Automated Pain Assessment using Electrodermal Activity Data and Machine Learning

Objective pain assessment is required for appropriate pain management in the clinical setting. However, clinical gold standard pain assessment is based on subjective methods. Automated pain detection from physiological data may provide important objective information to better standardize pain assessment. Specifically, electrodermal activity (EDA) can identify features of stress and anxiety induced by varying pain levels. However, notable variability in EDA measurement exists and research to date has demonstrated sensitivity but lack of specificity in pain assessment. In this paper, we use timescale decomposition (TSD) to extract salient features from EDA signals to identify an accurate and automated EDA pain detection algorithm to sensitively and specifically distinguish pain from no-pain conditions.

Different brain networks mediate the effects of social and conditioned expectations on pain

Information about others' experiences can strongly influence our own feelings and decisions. But how does such social information affect the neural generation of affective experience, and are the brain mechanisms involved distinct from those that mediate other types of expectation effects? Here, we used fMRI to dissociate the brain mediators of social influence and associative learning effects on pain. Participants viewed symbolic depictions of other participants' pain ratings (social information) and classically conditioned pain-predictive cues before experiencing painful heat. Social information and conditioned stimuli each had significant effects on pain ratings, and both effects were mediated by self-reported expectations. Yet, these effects were mediated by largely separable brain activity patterns, involving different large-scale functional networks. These results show that learned versus socially instructed expectations modulate pain via partially different mechanisms-a distinction that should be accounted for by theories of predictive coding and related top-down influences.

Modeling Hierarchical Versus Random Exposure Schedules in Pavlovian Fear Extinction: No Evidence for Differential Fear Outcomes

In exposure therapy, the client can either be confronted with the fear-eliciting situations in a hierarchical way or in a random way. In the current study we developed a procedure to investigate the effects of hierarchical versus random exposure on long-term fear responding in the laboratory. Using a fear conditioning procedure, one stimulus (CS+) was paired with an electric shock (US), whereas another stimulus was not paired with the shock (CS-). The next day, participants underwent extinction training including presentations of the CS-, CS+ and a series of morphed stimuli between the CS- and CS+. In the hierarchical extinction condition (HE; N = 32), participants were first presented with the CS-, subsequently with the morph most similar to the CS-, then with the morph most similar to that one, and so forth, until reaching the CS+. In the random extinction condition (RE; N = 32), the same stimuli were presented but in a random order. Fear responding to the CS+, CS- and a new generalization stimulus (GS) was measured on the third day. Higher expectancy violation, t(62) = -2.67, p = .01, physiological arousal, t(62) = -2.08, p = .04, and variability in US-expectancy ratings, t(62) = -2.25, p = .03, were observed in the RE condition compared to the HE condition, suggesting the validity of this novel procedure. However, no differences between the RE and HE condition were found in fear responding as tested one day later, F(1, 62) < 1. In conclusion, we did not find evidence for differential long-term fear responding in modeling hierarchical versus random exposure in Pavlovian fear extinction.

The Added Value of Studying Embodied Responses in Couple Therapy Research: A Case Study

This article reports on the added value of embodied responses identified through sympathetic nervous system (SNS) activity in couple therapy research. It focuses on moments of change and the timing of therapeutic interventions or therapeutic moves in a couple therapy session. The data for this single-case study comprise couple therapy process videotapes recorded in a multi-camera setting, and measurements of participants' SNS activity. The voluntary participants were a marital couple in their late thirties and two middle-aged male psychotherapists. The division into topic segments showed how the key issue of seeking help, which was found to comprise three separate components, was repeatedly dealt with in the session. SNS activity showed different degrees of synchronization between the couple, between the therapists, and between the couple and therapists during the dialogue pertaining to these three components. The issue of timing emerged as a complex, even ambivalent, phenomenon. Arousal in the therapists was in line with their therapeutic activity, whereas in the clients it was more anticipatory. The approach used here rendered visible some of the intensity that therapeutic dialogue can generate when dealing with issues of relationship change in the couple context and showed how this intensity can be dialogically regulated in the therapeutic system.

Can verbal suggestions strengthen the effects of a relaxation intervention?

Short stress management interventions such as relaxation therapy have demonstrated preliminary effectiveness in reducing stress-related problems. A promising tool to strengthen the effectiveness of relaxation-based interventions is the use of verbal suggestions, as previous research provided evidence that verbal suggestions can induce positive outcome expectancies, facilitate adaptive responses to stress and improve health outcomes. The present experimental proof-of-concept study aimed to investigate the effects of a brief relaxation intervention and specifically the role of verbal suggestions on stress-related outcomes assessed by self-report questionnaires and psychophysiological data. 120 participants (mean age = 22.1 years) were randomized to one of four intervention conditions: a brief relaxation intervention plus verbal suggestions condition, a brief relaxation intervention only condition, a verbal suggestions only condition, and a control condition. Afterwards, participants were subjected to a psychosocial stress challenge to assess reactivity to a stressful event. Immediately after both relaxation interventions (with and without verbal suggestions), lower self-reported state anxiety was found compared to the control condition, but no differences were observed in response to the stressor. The verbal suggestions only condition did not impact state anxiety. No significant effects were found for verbal suggestion interventions on cortisol, alpha amylase, heart rate and skin conductance. This is the first study investigating the role of verbal suggestions in the effectiveness of a brief relaxation intervention. Although this experimental proof-of-concept study provides support for the effectiveness of a brief relaxation intervention in lowering state anxiety directly after the intervention, the effects did not impact the response to a subsequent stressor and we did not observe any evidence for the add-on effectiveness of verbal suggestions. The effectiveness of brief relaxation interventions on stress responses should be investigated further in future research by incorporating interventions that are tailored to the specific stress challenge and various types of verbal suggestions.

