Use Of Physiological Measures Research Articles

Biomarkers of Immersion in Virtual Reality Based on Features Extracted from the EEG Signals: A Machine Learning Approach.

Virtual reality (VR) enables the development of virtual training frameworks suitable for various domains, especially when real-world conditions may be hazardous or impossible to replicate because of unique additional resources (e.g., equipment, infrastructure, people, locations). Although VR technology has significantly advanced in recent years, methods for evaluating immersion (i.e., the extent to which the user is engaged with the sensory information from the virtual environment or is invested in the intended task) continue to rely on self-reported questionnaires, which are often administered after using the virtual scenario. Having an objective method to measure immersion is particularly important when using VR for training, education, and applications that promote the development, fine-tuning, or maintenance of skills. The level of immersion may impact performance and the translation of knowledge and skills to the real-world. This is particularly important in tasks where motor skills are combined with complex decision making, such as surgical procedures. Efforts to better measure immersion have included the use of physiological measurements including heart rate and skin response, but so far they do not offer robust metrics that provide the sensitivity to discriminate different states (idle, easy, and hard), which is critical when using VR for training to determine how successful the training is in engaging the user's senses and challenging their cognitive capabilities. In this study, electroencephalography (EEG) data were collected from 14 participants who completed VR jigsaw puzzles with two different levels of task difficulty. Machine learning was able to accurately classify the EEG data collected during three different states, obtaining accuracy rates of 86% and 97% for differentiating easy versus hard difficulty states and baseline vs. VR states. Building on these results may enable the identification of robust biomarkers of immersion in VR, enabling real-time recognition of the level of immersion that can be used to design more effective and translative VR-based training. This method has the potential to adjust aspects of VR related to task difficulty to ensure that participants are immersed in VR.

A systematic review of physiological signals based driver drowsiness detection systems.

Driving a vehicle is a complex, multidimensional, and potentially risky activity demanding full mobilization and utilization of physiological and cognitive abilities. Drowsiness, often caused by stress, fatigue, and illness declines cognitive capabilities that affect drivers' capability and cause many accidents. Drowsiness-related road accidents are associated with trauma, physical injuries, and fatalities, and often accompany economic loss. Drowsy-related crashes are most common in young people and night shift workers. Real-time and accurate driver drowsiness detection is necessary to bring down the drowsy driving accident rate. Many researchers endeavored for systems to detect drowsiness using different features related to vehicles, and drivers' behavior, as well as, physiological measures. Keeping in view the rising trend in the use of physiological measures, this study presents a comprehensive and systematic review of the recent techniques to detect driver drowsiness using physiological signals. Different sensors augmented with machine learning are utilized which subsequently yield better results. These techniques are analyzed with respect to several aspects such as data collection sensor, environment consideration like controlled or dynamic, experimental set up like real traffic or driving simulators, etc. Similarly, by investigating the type of sensors involved in experiments, this study discusses the advantages and disadvantages of existing studies and points out the research gaps. Perceptions and conceptions are made to provide future research directions for drowsiness detection techniques based on physiological signals.

Self-Report Stress Measures to Assess Stress in Adults With Mild Intellectual Disabilities-A Scoping Review.

Stress has a major negative impact on the development of psychopathology and contributes to the onset of adverse physical conditions. Timely recognition and monitoring of stress-related problems are therefore important, especially in client populations that are more vulnerable to stress, such as people with mild intellectual disabilities (MID). Recent research on the use of physiological measures to assess stress levels emphasize that, in addition to these measures, self-report instruments are necessary to gain insight into the individual perception and impact of stress on daily life. However, there is no current overview of self-report stress measures that focus on the experience of stress in the present moment or in daily life. To provide an overview of the existing self-report stress measures for clinicians and researchers, a scoping review was conducted. In addition, to advise clinical professionals on the use of self-report measures of stress for people with MID, the results of an expert consultation were used to refine the preliminary findings. A systematic scoping literature search resulted in a total of 13 self-reported stress measures that met the final inclusion criteria, of which three were developed specifically for assessing stress in adults with MID (GAS-ID, LI, and SAS-ID). For each included self-report stress measure, the psychometric quality, assessment procedure, and suitability for adults with MID were reported. These were supplemented by the findings from the expert consultation. Implications for clinical practice on the use of self-report stress measures, particularly for people with MID, are discussed. Recommendations for future research and development are given.

