplifier was utilized for its capacity to record 32 channels of high fidelity wireless EEG data. The head cap’s electrodes used paper-cotton strips soaked in water to make electrical connection with the scalp. Accompanied by BIOPAC’s AcqKnowledge research software, researchers implemented a modern and efficient process while exploring the validity of their test results and research findings.
The campus research group sought to measure electro cortical evoked potentials in the general population using random subjects with hopes of creating a basic means of measurement. Furthermore, “real-time analysis of EEG data may allow quantum events to be predicted in advance, which would affect interpretations of quantum mechanics and our notions of causality” (Baumgart et. al.). While conducting their experiment, the research group focused on keeping a furtive introduction of stimuli to test subjects equipped with the Mobita Amplifier. Stimuli were then chosen using a quantum random number generator (qRNG) and introduced to non-selected test samples.
Time durations for both light and sound stimuli vary in lengths to provide a way to differentiate the stimuli in the digital channel recording. Since sound stimuli contain longer durations than light, stimuli were recognized by digital signal length as well as being recorded by the stimulus control program. To quantify the interval of sound stimuli, the digital conduit also evaluated the voltage in parallel across the buzzer circuit to better monitor the reaction to sound stimuli. Furthermore, identification of stimulus type based on post-stimulus reaction was supported by the group’s current data for the frontal and central regions but not the occipital region.
The yielded results have lead to planning of future tests and have implicated that the existence of retrocausality is in fact measurable.
MEAP and its Implications for Cardiovascular Research
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.
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.
Wireless | Personality Indicators for Flow State Susceptibility
Flow is described as almost complete immersion in a task or activity. Previous studies have identified that this intensive involvement leads to lower feelings of self consciousness, allowing concentration on a task to become effortless. Researchers Tain et al. (2017) sought to understand if there are precursors such as personality that would make individuals more susceptible to flow.
Video games were the chosen task for inducing participants’ state of flow. Computer moderated environments (CME’s) can provide clear goals and instant feedback important for eliciting flow. It’s also easy to manipulate CME’s difficulty, which was an important variable for the study. The researchers hypothesized higher reported levels of task difficulty and shyness would be identifiable precursors for an individual’s ability at attaining flow state.
Out of 350 potential participants who applied for the study, those who had the 20 highest and lowest scores for self-reported shyness were chosen. Once selected, these participants were then asked to play a 3D Tetris-like game. The participants had to play at three different intervals lasting six minutes, with each interval varying the speed in which the pieces fell for the purpose of manipulating difficulty. While on the computer, ECG signals of each participant were acquired through BIOPAC’s BioNomadix wireless respiration and ECG amplifier. Participants were asked to complete a questionnaire asking if they realized how much time had passed. Awareness of time passing allowed for measurement of the amount of flow participants were experiencing. ECG signals and self-reported information were then analyzed, comparing differences between the shy and non-shy groups.
Researchers found significant physiological differences between the two groups. The shy group was seen as having a high heart rate when in flow state, and high levels when completing moderate and difficult tasks. Despite physiological differences, researchers weren’t able to identify shyness as a precursor of flow state. When in flow, participants were found to have increased and deeper respiration, while heart rate and variability stayed moderate. Instead of resulting in an increased amount of mental effort, researchers were able to conclude that flow only required a moderate amount of effort but lead to an increased state of parasympathetic activity.
Being that challenge in the task was induced for the purpose of eliciting anxiety in participants, the authors recommended future experiments should asses the amount of skill the user has before the task is administered. The authors identified that more research should be done in this field examining how different mental and physiological measurements could be telling of flow state.
Video games were the chosen task for inducing participants’ state of flow. Computer moderated environments (CME’s) can provide clear goals and instant feedback important for eliciting flow. It’s also easy to manipulate CME’s difficulty, which was an important variable for the study. The researchers hypothesized higher reported levels of task difficulty and shyness would be identifiable precursors for an individual’s ability at attaining flow state.
Out of 350 potential participants who applied for the study, those who had the 20 highest and lowest scores for self-reported shyness were chosen. Once selected, these participants were then asked to play a 3D Tetris-like game. The participants had to play at three different intervals lasting six minutes, with each interval varying the speed in which the pieces fell for the purpose of manipulating difficulty. While on the computer, ECG signals of each participant were acquired through BIOPAC’s BioNomadix wireless respiration and ECG amplifier. Participants were asked to complete a questionnaire asking if they realized how much time had passed. Awareness of time passing allowed for measurement of the amount of flow participants were experiencing. ECG signals and self-reported information were then analyzed, comparing differences between the shy and non-shy groups.
Researchers found significant physiological differences between the two groups. The shy group was seen as having a high heart rate when in flow state, and high levels when completing moderate and difficult tasks. Despite physiological differences, researchers weren’t able to identify shyness as a precursor of flow state. When in flow, participants were found to have increased and deeper respiration, while heart rate and variability stayed moderate. Instead of resulting in an increased amount of mental effort, researchers were able to conclude that flow only required a moderate amount of effort but lead to an increased state of parasympathetic activity.