Influence of Anatomical Model and Skin Conductivity on the Electric Field Induced in the Head by Transcranial Magnetic Stimulation

Numerical evaluation of the electromagnetic (EM) quantities induced inside the brain during transcranial magnetic stimulation (TMS) applications is a fundamental step to obtain the optimization of the treatment in terms of coil position and current intensity. In this sense, the human head model considered and the electromagnetic properties used to characterize the tissues have an influence on the EM solution. Thus, the aim of this study is to evaluate how different skin conductivities and different computational head models, i.e. the ViP Duke and the MIDA, influence the electric field induced inside the brain by a typical TMS coil.

A Sensor-enabled Digital Trier Social Stress Test in an Enterprise Context

The Trier Social Stress Test (TSST) protocol is a widely accepted method of inducing social and/or cognitive stress in participants and studying its effects. Traditionally, this protocol is administered in laboratory or university settings, which are less formal than in offices. In this paper, we report the results of the analysis of multi-modal sensor data collected from employees of an enterprise who underwent the test. We briefly discuss the adaptations that enabled administering it digitally in a semi-automatic mode with minimal researcher/test-administrator intervention. In our setup, noninvasive sensor-signals, including the Galvanic Skin Response and Photoplethysmogram, were collected during and outside the stress-inducing tasks. We analyze the data collected from twenty participants and show that the State Trait Anxiety Inventory (STAI) score is needed in assessing the effect of the digital version of the TSST. A support vector machine classifier yielded an F₁ score of 0.723 with the STAI score taken as ground truth. We also introduce the idea of ground truth based on the change in the STAI scores to reduce variation due to subjective interpretation, for which an F₁ score of 0.847 was obtained.

Parental criticism and behavior problems in children with autism spectrum disorder

Associations between parent critical attitudes (a component of the Expressed Emotion construct) and behavior problems have been relatively well established in adolescents and young adults with autism spectrum disorder, but use of systems adapted for children with autism spectrum disorder and additional investigations with younger samples are needed. This study examined parental criticism, derived from a population-specific coding system, as related to behavior problems in children with autism spectrum disorder between the ages of 4 and 11 years, and considered parental warmth and children's psychophysiological reactivity as statistical moderators of these associations. In all, 40 children with autism spectrum disorder and their primary caregivers attended a visit involving collection of child electrodermal activity, parent-child interaction, a parent interview from which critical attitudes and warmth were coded, and parent report of child behavior problems. Criticism was directly related to higher child externalizing but not internalizing problems. Parental criticism interacted with warmth in the prediction of internalizing problems such that criticism was only associated with more problems in the context of moderate but not high warmth. Criticism was positively associated with externalizing problems under conditions of moderate and high, but not low, child electrodermal activity reactivity. Implications for conceptualizations of parental criticism in autism spectrum disorder, for understanding comorbid behavior problems in this population, and for intervention are discussed.

Effects of Virtual Reality and Augmented Reality on Induced Anxiety

To explore the effects of virtual reality (VR) and augmented reality (AR) in the treatment of claustrophobia, the potential effects of VR and AR on induced anxiety were investigated in this paper. During the experiment, 34 subjects were randomly selected and distributed in AR and VR scenes in a sequence. The skin conductance and heart rates of the subjects were measured throughout the entire process, and the anxiety scale was used to assess the subjective anxiety when the task in each scene was completed. The results showed the following: (1) AR and VR scenes led to feelings of discomfort, but the subjective anxiety scores obtained in the two scenes were not significantly different; (2) the skin conductance level of the subjects significantly increased from the baseline when the subjects entered the experimental scene but remained active in the two scenes without showing significant difference between the scenes; and (3) the heart rate index significantly increased from the baseline after the subjects entered the scene and then gradually decreased. The heart rates of the subjects significantly increased again when the anxiety-induced event was triggered. However, no significant difference was observed between AR and VR scenes. AR and VR have induced obvious anxiety, which was reflected in the subjective and objective physiological indicators. However, no significant difference was found in the effects of AR and VR on the induced anxiety. Considering the cost of building two scenes and other factors, AR was more suitable for the treatment of claustrophobia than VR.

Acute pain intensity monitoring with the classification of multiple physiological parameters

Current acute pain intensity assessment tools are mainly based on self-reporting by patients, which is impractical for non-communicative, sedated or critically ill patients. In previous studies, various physiological signals have been observed qualitatively as a potential pain intensity index. On the basis of that, this study aims at developing a continuous pain monitoring method with the classification of multiple physiological parameters. Heart rate (HR), breath rate (BR), galvanic skin response (GSR) and facial surface electromyogram were collected from 30 healthy volunteers under thermal and electrical pain stimuli. The collected samples were labelled as no pain, mild pain or moderate/severe pain based on a self-reported visual analogue scale. The patterns of these three classes were first observed from the distribution of the 13 processed physiological parameters. Then, artificial neural network classifiers were trained, validated and tested with the physiological parameters. The average classification accuracy was 70.6%. The same method was applied to the medians of each class in each test and accuracy was improved to 83.3%. With facial electromyogram, the adaptivity of this method to a new subject was improved as the recognition accuracy of moderate/severe pain in leave-one-subject-out cross-validation was promoted from 74.9 ± 21.0 to 76.3 ± 18.1%. Among healthy volunteers, GSR, HR and BR were better correlated to pain intensity variations than facial muscle activities. The classification of multiple accessible physiological parameters can potentially provide a way to differentiate among no, mild and moderate/severe acute experimental pain.