A Systematic Review of Physiological Measurements, Factors, Methods, and Applications in Virtual Reality

Measurements of physiological parameters provide an objective, often non-intrusive, and (at least semi-)automatic evaluation and utilization of user behavior. In addition, specific hardware devices of Virtual Reality (VR) often ship with built-in sensors, i.e. eye-tracking and movements sensors. Hence, the combination of physiological measurements and VR applications seems promising. Several approaches have investigated the applicability and benefits of this combination for various fields of applications. However, the range of possible application fields, coupled with potentially useful and beneficial physiological parameters, types of sensor, target variables and factors, and analysis approaches and techniques is manifold. This article provides a systematic overview and an extensive state-of-the-art review of the usage of physiological measurements in VR. We identified 1,119 works that make use of physiological measurements in VR. Within these, we identified 32 approaches that focus on the classification of characteristics of experience, common in VR applications. The first part of this review categorizes the 1,119 works by field of application, i.e. therapy, training, entertainment, and communication and interaction, as well as by the specific target factors and variables measured by the physiological parameters. An additional category summarizes general VR approaches applicable to all specific fields of application since they target typical VR qualities. In the second part of this review, we analyze the target factors and variables regarding the respective methods used for an automatic analysis and, potentially, classification. For example, we highlight which measurement setups have been proven to be sensitive enough to distinguish different levels of arousal, valence, anxiety, stress, or cognitive workload in the virtual realm. This work may prove useful for all researchers wanting to use physiological data in VR and who want to have a good overview of prior approaches taken, their benefits and potential drawbacks.

Experience of Registered Nurses of Postoperative Pain Assessment Using Objective Measures among Children at Effia Nkwanta Regional Hospital in Ghana

Introduction: People undergoing surgical operations experience some level of pain. Assessing pain intensity is one of the duties of the nurse and it involves subjective measures (self-report), and objective measures (behavioural and physiological). It has been observed by the researcher that nurses in clinical practice do not assess pain before management more so among children. Also, there is limited research in the area of pain assessment in children who cannot communicate. This study aimed to describe the experiences of registered nurses in assessing postoperative pain among children (0-3 years) using objective measures. Methods: Descriptive phenomenology was the chosen design. Maximum variation sampling was used to recruit nine registered nurses with experience in nursing children after surgery at Effia Nkwanta Regional Hospital (ENRH) in Ghana. The researchers conducted audio-recorded in-depth interviews, transcribed verbatim and qualitatively analyzed following Colaizzi’s approach to descriptive phenomenology analysis. Results: The study revealed that the nurses have more experience with using behavioural measures with limited experience with the use of physiological measures. The behavioural measures mostly reported from their experience were changes in facial expression and unusual crying of the child. In general, the nurses do not formally use consistent approaches to assess pain among children. Conclusion: Given these results, opportunities should be made available for nurses to enhance their skills and utilize evidence-based approaches to formally assess pain among post-operative children.

Dynamic assessment of control room operator's cognitive workload using Electroencephalography (EEG)

In modern plants with high levels of automation, acquiring an adequate mental model of the process has become a challenge for operators. Studies indicate that sub-optimal decisions occur when there is a mismatch between the demands of the process and the human's capability. This mismatch leads to high cognitive workload in human operators, often a precursor for poor performance. Recently, researchers in various safety critical domains (aviation, driving, marine, NPP, etc.) have started to explore the use of physiological measurements from humans to understand their cognitive workload and its effect. In this work, we evaluate the potential of EEG to measure cognitive workload of human operators in chemical process control room. We propose a single dry electrode EEG based methodology for identifying the similarities and mismatch between the operators’ mental model of the process and the actual process behaviour during abnormal situations. Our results reveal that SƟ(ω), the power spectral density of theta (ɵ) waves (frequency range 4–7 Hz) in the EEG signal has the potential to identify such mismatches. Results indicate that SƟ(ω) is positively correlated with workload and hence can be used for assessing the cognitive workload of operators in process industries.

