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.

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.

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.

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.