Physiological Arousal Quantifying Perception of Safe and Unsafe Virtual Environments by Older and Younger Adults

Physiological arousal has been increasingly applied to monitor exploration (or navigation) of a virtual environment (VE), especially when the VE is designed to evoke an anxiety-related response. The present work aims to evaluate human physiological reactions to safe and unsafe VEs. We compared the effect of the presence of handrails in the VE in two different samples, young and older adults, through self-reports and physiological data: Electrodermal activation (EDA) and electrocardiogram (ECG) sensors. After navigation, self-report questionnaires were administered. We found that the VEs evoked a clearly differentiated perception of safety and unsafety demonstrated through self-reports, with older adults being more discriminative in their responses and reporting a higher sense of presence. In terms of physiological data, the effect of handrails did not provoke significant differences in arousal. Safety was better operationalized by discriminating neutral/non-neutral spaces, where the reaction of older adults was more pronounced than young adults. Results serve as a basis for orienting future experiments in the line of VE and applied physiology usage in the architectural spaces design process. This specific work also provided a basis for the development of applications that integrate virtual reality and applied biofeedback, tapping into mobility and ageing.

Design and Implementation of an Ultra-Low Resource Electrodermal Activity Sensor for Wearable Applications ‡

While modern low-power microcontrollers are a cornerstone of wearable physiological sensors, their limited on-chip storage typically makes peripheral storage devices a requirement for long-term physiological sensing—significantly increasing both size and power consumption. Here, a wearable biosensor system capable of long-term recording of physiological signals using a single, 64 kB microcontroller to minimize sensor size and improve energy performance is described. Electrodermal (EDA) signals were sampled and compressed using a multiresolution wavelet transformation to achieve long-term storage within the limited memory of a 16-bit microcontroller. The distortion of the compressed signal and errors in extracting common EDA features is evaluated across 253 independent EDA signals acquired from human volunteers. At a compression ratio (CR) of 23.3×, the root mean square error (RMSErr) is below 0.016 μS and the percent root-mean-square difference (PRD) is below 1%. Tonic EDA features are preserved at a CR = 23.3× while phasic EDA features are more prone to reconstruction errors at CRs > 8.8×. This compression method is shown to be competitive with other compressive sensing-based approaches for EDA measurement while enabling on-board access to raw EDA data and efficient signal reconstructions. The system and compression method provided improves the functionality of low-resource microcontrollers by limiting the need for external memory devices and wireless connectivity to advance the miniaturization of wearable biosensors for mobile applications.

Amygdala and prefrontal cortex activity varies with individual differences in the emotional response to psychosocial stress

Stress elicits a variety of psychophysiological responses that show large interindividual variability. Determining the neural mechanisms that mediate individual differences in the emotional response to stress would provide new insight that would have important implications for understanding stress-related disorders. Therefore, the present study examined individual differences in the relationship between brain activity and the emotional response to stress. In the largest stress study to date, 239 participants completed the Montreal Imaging Stress Task (MIST) while heart rate, skin conductance response (SCR), cortisol, self-reported stress, and blood oxygen level dependent (BOLD) functional MRI (fMRI) signal responses were measured. The relationship between differential responses (heart rate, SCR, cortisol, and self-reported stress) and differential BOLD fMRI data was analyzed. Dorsolateral prefrontal cortex (PFC), dorsomedial PFC, ventromedial PFC, and amygdala activity varied with the behavioral response (i.e., SCR and self-reported stress). These results suggest the PFC and amygdala support processes that are important for the expression and regulation of the emotional response to stress, and that stress-related PFC and amygdala activity underlie interindividual variability in peripheral physiologic measures of the stress response. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Psychophysiological Responses to Subliminal Auditory Suggestions for Activation,

The aim of this study was to characterize further the experimental procedure proposed by Borgeat and Goulet in 1983. Subliminal activation auditory suggestions were expected to increase heart rate and skin conductance in presence of a stressing task. 20 subjects were alternately exposed to activating or neutral (random numbers) 25-dB suggestions masked by a 40-dB white noise. Analyses of variance and covariance indicated an effect of the activating suggestions on heart rate but not on skin conductance. Partly confirming previous results, the data support the reliability of heart rate and the importance of a stressing factor to reveal the effects of preconscious or subliminal stimulations.

The relative impact of smartwatch and smartphone use while driving on workload, attention, and driving performance

The impact of using a smartwatch to initiate phone calls on driver workload, attention, and performance was compared to smartphone visual-manual (VM) and auditory-vocal (AV) interfaces. In a driving simulator, 36 participants placed calls using each method. While task time and number of glances were greater for AV calling on the smartwatch vs. smartphone, remote detection task (R-DRT) responsiveness, mean single glance duration, percentage of long duration off-road glances, total off-road glance time, and percent time looking off-road were similar; the later metrics were all significantly higher for the VM interface vs. AV methods. Heart rate and skin conductance were higher during phone calling tasks than "just driving", but did not consistently differentiate calling method. Participants exhibited more erratic driving behavior (lane position and major steering wheel reversals) for smartphone VM calling compared to both AV methods. Workload ratings were lower for AV calling on both devices vs. VM calling.

A Physiological Sensor-Based Android Application Synchronized with a Driving Simulator for Driver Monitoring

In this paper, we present an Android application to control and monitor the physiological sensors from the Shimmer platform and its synchronized working with a driving simulator. The Android app can monitor drivers and their parameters can be used to analyze the relation between their physiological states and driving performance. The app can configure, select, receive, process, represent graphically, and store the signals from electrocardiogram (ECG), electromyogram (EMG) and galvanic skin response (GSR) modules and accelerometers, a magnetometer and a gyroscope. The Android app is synchronized in two steps with a driving simulator that we previously developed using the Unity game engine to analyze driving security and efficiency. The Android app was tested with different sensors working simultaneously at various sampling rates and in different Android devices. We also tested the synchronized working of the driving simulator and the Android app with 25 people and analyzed the relation between data from the ECG, EMG, GSR, and gyroscope sensors and from the simulator. Among others, some significant correlations between a gyroscope-based feature calculated by the Android app and vehicle data and particular traffic offences were found. The Android app can be applied with minor adaptations to other different users such as patients with chronic diseases or athletes.