Mindfulness-based interventions in undergraduate students: a systematic review

Objective To describe how mindfulness-based intervention (MBIs) are held with undergraduate students, systematize the outcomes of these interventions and indicate possible limitations. Method: Systematic searches were performed in seven databases in January 2019 with the following descriptors: (“mindfulness intervention” AND (“undergraduate” OR “college” OR “students”). Results: A total of 510 articles were found, and 19 articles fully met the inclusion criteria. The searches showed a visible growth in this field of research as articles publications increased in the past years. Regardless of intervention’s length, most studies reported beneficial effects. The examination of Anxiety, Stress, and Depression constructs have shown to be predominant. Even though study designs were mostly randomized controlled trials (RCT), it was noticed a shortage use of physiological measures and follow-up assessments. Conclusions: Nonetheless, MBIs have shown to be promising interventions to promote mental health in academic settings.

Team Physiological Dynamics: A Critical Review.

Review the use of physiological measurement in team settings and propose recommendations to improve the state of the science. New sensor and analytical capabilities enable exploration of relationships between team members' physiological dynamics. We conducted a review of physiological measures used in research on teams to understand (1) how these measures are theoretically and operationally related to team constructs and (2) what types of validity evidence exist for physiological measurement in team settings. We identified 32 articles that investigated task-performing teams using physiological data. Articles were coded on several dimensions, including team characteristics. Study findings were categorized by relationships tested between team physiological dynamics (TPD) and team inputs, mediators/processes, outputs, or psychometric properties. TPD researchers overwhelmingly measure single physiological systems. Although there is research linking TPD to inputs and outputs, the research on processes is underdeveloped. We recommend several theoretical, methodological, and statistical themes to expand the growth of the TPD field. Physiological measures, once established as reliable indicators of team functioning, might be used to diagnose suboptimal team states and cue interventions to ameliorate these states.

A Systematic Review of Physiological Measures of Mental Workload.

Mental workload (MWL) can affect human performance and is considered critical in the design and evaluation of complex human-machine systems. While numerous physiological measures are used to assess MWL, there appears no consensus on their validity as effective agents of MWL. This study was conducted to provide a comprehensive understanding of the use of physiological measures of MWL and to synthesize empirical evidence on the validity of the measures to discriminate changes in MWL. A systematical literature search was conducted with four electronic databases for empirical studies measuring MWL with physiological measures. Ninety-one studies were included for analysis. We identified 78 physiological measures, which were distributed in cardiovascular, eye movement, electroencephalogram (EEG), respiration, electromyogram (EMG) and skin categories. Cardiovascular, eye movement and EEG measures were the most widely used across varied research domains, with 76%, 66%, and 71% of times reported a significant association with MWL, respectively. While most physiological measures were found to be able to discriminate changes in MWL, they were not universally valid in all task scenarios. The use of physiological measures and their validity for MWL assessment also varied across different research domains. Our study offers insights into the understanding and selection of appropriate physiological measures for MWL assessment in varied human-machine systems.

Measuring presence in video games: An investigation of the potential use of physiological measures as indicators of presence

Abstract Presence has become an increasingly central component of Games User Research (GUR) as developments in technology continuously make modern video games more conducive to the sensation of ‘being there’ in virtual environments. The quality of games is now commonly evaluated based on how reliably they elicit presence; however, no standardized objective measure of presence currently exists. This study investigated two physiological measures, Galvanic Skin Response (GSR) and task-irrelevant Event-Related Potentials (ERPs), as potential objective indicators of presence in games. A total of 34 participants were divided into low or high presence groups based on their self-reported presence evoked from experiencing a horror game while task-irrelevant tones were being played. It was hypothesized that presence is associated with attentional resources being fully absorbed by the game, which would lead to less or insufficient perceptual resources available for processing the concurrent game-irrelevant oddball-task. This effect was expected to manifest as a measurable decrease in early ERP component amplitudes. It was also hypothesized that presence would make players react to emotion-eliciting events as if they were real, which would result in more GSR peaks throughout the game while not impacting event response magnitude. ERP components (N1, MMN and SW), GSR peaks/min and response magnitude were compared between the presence groups revealing significant differences in GSR peaks/min and early ERP components of N1 and MMN, but not in GSR response magnitude. The findings support the hypotheses and show that GSR peaks/min, N1 and MMN correlate with presence and have potential as presence indicators.

