Using Machine Learning to Regulate Intensity of Immersion Therapy Treatment of Phobias Through Vital Feedback

The treatment of acrophobia has been trying to keep up with newer technology with the incorporation of virtual reality for exposure therapy, but that approach still lacks automation and still leaves a good portion for human error. The proposed method introduced in this paper is that a machine learning model could replace the need for continuous human intervention. With a few different models of bridges and buildings and the ability for a machine learning model to dynamically alter the height of these building we could theoretically put the patient in the exact situation that will maximize the efficiency of their treatment. The proposed solution will utilize a random forest classifier and with continuous access to the patient’s heart rate, blood pressure and galvanic skin response it can translate that information to fear levels. Using a second deep neural network it can determine what kind of environment will be most effective in treating the patient

Voice Analysis for Stress Detection and Application in Virtual Reality to Improve Public Speaking in Real-time: A Review

Stress during public speaking is common and adversely affects performance and self-confidence. Extensive research has been carried out to develop various models to recognize emotional states. However, minimal research has been conducted to detect stress during public speaking in real time using voice analysis. In this context, the current review showed that the application of algorithms was not properly explored and helped identify the main obstacles in creating a suitable testing environment while accounting for current complexities and limitations. In this paper, we present our main idea and propose a stress detection computational algorithmic model that could be integrated into a Virtual Reality (VR) application to create an intelligent virtual audience for improving public speaking skills. The developed model, when integrated with VR, will be able to detect excessive stress in real time by analysing voice features correlated to physiological parameters indicative of stress and help users gradually control excessive stress and improve public speaking performanceComment: 41 pages, 7 figures, 4 table

Measuring prefrontal cortex response to virtual reality exposure therapy in freely moving participants

Virtual Reality Exposure Therapy has demonstrated efficacy in the treatment of phobias; yet little is known about its underlying neural mechanisms. Neuroimaging studies have demonstrated that both traditional exposure therapy and virtual reality exposure therapy normalise brain activity within a prefrontal - amygdalar fear circuit after the treatment. However, the previous studies employed technologies that perhaps impact on ecological validity and naturalness of experience. Moreover, there are no studies investigating what is happening in the brain within a virtual reality session. This PhD takes a multidisciplinary approach and draws upon research areas of cognitive neuroscience, neuropsychology, and virtual reality. The approach is twofold - developmental and experimental. A key methodological objective was to maximise ecological validity by allowing freedom of movement and sight of one’s own body. This was approached by combining wearable fNIRS within Immersive Projection Technology (IPT). The stimulus was adapted from a classic VR experiment - Pit Room. The scope of this PhD includes three experiments. The first pilot experiment tested the potential of combining the wearable Functional Near-Infrared Spectroscopy (fNIRS) device – NIRSport, with virtual reality (VR) display - CAVE-like Immersive Projection Technology (IPT) system – Octave. The aim was to test the feasibility of the protocol in terms of the design, integration of technology, and signal to noise ratio in the Pit Room study, which involved measuring brain response during exposure to heights in virtual reality. The study demonstrated that brain activity could be measured in IPT without a significant signal interference. Although there was no significant change in brain activity during exposure to virtual heights, the study found trends toward increased HbO in the prefrontal cortex. The second study investigated the brain activity indicative of fear inhibition and cognitive reappraisal within a single session of VRET in healthy controls. The heart rate was also measured as an indicator of emotional arousal (fear response) during the VRET session. 27 healthy volunteers were exposed to heights in virtual reality. Changes in oxygenated haemoglobin concentration in the prefrontal cortex were measured in three blocks using a wireless fNIRS, and heart rate was measured using a wireless psychophysiological monitor. Results revealed increased HbO concentration in the DLPFC and MPFC during exposure to the fear-evoking VR, consistent with fear inhibition and cognitive reappraisal measured in previous neuroimaging studies that had not used VR. Within-session brain activity was measured at much higher temporal resolution than in previous studies. Consistent with previous studies, a trend showed an increase of brain activity in the DLPFC indicative of cognitive reappraisal at the beginning of the session. Then additionally the MPFC was activated consistent with fear inhibition. The heart rate showed a trend towards a gradual decrease within a session. The aim of the third study was to investigate the neural basis of VRET in an acrophobic population. In particular, the study focused on measuring functional brain activity associated with both within- and between-session learning. Psychophysiological monitoring was also employed to measure levels of emotional arousal within- and between sessions. 13 acrophobic volunteers took part in three-session VRET for a fear of heights. Changes in HbO in the prefrontal cortex were measured in three blocks to investigate within–session brain activity and across three sessions to investigate between-session inhibitory learning. Results demonstrated that phobic participants have decreased activity in the DLPFC and MPFC at the beginning, however, after three sessions of VRET, activity in these brain areas increased towards normal (measured in healthy controls). Although there was no within-session learning during the first and second session, the study found a significant increase in the DLPFC at the beginning of a session. During the second block, additionally, the MPFC was activated. The magnitude of brain activity in those regions was negatively correlated with the initial level of acrophobia. Due to the technical difficulties, no significant results were found in psychophysiological measures. However, subjective fear ratings decreased significantly within- and between sessions. Moreover, participants who felt more present demonstrated stronger results in brain activity at the end of VRET. This is the first project that investigated the neural correlates of fear inhibition and inhibitory learning by combining a VR display in which people can move around and see their body, with wearable neural imaging that gave a reasonable compromise between spatial and temporal resolution. This project has an application in widening access to immersive neuroimaging across understanding, diagnosis, assessment, and treatment of, a range of mental disorders such as phobia, anxiety or post-traumatic stress disorder. An application that is receiving an interest in the clinical community is repeatable, direct and quantifiable assessment within clinics, to diagnose, steer treatment and measure treatment outcome