Being that challenge in the task was induced for the purpose of eliciting anxiety in participants, the authors recommended future experiments should asses the amount of skill the user has before the task is administered. The authors identified that more research should be done in this field examining how different mental and physiological measurements could be telling of flow state.
Wireless | Testing VO2 Max
Cardiovascular tests during a self-paced maximal exercise protocol (SPV) continually scored high ratings of VO2 max when compared to more traditional procedures. Jenkins et. al sought to understand the underlying causes of this increase in VO2 max by testing SPV versus the more regimented RAMP method. They sought to explore the results through extensive physiological measurement, as well as testing difference in older and younger age groups, while participants completed physical experiments.
The SPV protocol was completed on an air-braked cycle ergometer, which allowed participants to continually vary their Power Output (PO) throughout the test. An electro-magnetically braked cycle ergometer was used for the RAMP protocol, so that PO was fixed for each stage of the incremental RAMP protocol.
VO2 Max is essentially the maximum amount of oxygen utilized during a workout. Forty-four (44) male and female participants completed the experiment, half aged between 18- 30 and half between 50-75. The participants completed each test over a multi-day period. The tests were exhaustive, requiring subjects to cycle in place until they couldn’t any longer.
Jenkins et. al recorded various physiological signals including NIRS, breathing/expired gases, cardiac output/ stroke volume, blood lactate, and electromyography (EMG). BIOPAC’s BioNomadix research acquisition system wirelessly transmitted EMG data using two electrodes placed on participants’ right leg while they completed physical tasks.
Researchers were able find differences in the interaction effects of EMG between the two test protocols in the older group. The results complied with previous research, in that SPV allowed a higher VO2 max compared RAMP. Through monitoring physiological measurement, the study results suggested increased oxygen delivery as to an increase in oxygen-muscle extraction. The researchers found that there wasn’t a significance difference between the two testing protocols with the older population, though it’s unclear why. Overall, the experiment provides greater understanding of what causes differences in VO2 max between the two experimental procedures.
Wearable | Pitch Perfect Analysis
Pitch determines the level of influence on listener perception, physiological arousal, attention, and memory, according to new research published in Human Communication Research (June 2017). Professors at the Communication Department and Department of Translation and Language Sciences at Universitat Pompeu Fabra and the Institute for Communication Research at Indiana University conducted the joint study to examine intonation’s impact on interpersonal influence with self-report analyses and memory tests.
BIOPAC’s BioNomadix helped the researchers discover the psychophysiological signs of comprehension and autonomic arousal. Physiological data aided the researchers in understanding participant attention, offering an objective analysis of the participant’s experience. Each participant identified as female and listened to both narrative and informative commercials, with varying intonation, while wearing BIOPAC’s technology. The participants' retention and cognitive processing suggest that tone does affect interpersonal influence. Commercials, with a unique level of intonation (or the most varying), proved to have the highest standards of influence. The more varying in pitch or tone, the more likely participants were to process and recall information in the commercials. BIOPAC’s BioNomadix allowed the researchers to record wireless EDA from the participants, capturing electrical responses to communication within participants to improve understandings of effective communication. Specifically, BioNomadix wirelessly recorded response data from a wearable transmitter to measure the arousal and attention of participants by capturing their skin conductance response after exposure to stimuli. This type of research will continue evolving media communication and interpersonal influence systems for anyone interested in effective communication strategies. The study’s breakthrough research offers an incentive for further study into the cognitive processing of audio communication.
BIOPAC’s BioNomadix helped the researchers discover the psychophysiological signs of comprehension and autonomic arousal. Physiological data aided the researchers in understanding participant attention, offering an objective analysis of the participant’s experience. Each participant identified as female and listened to both narrative and informative commercials, with varying intonation, while wearing BIOPAC’s technology. The participants' retention and cognitive processing suggest that tone does affect interpersonal influence. Commercials, with a unique level of intonation (or the most varying), proved to have the highest standards of influence. The more varying in pitch or tone, the more likely participants were to process and recall information in the commercials. BIOPAC’s BioNomadix allowed the researchers to record wireless EDA from the participants, capturing electrical responses to communication within participants to improve understandings of effective communication. Specifically, BioNomadix wirelessly recorded response data from a wearable transmitter to measure the arousal and attention of participants by capturing their skin conductance response after exposure to stimuli. This type of research will continue evolving media communication and interpersonal influence systems for anyone interested in effective communication strategies. The study’s breakthrough research offers an incentive for further study into the cognitive processing of audio communication.
Facial EMG for Advertising Research
Wireless │Monitoring and Comparing Speech Rate Processing
Wireless │ Children’s Behavioral Inhibition
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.
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.