Archive for 2016
Wearable | Flow State in VR Video Games
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.
Wireless | Emotional Regulation
Wouldn’t it be nice to be able to regulate your emotional reactions? Birk and Bonanno (2016) studied the adaptiveness of modifying emotional regulation (ER) strategies based on affective and physiological feedback. They wanted to understand how people use emotional regulation to adjust from thinking about emotional situation to more neutral information (distraction). To develop a more coherent comprehensive understanding, researchers studied whether people use internal feedback (negative intensity, corrugator’s activity, heart rate) to guide emotional regulation. Birk and Bonanno performed two studies: Study 1 examined switching from reappraisal to distraction and Study 2 examined switching from distraction to reappraisal.
The studies explored whether internal feedback influenced people to shift to an optimal strategy (distraction), instead of a nonoptimal (reappraisal) strategy, when regulating strong emotional reactions. In addition, both researchers tested whether the frequency of switching and response to internal feedback (RIF) predicted well-being. The researchers found that negative intensity, corrugator’s activity, and the magnitude of heart rate deceleration were higher on switching rather than maintained strategies. In Study 1, researchers found that a greater switching frequency showed higher rates of higher and lower life satisfaction.
Birk and Bonanno were able to record and analyze data using a BIOPAC Research System with wireless BioNomadix and AcqKnowledge software. Facial electromyography, electrocardiography, and electrodermal activity were the physiological signals measured. Wireless BioNomadix data recording allows researchers to assess ambulatory subjects in an environment most appropriate for their study. BioNomadix amplifiers are capable of interfacing with MP Systems and AcqKnowledge software for a complete, wireless solution that supports advanced analysis for multiple applications.
In conclusion, Birk and Bonanno collectively found that internal feedback about the experience of intense negative emotion guides the decision to switch form reappraisal to distraction in Study 1, but not the reverse order of strategies in Study 2.
Wearable | Visualizing Exercise
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.
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.
Evaluation of an mHealth Application for Stress Management | Wireless BIOPAC
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.
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.
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.
Wireless | Psychological Stress Across Training Backgrounds
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.
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.
Wearable | Cardiovascular Risk Factors in Children
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.
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.
Wireless | Fear of Flying
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.
Wireless | Flow State
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.
Wireless | Influence of Gender on Muscle Activity
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.
Wireless Data | Sitting and Muscle Weakness
A growing health risk in modern times is the increased amount of time the average person spends sitting. Whether at work for 8 hours at a computer or on the couch all day watching a favorite show, sitting contributes to a sedentary lifestyle, which is a known risk factor for cardiovascular disease and diabetes. It has been found that even those who exercise regularly, yet spend a prolonged portion of their day seated, have increased risk of similar ailments. Though many health risks of sitting are known, there has been little research on its impact on the musculoskeletal system. Physical therapists have noted an inexplicably high rate of clinical weakness of the gluteus maximus muscle. Doctoral candidates in physical therapy at City University of New York recently published a capstone project on their hypothesis that the habit of prolonged sitting directly leads to weakening of the gluteus maximus and the hamstrings. In the experiment, subjects were asked, after a brief warm-up, to perform maximal voluntary isometric contraction (MVIC) for both muscle groups. In addition, two functional activities were performed by the subjects: a “sit-to-stand” exercise and a “forward step-up” exercise. The subjects were separated into two groups based on their sitting/standing habits throughout the day. Surface EMG signals were recorded from the subjects using a BioNomadix wireless EMG Transmitter and Receiver set, along with an MP150 data acquisition system. Using AcqKnowledge software, the researchers were able to process the raw EMG signals with automated data reduction routines and statistical analysis. Further analysis of the data found no statistically significant differences in gluteus strength between the two groups. However, the group still believes that there remains to be studied the muscular effects of prolonged sitting. Further studies may be benefitted by the use of the BioNomadix Logger for continuous, 24-hour logging of a range of physiological signals. BIOPAC offers BioNomadix wireless physiology systems and a number of other solutions for EMG and other signals and measurements.
Wireless | Emotion Processing in Schizophrenia
Schizophrenia has long been known to be a very complicated and poorly understood cognitive disorder. To attempt to understand the differences in emotional processing in schizophrenic patients, psychologists use physiological parameters to quantify psychological activity. Researchers Peterman et al. performed a study in which Galvanic Skin Response (GSR or EDA) and Facial Electromyography (fEMG) were recorded in schizophrenic and control subjects in response to social stimuli to assess the differences in adaptive emotional response. To measure these signals, they used wireless BIOPAC BioNomadix amplifiers, one for GSR (BN-PPGED) and two for fEMG (BN-EMG2). The participants were asked to view a block of images of the same category (e.g., social positive, non-social negative, etc.), then select a positivity response (valence rating) as to how they felt about the images. Subjects viewed several blocks of images to evoke differing responses. The self-reported valence ratings were paired to physiological data acquired with wireless BioNomadix transmitters. The GSR and fEMG were collected with an MP150 data acquisition system, and the data was analyzed with AcqKnowledge software. Researchers found that the Schizophrenic subjects responded similarly to the controls in the valence ratings, but their GSR and fEMG data diverged significantly. The Schizophrenic subjects showed a stronger overall GSR response to the images; however they did not show an effect by the sociality of the pictures. The fEMG response was also greater overall in the Schizophrenic group, but also did not vary by sociality. The results provide physiological background to the disrupted self-awareness of emotion processing in Schizophrenics. The complexity of emotion processing in cognitive disorders continues to elude us and to pave new avenues for scientific study. Along with the BioNomadix modules used in the study, BIOPAC Systems offers several wireless, wearable physiological data acquisition and analysis systems for psychophysiological research.
Wireless | HRV Data and Home Exercise
Exercise researchers at Johns Hopkins University recently performed a study regarding the effectiveness of using short-term heart rate variability (HRV) as a means to monitor the efficiency and safety of cycling activity. Though it had been previously shown that beat-by-beat heart rate data is a good indicator of physiological stress, the potential value of short-term HRV as an automated assessment of exertion level was unknown. The study was designed as such: subjects were asked to perform a 13-minute cycling exercise on an interactive Biking Exercise program, and HRV data was recorded with an electrocardiogram transmitter. Time periods denoting different levels of exercise before and during the program were classified as “rest,” “highest exertion” and “recovery.” A BIOPAC BN-RSPEC wireless ECG and Respiration transmitter/receiver pair was used to acquire appropriate heart rate data. Data from the wireless ECG amplifier was sampled by an MP150 data acquisition system connected to a standard laptop PC. From each subject, nine sets of ECG data were obtained—three each for rest, highest exertion, and recovery time periods. These data sets were recorded with AcqKnowledge software. Further analysis showed significant differences were found among seven HRV variables between time-domains characterized by differing levels of physical exertion. These data were shown to closely match their predictive model. This allowed researchers to conclude that the HRV coupled to time-domain indices separated by exertion level accurately reflected autonomic balance and stress levels during the exercise program. This suggests HRV data can be used short term to measure the efficacy of home-based exercise programs. BIOPAC Systems offers a variety of solutions for Heart Rate Variability and ECG extraction including wireless, wearable and MRI applications. Use of these physiological parameters can be utilized in further studies, continuing to examine and compare the benefits of home-based cycling and other exercise programs for subjects with differing lifestyles and clinical conditions.