Presence 2005: the eighth annual international workshop on presence, 21-23 September, 2005 University College London (Conference proceedings)

OVERVIEW (taken from the CALL FOR PAPERS) Academics and practitioners with an interest in the concept of (tele)presence are invited to submit their work for presentation at PRESENCE 2005 at University College London in London, England, September 21-23, 2005. The eighth in a series of highly successful international workshops, PRESENCE 2005 will provide an open discussion forum to share ideas regarding concepts and theories, measurement techniques, technology, and applications related to presence, the psychological state or subjective perception in which a person fails to accurately and completely acknowledge the role of technology in an experience, including the sense of 'being there' experienced by users of advanced media such as virtual reality. The concept of presence in virtual environments has been around for at least 15 years, and the earlier idea of telepresence at least since Minsky's seminal paper in 1980. Recently there has been a burst of funded research activity in this area for the first time with the European FET Presence Research initiative. What do we really know about presence and its determinants? How can presence be successfully delivered with today's technology? This conference invites papers that are based on empirical results from studies of presence and related issues and/or which contribute to the technology for the delivery of presence. Papers that make substantial advances in theoretical understanding of presence are also welcome. The interest is not solely in virtual environments but in mixed reality environments. Submissions will be reviewed more rigorously than in previous conferences. High quality papers are therefore sought which make substantial contributions to the field. Approximately 20 papers will be selected for two successive special issues for the journal Presence: Teleoperators and Virtual Environments. PRESENCE 2005 takes place in London and is hosted by University College London. The conference is organized by ISPR, the International Society for Presence Research and is supported by the European Commission's FET Presence Research Initiative through the Presencia and IST OMNIPRES projects and by University College London

Contributions to Neuropsychotherapy of the Combined Use of Neuroimaging and Virtual Exposure for Assessment in Psychological Treatments

Neuropsychotherapy is a new philosophy in the treatment of mental disorders that bases its principles in the application of the information we have about the brain activations and brain functioning to adjust the therapy to them, in order to center the process in how the brain evolves to its normal activations. New tools in the field of neuroimaging have helped in this process, providing accurate and detailed information about how the particular brain of each patient works. Between the many neuroimaging techniques available nowadays, the functional magnetic resonance (fMRI) stands out by its high spatial resolution, which allows a better knowledge of which brain area is activated before each stimulus or while performing each activity. The disadvantages this technique presents in terms of size of the scanner and restriction of movements give light to another technique, more suitable in certain domains: the electroencephalography (EEG), which provides a greater freedom of movement and higher temporal resolution. For the purposes of this PhD Thesis, both techniques will be compared, in order to find which one better suits our interests. For doing so, another factor will be taken into account. Due to the limitations the neuroimaging techniques have in terms of presentation of the stimuli, we are not able to expose the subject to certain kinds of real life situations. There is where the virtual reality (VR) enters the scene. With VR we are able to move the subject to a virtual world where any kind of stimulus is possible. In the case of neuropsychotherapy, it will allow the exposition of the patient to a situation related to his disorder, in a safer and more controlled environment. In fact, virtual reality has been widely used for the treatment of psychological disorders; but, until now, it has not been applied during the assessment of the disease. For the aims of this Thesis, virtual environments will be used for the assessment of subjects before and after undergoing a psychological treatment for a specific disorder, using neuroimaging techniques to find useful information that could help during the therapeutic process. As an example of disorder, the phobia to small animals (spiders and cockroaches) has been chosen, although the conclusions of this study could be extended to other kinds of psychological disorders. Before being able to assure that the brain activations obtained are related to the disorder and not to other issues, it is needed to measure the sense of presence the subjects felt during the virtual experience. This is why before the assessment of a psychological disorder, a study of the sense of presence in a virtual environment was introduced. This study also helped in the decision of which neuroimaging technique apply in the second part of the Thesis. EEG and fMRI were used for the measure of presence in the same virtual environments, and the results in terms of brain activations were compared. Presence was also measured by means of questionnaires, the traditional subjective way of measuring it. As a result of this study it is expected to check if VR could effectively stimulate presence and which neuroimaging technique is more appropriate for the targets of this Thesis. To sum up, the initial hypotheses of this Thesis are that: 1- The new neuroimaging techniques can provide of useful information to use during neuropsychotherapy. 2- Virtual reality would help in the assessment of the disorder, improving the accuracy in the way the subjects are exposed to the stimuli. 3- The environments used would be immersive enough so the patient will feel present in them and feel them as real. For fulfilling these objectives, each of the two courses of work (study of presence and assessment of a mental disorder) was divided in two parts. In total, four studies were developed: 1- Study of the sense of presence in a virtual environment using fMRI: the aim of this part of the Thesis was to check if the environments were able to stimulate the sense of presence, correlating the results with those given to questionnaires. 2- Study of the sense of presence in a virtual environment using EEG: the aim here was to compare the brain activations obtained with EEG with those from the previous study, and if the responses of the questionnaires were equivalent despite being in a less intrusive scanner. As a result of these two studies, it was decided that the environments were immersive enough to induce the sense of presence, and that the best neuroimaging technique for the next part of the Thesis was the fMRI, due to the higher spatial resolution it brought. 3- Assessment of a psychological disorder, pre-treatment: once decided the study will continue with fMRI, the areas related to a specific disorder (small animals¿ phobia) were studied using VR as stimulus. Until now, the assessment has been done using real animals as stimuli but not using VR, which here is hypothesized to allow a better approach to the phobic experience than the view of photographs or videos of real animals. 4- Assessment of the state of subjects with a psychological disorder, post-treatment: once the patients had underwent a treatment to cure the disorder, they were assessed again to check if the brain areas related to the phobia stopped being activated after it. As a result of this second part of the Thesis, the brain areas related to the phobia (that stopped being activated after the treatment) were obtained, and this information is hoped to be useful in future neuropsychotherapeutic works, for the better adjustment of the disorder. In conclusion, this PhD Thesis studies the advantages that the new neuroimaging techniques and virtual reality could bring to the study of neuropsychotherapy.Clemente Bellido, M. (2014). Contributions to Neuropsychotherapy of the Combined Use of Neuroimaging and Virtual Exposure for Assessment in Psychological Treatments [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/37234TESI