Emotion theory in education research practice: an interdisciplinary critical literature review

In this critical literature review, we seek to understand why multidimensional, psychological measures of human emotion that have been popular in the study of emotion and learning to date, may not yield the statistical power or construct validity necessary to consistently explain or predict human learning. We compare competing theories and conclude that educational studies tend towards use of multi-dimensional models of human emotions which, while useful in educational psychology and therapeutic practice, suffer from psychometric flaws and generate lower power when used as empirical research constructs compared with the “basic emotion” models and their derivatives popular in the neurobiological, cognitive, and social sciences. Based on our review, we conclude that more extensive use of physiological measures and analysis of spontaneous emotion language, both rooted in the basic emotions tradition rather than continued psychological measurement of multi-dimensional emotions, may yield more consistent and significant results and reduce education researchers’ reliance on self-report measures. Findings from the review may advance the selection of operational definitions and formulation of research questions for new empirical studies of the intersections between emotion and learning.

Are Patient Admission Handoffs from the ED to MICU PARfect?

Studies have highlighted the importance of using objective physiological measures in quickly identifying critical patients who are at an increased risk of clinical deterioration and decompensation. In this exploratory study, we investigate the use of physiological measures within a modified Patient at Risk (PAR) framework for identifying potential ICU admissions during ED-MICU handoffs.

Measuring Cognitive Load in Embodied Learning Settings.

In recent years, research on embodied cognition has inspired a number of studies on multimedia learning and instructional psychology. However, in contrast to traditional research on education and multimedia learning, studies on embodied learning (i.e., focusing on bodily action and perception in the context of education) in some cases pose new problems for the measurement of cognitive load. This review provides an overview over recent studies on embodied learning in which cognitive load was measured using surveys, behavioral data, or physiological measures. The different methods are assessed in terms of their success in finding differences of cognitive load in embodied learning scenarios. At the same time, we highlight the most important challenges for researchers aiming to include these measures into their study designs. The main issues we identified are: (1) Subjective measures must be appropriately phrased to be useful for embodied learning; (2) recent findings indicate potentials as well as problematic aspects of dual-task measures; (3) the use of physiological measures offers great potential, but may require mobile equipment in the context of embodied scenarios; (4) meta-cognitive measures can be useful extensions of cognitive load measurement for embodied learning.

Physiological Measurement in the Organizational Sciences: A Review and Recommendations for Future Use

We review recent literature in the organizational sciences that uses some form of physiological measurement. We organize our review in terms of the underlying constructs that physiological measures were intended to assess. The majority of such constructs represents stress, health, or arousal, although these constructs are often studied in an attempt to understand a diverse set of other phenomena. The majority of the studies we discuss use peripheral measures of the autonomic nervous system or biological indicators of various physiological subsystems, such as the cardiovascular, metabolic, or immunological. Advances in instrumentation and biological assaying methods have made the use of physiological measures more feasible, and in some cases, affordable for researchers without specialized training in physiology. The significant challenges we discuss mostly concern issues of sampling and timing, as well as the careful selection of physiological indicators to fit the theoretical demands of the research.

Examining Social Desirability in Measures of Religion and Spirituality Using the Bogus Pipeline

A primary concern in the psychology of religion is the distinct possibility that responses to empirical assessments of individuals’ degree and type of religiosity and spirituality are exaggerated owing to social desirability bias. In spite of increased secularization in American culture and a growing distrust of organized religion, religious involvement, personal religiosity, and spirituality are still viewed as highly desirable characteristics. This study estimates the extent of social desirability biases that affect self-reports of religion and spirituality by utilizing a bogus pipeline procedure. In this procedure, participants are convinced that experimenters can detect disingenuous responses to individual items on questionnaires through the use of physiological measures, although no physiological data are actually collected. If the self-reports of participants in the bogus pipeline condition indicate greater religiosity or spirituality than those in the control condition, self-report bias is indicated. The bogus pipeline procedure has been used in other areas of study to increase veracity of self-reports when social desirability effects are present (such as reporting sexual behaviors or prejudice). The results indicate that social desirability biases influence multiple constructs including religious orientations, religious coping, and daily spiritual experiences. Implications for future research relying on self-reports of religion and spirituality are discussed.