Sympathetic responding to unconditioned stimuli predicts subsequent threat expectancy, orienting, and visuocortical bias in human aversive Pavlovian conditioning

Threat expectancy is the ability to predict an aversive outcome. What is not known is the influence of initial threat responding on the acquisition of verbal, attentional and perceptual biases towards conditioned threat cues. This study evaluated the extent to which initial unconditioned stimulus (UCS) responding was related to trial-by-trial self-reported expectancy, sensory processing (visuocortical EEG) and orienting (heart rate deceleration) to threat cues during extinction learning. Participants (n = 38) viewed oriented Gabor gratings, associated with the presence (CS+) or absence (CS-) of a 96 dB white noise (UCS), flickering at 12 Hz to elicit steady state visually evoked potentials (ssVEPs). Multivariate multiple regression revealed greater initial UCS skin conductance responding to predict extinction responding: enhanced visuocortical discrimination, greater heart rate deceleration to CS+, and greater threat expectancy endorsements. These results suggest that the motivational intensity of initial threat reactivity (sympathetic UCS responding) drives learning-induced defensive dispositions across multiple response systems.

Emotion Recognition Using Electrodermal Activity Signals and Multiscale Deep Convolution Neural Network

Automated emotion recognition plays a vital role in problem solving, decision making and social activities of human life. An emotion is a set of reactions and experience to a given conditions, which are modeled as a linear combination of arousal and valence dimensions. Emotional pattern recognition based on physiological signals is a relatively new and fast growing area of research. Several physiological signals such as ECG, EEG, and EMG have been used for emotion recognition. Analysis of Electrodermal Activity (EDA) signals is one of the popular technique for emotion state analysis. In this work, an attempt is made to discriminate arousal-valence dimensions using EDA signals and multiscale one dimensional convolution neural network (MCNN). For this, EDA signals are obtained from publically available online DEAP database. These signals are normalized using channel normalization and subjected to MCNN for event-related robust features and classification. K-fold cross validation is used to investigate the performance of classifier. The result shows that the MCNN are able to discriminate the emotional states in arousal/valence dimensions. The proposed approach obtained an overall classification accuracy of 83.75% and 81.25% for arousal and valence scale, respectively. The network yields better classification performance for arousal scale then valence diemension. This might be due to the fact that arousal represent the intensity of emotions. The result also show that the proposed approach is better than the conventional hand-crafted feature based approach. Thus, it appears that the proposed approach can be used to differentiate autonomic and clinical conditions.

Psychosocial stress reactivity is associated with decreased whole-brain network efficiency and increased amygdala centrality

Cognitive and emotional functions are supported by the coordinated activity of a distributed network of brain regions. This coordinated activity may be disrupted by psychosocial stress, resulting in the dysfunction of cognitive and emotional processes. Graph theory is a mathematical approach to assess coordinated brain activity that can estimate the efficiency of information flow and determine the centrality of brain regions within a larger distributed neural network. However, limited research has applied graph-theory techniques to the study of stress. Advancing our understanding of the impact stress has on global brain networks may provide new insight into factors that influence individual differences in stress susceptibility. Therefore, the present study examined the brain connectivity of participants that completed the Montreal Imaging Stress Task (Goodman et al., 2016; Wheelock et al., 2016). Salivary cortisol, heart rate, skin conductance response, and self-reported stress served as indices of stress, and trait anxiety served as an index of participant's disposition toward negative affectivity. Psychosocial stress was associated with a decrease in the efficiency of the flow of information within the brain. Further, the centrality of brain regions that mediate emotion regulation processes (i.e., hippocampus, ventral prefrontal cortex, and cingulate cortex) decreased during stress exposure. Interestingly, individual differences in cortisol reactivity were negatively correlated with the efficiency of information flow within this network, whereas cortisol reactivity was positively correlated with the centrality of the amygdala within the network. These findings suggest that stress reduces the efficiency of information transfer and leaves the function of brain regions that regulate the stress response vulnerable to disruption. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Emotion perception and overconfidence in errors under stress in psychosis

Vulnerability stress models are well-accepted in psychosis research, but the mechanisms that link stress to psychotic symptoms remain vague. Little is known about how social cognition and overconfidence in errors, two putative mechanisms for the pathogenesis of delusions, relate to stress. Using a repeated measures design, we tested four groups (N=120) with different liability to psychosis (schizophrenia patients [n=35], first-degree relatives [n=24], participants with attenuated positive symptoms [n=19] and healthy controls [n=28]) and depression patients (n=14) as a clinical control group under three randomized experimental conditions (no stress, noise and social stress). Parallel versions of the Emotion Perception and Confidence Task, which taps both emotion perception and confidence, were used in each condition. We recorded subjective stress, heart rate, skin conductance level and salivary cortisol to assess the stress response across different dimensions. Independent of the stress condition, patients with schizophrenia showed poorer emotion perception performance and higher confidence in emotion perception errors than participants with attenuated positive symptoms and healthy controls. However, they did not differ from patients with depression or first-degree relatives. Stress did not influence emotion perception or the extent of high-confident errors, but patients with schizophrenia showed an increase in high-confident emotion perception errors conditional on higher arousal. A possible clinical implication of our findings is the necessity to provide stress management programs that aim to reduce arousal. Moreover, patients with schizophrenia might benefit from interventions that help them to reduce overconfidence in their social cognition judgements in times in which they feel being under pressure.