Augmented Reality

Augmented Reality (AR) is a natural development from virtual reality (VR), which was developed several decades earlier. AR complements VR in many ways. Due to the advantages of the user being able to see both the real and virtual objects simultaneously, AR is far more intuitive, but it's not completely detached from human factors and other restrictions. AR doesn't consume as much time and effort in the applications because it's not required to construct the entire virtual scene and the environment. In this book, several new and emerging application areas of AR are presented and divided into three sections. The first section contains applications in outdoor and mobile AR, such as construction, restoration, security and surveillance. The second section deals with AR in medical, biological, and human bodies. The third and final section contains a number of new and useful applications in daily living and learning

Human Health Engineering Volume II

In this Special Issue on “Human Health Engineering Volume II”, we invited submissions exploring recent contributions to the field of human health engineering, i.e., technology for monitoring the physical or mental health status of individuals in a variety of applications. Contributions could focus on sensors, wearable hardware, algorithms, or integrated monitoring systems. We organized the different papers according to their contributions to the main parts of the monitoring and control engineering scheme applied to human health applications, namely papers focusing on measuring/sensing physiological variables, papers highlighting health-monitoring applications, and examples of control and process management applications for human health. In comparison to biomedical engineering, we envision that the field of human health engineering will also cover applications for healthy humans (e.g., sports, sleep, and stress), and thus not only contribute to the development of technology for curing patients or supporting chronically ill people, but also to more general disease prevention and optimization of human well-being

Emotion and Stress Recognition Related Sensors and Machine Learning Technologies

This book includes impactful chapters which present scientific concepts, frameworks, architectures and ideas on sensing technologies and machine learning techniques. These are relevant in tackling the following challenges: (i) the field readiness and use of intrusive sensor systems and devices for capturing biosignals, including EEG sensor systems, ECG sensor systems and electrodermal activity sensor systems; (ii) the quality assessment and management of sensor data; (iii) data preprocessing, noise filtering and calibration concepts for biosignals; (iv) the field readiness and use of nonintrusive sensor technologies, including visual sensors, acoustic sensors, vibration sensors and piezoelectric sensors; (v) emotion recognition using mobile phones and smartwatches; (vi) body area sensor networks for emotion and stress studies; (vii) the use of experimental datasets in emotion recognition, including dataset generation principles and concepts, quality insurance and emotion elicitation material and concepts; (viii) machine learning techniques for robust emotion recognition, including graphical models, neural network methods, deep learning methods, statistical learning and multivariate empirical mode decomposition; (ix) subject-independent emotion and stress recognition concepts and systems, including facial expression-based systems, speech-based systems, EEG-based systems, ECG-based systems, electrodermal activity-based systems, multimodal recognition systems and sensor fusion concepts and (x) emotion and stress estimation and forecasting from a nonlinear dynamical system perspective