Evaluating the Impact of AAC Interventions in Reducing Hospitalization-related Stress: Challenges and Possibilities

Hospitalization is a stressful context for all children and their families, but especially for children with communication difficulties. Effective communication using augmentative and alternative communication (AAC) strategies can play a critical role in preparing and supporting everyone involved in such situations to have discussions that minimize insecurity, allow children to express their concerns, and so decrease negative stress and anxiety. However, there is a critical need to identify robust and reliable ways of evaluating the effectiveness of interventions that seek to achieve this aim. This research note illustrates some of the challenges and problems that require attention and suggests possible new research tools, for example, the use of physiological measures. The evaluation of an AAC intervention on a day surgery ward is described and used to illustrate one potential physiological measure for evaluating the impact of an intervention.

Dynamics of Perceived Exertion in Constant-Power Cycling: Time- and Workload-Dependent Thresholds

Purpose: The purpose of this study was to test the dynamics of perceived exertion shifts (PES) as a function of time and workload during constant-power cycling. Method: Fifty-two participants assigned to 4 groups performed a cycling task at 4 different constant workloads corresponding to their individual rates of perceived exertion (RPEs = 13, 15, 17, and 19, respectively). PES (“increased”/“decreased” perceptions) without magnitude were reported when they occurred. PES “increased” percentages in different nonoverlapping temporal windows and for each workload were calculated to study the time- and workload-dependent relations, respectively. Results: A fluctuating PES dynamic characterized the cycling at RPE-13 and RPE-15. In contrast, a nonfluctuating PES dynamic characterized the cycling at RPE-17 and RPE-19. A time-dependent PES threshold, manifested as a switch from PES fluctuating to nonfluctuating dynamics, emerged in the RPE-15 condition near volitional exhaustion. A workload-dependent PES threshold occurred from RPE-15 to RPE-17. Conclusions: Time- and workload-dependent thresholds were revealed studying the PES dynamics in constant cycling. Monitoring PES can complement or provide an alternative to the use of physiological measures for an accurate control of training workloads.

Collection and Analysis of Physiological Measures in Driving Research

Driving research has recently seen a surge in the collection and use of physiological measurements. This use of physiological data is often part of an attempt to either measure cognitive load or detect affective states. While these methods are becoming more popular it seems that many driving researchers are still unsure of the best methods of data collection and analysis. This discussion panel will center around a question and answer session between the audience and experts in techniques for the collection and analysis of physiological measures in the driving research fields to help researchers increase their productivity in this space and provide a forum for frank discussion on methods in the area.

Cognition and Physiological Response

Complex tasks in large and error-prone environments require unobtrusive, unbiased and real-time measurement of cognitive variables to promote safety and to achieve optimal performance. Despite the prevalence of physiological measurement of cognitive constructs and cognitive performance, such as workload, little has been done to justify the inference of cognitive states from physiological measures. We develop a framework based on the extant literature to provide the groundwork for further validation of physiological measurement. Specifically, we leverage theoretically-grounded conditions of measurement to aid in investigating the logical sampling and construct validity for use of such metrics. Further meta-analytic investigation is warranted to validate the model and justify use of physiological measures.

Physiological Measurements as Validation of Alertness Observations: An Exploratory Case Study of Three Individuals with Profound Intellectual and Multiple Disabilities

Although observation largely takes into account the needs and abilities of individuals with profound intellectual and multiple disabilities, several difficulties are related to this assessment method as well. Our aim in this study was to investigate what possibilities the use of physiological measurements make available to validate alertness observations. Measurements of five physiological parameters were compared with video observations of three individuals with profound intellectual and multiple disabilities. Because our first findings are broadly in line with those of studies involving individuals in the general population, we hypothesize that physiological measurements can be used to validate alertness observations in individuals with profound intellectual and multiple disabilities. Future studies are needed to compensate for the limitations of this study and to answer ensuing questions.