Into the Wild: The Challenges of Physiological Stress Detection in Laboratory and Ambulatory Settings

Stress and mental health have become major concerns worldwide. Research has already extensively investigated physiological signals as quantitative and continuous markers of stress. In recent years, the focus of the field has shifted from the laboratory to the ambulatory environment. We provide an overview of physiological stress detection in laboratory settings with a focus on identifying physiological sensing priorities, including electrocardiogram, skin conductance, and electromyogram, and the most suitable machine learning techniques, of which the choice depends on the context of the application. Additionally, an overview is given of new challenges ahead to move toward the ambulant environment, including the influence of physical activity, lower signal quality due to motion artifacts, the lack of a stress reference, and the subject-dependent nature of the physiological stress response. Finally, several recommendations for future research are listed, focusing on large-scale, longitudinal trials across different population groups and just-in-time interventions to move toward disease prevention and interception.

Eliminating Individual Bias to Improve Stress Detection from Multimodal Physiological Data

Stress monitoring is important for mental wellbeing and early detection of related disorders. The current work is focused on stress detection from multiple non-invasive physiological signals like Electroencephalogram (EEG), Photoplethysmogram (PPG) and Galvanic Skin Response (GSR). We show that, compared to using only the well known EEG band powers in different frequencies for stress detection, an early fusion with GSR and PPG features shows a significant improvement. Maximum Relevance Minimum Redundancy (mRMR) based feature selection is used to identify the most suitable physiological features correlating with stress. A major contribution of this work lies in eliminating subject-specific bias to improve the classification accuracy. We use self-reported values of Valence, Arousal and Dominance to cluster subjects and build separate classification models specific to clusters. The proposed approach is validated on a publicly available dataset comprising 146 data instances from 10 subjects. The performances of Leave-One- Subject-Out cross validation (LOSOCV) in terms of mean Fscores are 0.61 using EEG features only, 0.64 using early fusion of EEG, GSR and PPG features and 0.69 by applying our clustering technique before fusion and classification.

Vomit Comet Physiology: Autonomic Changes in Novice Flyers

This exploratory study examined the effects of varying g-forces, including feelings of weightlessness, on an individual's physiology during parabolic flight. Specifically, we collected heart rate, accelerometer, and skin conductance measurements from 16 flyers aboard a parabolic flight using wearable, wireless sensors. The biosignals were then correlated to participant reports of nausea, anxiety, and excitement during periods of altered g-forces. Using linear mixed-effects models, we found that (1) heart rate was positively correlated to individuals' self-reported highest/lowest periods of both anxiety and excitement, and (2) bilateral skin conductance asymmetry was positively correlated to individuals' self-reported highest/lowest periods of nausea.

Multi-modal Approach for Affective Computing

Throughout the past decade, many studies have classified human emotions using only a single sensing modality such as face video, electroencephalogram (EEG), electrocardiogram (ECG), galvanic skin response (GSR), etc. The results of these studies are constrained by the limitations of these modalities such as the absence of physiological biomarkers in the face-video analysis, poor spatial resolution in EEG, poor temporal resolution of the GSR etc. Scant research has been conducted to compare the merits of these modalities and understand how to best use them individually and jointly. Using multi-modal AMIGOS dataset, this study compares the performance of human emotion classification using multiple computational approaches applied to face videos and various bio-sensing modalities. Using a novel method for compensating physiological baseline we show an increase in the classification accuracy of various approaches that we use. Finally, we present a multi-modal emotion-classification approach in the domain of affective computing research.

Physiological Responses of the Youth Viewing a Japanese Garden

Previous studies have demonstrated that exposure to a Japanese garden is a non-pharmacological measure to improve the behavioral symptoms of elderly people with dementia, and that Japanese gardens are significantly more effective than other environments. However, it is not clear whether Japanese gardens have similar effects in the young. To address this open question, we measured the physiological responses of university students when viewing a Japanese garden, and compared them to the same students' responses when viewing a control space. We measured three physiological indicators of autonomous nervous system (ANS) activity: the electrocardiograph (ECG), the blood volume pulse (BVP) and the galvanic skin response (GSR). Our results suggest that the Japanese garden does not have as calming an effect on younger subjects as observed previously in elderly subjects. However, students did respond more positively to the Japanese garden than to an unstructured space. Ambient temperature was found to be a critical factor affecting heart rate and heart rate variability, but not other measures.

Unraveling current and future adolescent depressive symptoms: The role of stress reactivity across physiological systems

Neurobiological processes are highlighted in animal and theoretical models of the development of depression, but there is mixed empirical evidence about associations between stress physiology and depressive symptoms. Adolescence has been highlighted as a period during which coordination across physiological stress response systems may be particularly important. However, most studies have focused on depressive symptoms and physiological reactivity in isolated systems. The goal of this study was to examine associations of hypothalamic-pituitary-adrenal (HPA) axis and autonomic nervous system (ANS; i.e., sympathetic and parasympathetic nervous system [SNS and PNS, respectively]) reactivity with depressive systems, as well as the interrelatedness of reactivity across systems. Participants were adolescents (n = 153, 10-17 years) from diverse backgrounds, recruited from the community. Adolescents experienced a stressor, during which cortisol (HPA axis), skin conductance level (SCL; SNS), and respiratory sinus arrhythmia (RSA; PNS) were measured; youth also reported depressive symptoms. Some youth (n = 60) reported depressive symptoms again 1 year later as part of another study. Results from latent growth analysis embedded in a structural equation model (SEM) indicated that concurrent depressive symptoms were predicted by an interaction between cortisol reactivity and baseline RSA levels, with fewer symptoms for adolescents who had lower baseline RSA and greater cortisol reactivity. Controlling for concurrent depressive symptoms, prolonged cortisol recovery (above and beyond cortisol or ANS reactivity), was related to prospective depressive symptoms. Results support and extend theoretical arguments about the role of dysregulated stress physiology in the development of depressive symptoms, and the importance of multisystem approaches to understanding the role of stress physiology in risk and resilience. (PsycINFO Database Record

Mental workload is reflected in driver behaviour, physiology, eye movements and prefrontal cortex activation

Mental workload is an important factor during driving, as both high and low levels may result in driver error. This research examined the mental workload of drivers caused by changes in road environment and how such changes impact upon behaviour, physiological responses, eye movements and brain activity. The experiment used functional near infrared spectroscopy to record prefrontal cortex activation associated with changes in mental workload during simulated driving. Increases in subjective ratings of mental workload caused by changes in road type were accompanied by increases in skin conductance, acceleration signatures and horizontal spread of search. Such changes were also associated with increases in the concentration of oxygenated haemoglobin in the prefrontal cortex. Mental workload fluctuates during driving. Such changes can be identified using a range of measures which could be used to inform the development of in-vehicle devices and partially autonomous systems.

[Anxiety and depressive symptoms in epilepsy in the context of defense mechanisms and electrodermal activity]

Depressive and anxiety disorders among people with epilepsy are more common than in general population and they are associated with less efficient emotion regulation and reduced quality of life. Unfortunately, these disorders are not always correctly diagnosed or treated. Some studies suggest that the electrodermal activity may serve as a marker for depression.

AIM

The aim of the study was to measure and compare depressive and anxiety symptoms, defense mechanisms and electrodermal activity in response to cognitive stimulation in patients with epilepsy with the control group, and to test the correlations between symptoms of anxiety and depression, defense mechanisms and the electrodermal activity.

MATERIALS AND METHODS

64 patients diagnosed with epilepsy and 66 people from the control group were assessed with following psychological questionnaires: State-Trait Anxiety Inventory, Beck Depression Inventory, Defense Styles Questionnaire 40. MindLAB Set was used to measure electrodermal activity.

RESULTS

The study showed that people with epilepsy tend to have increased levels of anxiety and depressive symptoms compared with the control group. Patients also tend to use neurotic defense mechanisms what may be associated with poorer emotion regulation. Electrodermal activity was lower among people with epilepsy after cognitive stimulation. There was no statistically significant correlation between electrodermal activity, anxiety and depressive symptoms.

CONCLUSIONS

The results indicate the need for assessment of anxiety, depressive symptoms and types of defense mechanisms among patients with epilepsy, as appropriate psychotherapeutic and/or pharmacological intervention could significantly improve the quality of life of these patients.

Multimodal Ambulatory Sleep Detection Using LSTM Recurrent Neural Networks

Unobtrusive and accurate ambulatory methods are needed to monitor long-term sleep patterns for improving health. Previously developed ambulatory sleep detection methods rely either in whole or in part on self-reported diary data as ground truth, which is a problem, since people often do not fill them out accurately. This paper presents an algorithm that uses multimodal data from smartphones and wearable technologies to detect sleep/wake state and sleep onset/offset using a type of recurrent neural network with long-short-term memory (LSTM) cells for synthesizing temporal information. We collected 5580 days of multimodal data from 186 participants and compared the new method for sleep/wake classification and sleep onset/offset detection to, first, nontemporal machine learning methods and, second, a state-of-the-art actigraphy software. The new LSTM method achieved a sleep/wake classification accuracy of 96.5%, and sleep onset/offset detection F₁ scores of 0.86 and 0.84, respectively, with mean absolute errors of 5.0 and 5.5 min, res-pectively, when compared with sleep/wake state and sleep onset/offset assessed using actigraphy and sleep diaries. The LSTM results were statistically superior to those from nontemporal machine learning algorithms and the actigraphy software. We show good generalization of the new algorithm by comparing participant-dependent and participant-independent models, and we show how to make the model nearly realtime with slightly reduced performance.

On the Feasibility of Low-Cost Wearable Sensors for Multi-Modal Biometric Verification

Biometric systems designed on wearable technology have substantial differences from traditional biometric systems. Due to their wearable nature, they generally capture noisier signals and can only be trained with signals belonging to the device user (biometric verification). In this article, we assess the feasibility of using low-cost wearable sensors—photoplethysmogram (PPG), electrocardiogram (ECG), accelerometer (ACC), and galvanic skin response (GSR)—for biometric verification. We present a prototype, built with low-cost wearable sensors, that was used to capture data from 25 subjects while seated (at resting state), walking, and seated (after a gentle stroll). We used this data to evaluate how the different combinations of signals affected the biometric verification process. Our results showed that the low-cost sensors currently being embedded in many fitness bands and smart-watches can be combined to enable biometric verification. We report and compare the results obtained by all tested configurations. Our best configuration, which uses ECG, PPG and GSR, obtained 0.99 area under the curve and 0.02 equal error rate with only 60 s of training data. We have made our dataset public so that our work can be compared with proposals developed by other researchers.

Modeling and Quantification of Impact of Psychological Factors on Rehabilitation of Stroke Patients

The brain damage could lead to the loss of the central nervous system, so a stroke patient may lose the function of dominating his/her body. The rehabilitation aims to maximize the potential to restore a patient who has an impairment. Traditional rehabilitation is to train a patient's muscles and joints under the guidance of doctors to improve the strength of muscles and restore the motor function of joints. However, stroke patients are usually depressed, lonely, and irritable, and they might easily generate negative emotions during a rehabilitation process. With a sole goal of helping patients restore their body functions from the physiology perspective, the traditional rehabilitation took little consideration on the impact of rehabilitation, which is reflected and measured from the perspective of emotions. Therefore, we suggest adding affective regulation to the stroke rehabilitation; in such a way, the patients' exercise could be completed with high intrinsic motivation, and the performance of the rehabilitation process can be enhanced. Two main contributions in the presented works are: 1) the expanded emotional model to represent the status of stroke patients where the impact of psychological factors can be taken into consideration and 2) the quantifiable measurement of rehabilitation performance as well as the corresponding design of experiments to verify the positive impact of psychological adjustment on human subjects. Note that due to the limited conditions, the experimental verification was performed on healthy college students. Since our work focused on modeling and quantification of psychological factors, it is reasonable to expend our work to other human subjects including stoke patients.

Development of a Novel Wearable Ring-Shaped Biosensor

We report on the preliminary results obtained out of a wearable module designed to be encompassed within a ring-shaped system aimed at providing healthcare services. The module is composed of two sensors for the measuring of Galvanic Skin Response (GSR) and Heart Rate Variability (HRV). A first device validation was carried out by involving four subjects who were asked to perform tasks providing different stress-related statuses. A comparison of physiological parameters measured by the module with those measured by a commercial HRV-GSR sensor chosen as gold standard was made. Two out of the three HRV parameters and all of the GSR parameters measured with the module resulted consistent (mostly differing less than 10%) with the same parameters measured by the gold standard. The work reported in this paper set a milestone for the realization of a system exploiting sensor fusion to provide active ageing, stress detection, activity recognition and e-health services has been achieved.

What determines drivers' speed? A replication of three behavioural adaptation experiments in a single driving simulator study

We conceptually replicated three highly cited experiments on speed adaptation, by measuring drivers' experienced risk (galvanic skin response; GSR), experienced task difficulty (self-reported task effort; SRTE) and safety margins (time-to-line-crossing; TLC) in a single experiment. The three measures were compared using a nonparametric index that captures the criteria of constancy during self-paced driving and sensitivity during forced-paced driving. In a driving simulator, 24 participants completed two forced-paced and one self-paced run. Each run held four different lane width conditions. Results showed that participants drove faster on wider lanes, thus confirming the expected speed adaptation. None of the three measures offered persuasive evidence for speed adaptation because they failed either the sensitivity criterion (GSR) or the constancy criterion (TLC, SRTE). An additional measure, steering reversal rate, outperformed the other three measures regarding sensitivity and constancy, prompting a further evaluation of the role of control activity in speed adaptation. Practitioner Summary: Results from a driving simulator experiment suggest that it is not experienced risk, experienced effort or safety margins that govern drivers' choice of speed. Rather, our findings suggest that steering reversal rate has an explanatory role in speed adaptation.

Wearable Devices in Clinical Trials: Hype and Hypothesis

The development of innovative wearable technologies has raised great interest in new means of data collection in healthcare and biopharmaceutical research and development. Multiple applications for wearables have been identified in a number of therapeutic areas; however, researchers face many challenges in the clinic, including scientific methodology as well as regulatory, legal, and operational hurdles. To facilitate further evaluation and adoption of these technologies, we highlight methodological and logistical considerations for implementation in clinical trials, including key elements of analytical and clinical validation in the specific context of use (COU). Additionally, we provide an assessment of the maturity of the field and successful examples of recent clinical experiments.

Frontoparietal processing of stress-relevant information differs in individuals with a negative cognitive style

Prior research indicates that cognitive vulnerabilities can render individuals more susceptible to psychopathology in the wake of stressful events. However, little work has directly targeted the neural mechanisms involved. In this study, we examined functional magnetic resonance imaging (fMRI) activity as a function of negative cognitive style, a well-studied cognitive vulnerability for depression. We adapted a robust paradigm in which undergraduate students completed fMRI testing after a known ecologically valid stressor (a midterm exam). Negative cognitive style correlated with brain activity in response to both negative and exam-related information in dorsolateral prefrontal cortex and/or angular gyrus, both regions involved in abstract, self-referential thought. There were commonalities and differences in patterns of activity, suggesting that these individuals may process domain-general and domain-specific negative information in different ways but drawing upon a common frontoparietal network. This study, thus, identifies a potential brain network associated with negative cognitive style, and enhances our understanding of neural mechanisms of cognitive vulnerability to psychopathology. (PsycINFO Database Record

One-stop microvascular screening service: an effective model for the early detection of diabetic peripheral neuropathy and the high-risk foot

AIMS

To evaluate the feasibility of a one-stop microvascular screening service for the early diagnosis of diabetic distal symmetrical polyneuropathy, painful distal symmetrical polyneuropathy and the at-risk diabetic foot.

METHODS

People with diabetes attending retinal screening in hospital and community settings had their feet examined by a podiatrist. Assessment included: Toronto Clinical Neuropathy Score evaluation; a 10-g monofilament test; and two validated, objective and quick measures of neuropathy obtained using the point-of-care devices 'DPN-Check', a hand-held device that measures sural nerve conduction velocity and amplitude, and 'Sudoscan', a device that measures sudomotor function. The diagnostic utility of these devices was assessed against the Toronto Clinical Neuropathy Score as the 'gold standard'.

RESULTS

A total of 236 consecutive people attending the retinal screening service, 18.9% of whom had never previously had their feet examined, were evaluated. The prevalence of distal symmetrical polyneuropathy, assessed using the Toronto Clinical Neuropathy Score, was 30.9%, and was underestimated by 10-g monofilament test (14.4%). The prevalence of distal symmetrical polyneuropathy using DPN-check was 51.5% (84.3% sensitivity, 68.3% specificity), 38.2% using Sudoscan foot electrochemical skin conductance (77.4% sensitivity, 68.3% specificity), and 61.9% using abnormality in either of the results (93.2% sensitivity, 52.8% specificity). The results of both devices correlated with Toronto Clinical Neuropathy Score (P<0.001). A new diagnosis of painful distal symmetrical polyneuropathy was made in 59 participants (25%), and 56.6% had moderate- or high-risk foot. Participants rated the service very highly.

CONCLUSIONS

Combined, eye, foot and renal screening is feasible, has a high uptake, reduces clinic visits, and identifies painful distal symmetrical polyneuropathy and the at-risk foot. Combined large- and small-nerve-fibre assessment using non-invasive, quantitative and quick point-of-care devices may be an effective model for the early diagnosis of distal symmetrical polyneuropathy.

Emotional ratings and skin conductance response to visual, auditory and haptic stimuli

The human emotional reactions to stimuli delivered by different sensory modalities is a topic of interest for many disciplines, from Human-Computer-Interaction to cognitive sciences. Different databases of stimuli eliciting emotional reaction are available, tested on a high number of participants. Interestingly, stimuli within one database are always of the same type. In other words, to date, no data was obtained and compared from distinct types of emotion-eliciting stimuli from the same participant. This makes it difficult to use different databases within the same experiment, limiting the complexity of experiments investigating emotional reactions. Moreover, whereas the stimuli and the participants' rating to the stimuli are available, physiological reactions of participants to the emotional stimuli are often recorded but not shared. Here, we test stimuli delivered either through a visual, auditory, or haptic modality in a within participant experimental design. We provide the results of our study in the form of a MATLAB structure including basic demographics on the participants, the participant's self-assessment of his/her emotional state, and his/her physiological reactions (i.e., skin conductance).

Muscle fatigue assessment through electrodermal activity analysis during isometric contraction

We studied the effects of muscle fatigue on the Autonomic Nervous System (ANS) dynamics. Specifically, we monitored the electrodermal activity (EDA) on 32 healthy subjects performing isometric biceps contraction. As assessed by means of an electromyography (EMG) analysis, 15 subjects showed muscle fatigue and 17 did not. EDA signals were analyzed using the recently proposed cvxEDA model in order to decompose them into their phasic and tonic components and extract effective features to study ANS dynamics. A statistical comparison between the two groups of subjects was performed. Results revealed that relevant phasic EDA features significantly increased in the fatigued group. Moreover, a pattern recognition system was applied to the EDA dataset in order to automatically discriminate between fatigued and non-fatigued subjects. The proposed leave-one-subject-out KNN classifier showed an accuracy of 75.69%. These results suggest the use of EDA as correlate of muscle fatigue, providing integrative information to the standard indices extracted from the EMG signals.

Differential effects of physical and psychological stressors on electrodermal activity

Stress being labelled by WHO as "the health epidemic of 21^st century" need to be treated as a clarion call for devising strategies that aim at its early detection, for the reason that stress is the cause as well as the catalyst for several chronic human health disorders. The work reported here in is a progression towards the development of a stress detection system based on the electrodermal activity (EDA) in humans, which can further be incorporated into a wearable vital signs monitor. The utility of EDA as a potential physiological measure for classifying physical and psychological stressors is analyzed in this paper. A group of 12 subjects (8 males and 4 females, age: 25.4 ± 3.1 years, mean ± SD) volunteered to participate in a laboratory stress task that included a psychological stressor close to real life work stress scenario and a physical stressor. The capability of stressors to elicit persistent stress response was validated by assessing variations in salivary cortisol levels. EDA was monitored throughout the experiment sessions as a measure of sympathetic activation in subjects. Six classification models were investigated concerning their usability to distinguish physical and psychological stressors based on EDA. A maximum accuracy of 95.1% was achieved using linear discriminat analysis (LDA) based classifier which imply that EDA is indeed a potential discriminate measure to classify physical and psychological stress responses. Furthermore, the best feature combination for maximum classification accuracy was also determined.

Classification of BCI Users Based on Cognition

Brain-Computer Interfaces (BCI) are systems originally developed to assist paralyzed patients allowing for commands to the computer with brain activities. This study aims to examine cognitive state with an objective, easy-to-use, and easy-to-interpret method utilizing Brain-Computer Interface systems. Seventy healthy participants completed six tasks using a Brain-Computer Interface system and participants' pupil dilation, blink rate, and Galvanic Skin Response (GSR) data were collected simultaneously. Participants filled Nasa-TLX forms following each task and task performances of participants were also measured. Cognitive state clusters were created from the data collected using the K-means method. Taking these clusters and task performances into account, the general cognitive state of each participant was classified as low risk or high risk. Logistic Regression, Decision Tree, and Neural Networks were also used to classify the same data in order to measure the consistency of this classification with other techniques and the method provided a consistency between 87.1% and 100% with other techniques.

Preliminary evidence for physiological markers of implicit memory

The Concealed Information Test (CIT) aims to detect concealed knowledge and is known to be sensitive to explicit memory. In two experiments, we examined whether the CIT is also sensitive to implicit memory using skin conductance, respiration and heart rate measures. For each participant, previously studied items were either categorized as explicitly remembered, implicitly remembered or forgotten. The two experiments differed in the strength of memory encoding, the type of implicit memory test, the delay between study and test and the number of critical CIT items. The results of Experiment 1 revealed that CIT detection efficiency was weak and significant only in the explicit memory condition. In Experiment 2, however, CIT detection efficiency was stronger and significant in both the explicit and implicit memory conditions as indexed by skin conductance and respiration. Altogether, our results provide initial evidence that the CIT may be sensitive to implicit memory. Theoretical and practical implications are discussed.

Model- based filtering for artifact and noise suppression with state estimation for electrodermal activity measurements in real time

Measurement of electrodermal activity (EDA) has recently made a transition from the laboratory into daily life with the emergence of wearable devices. Movement and nongelled electrodes make these devices more susceptible to noise and artifacts. In addition, real-time interpretation of the measurement is needed for user feedback. The Kalman filter approach may conveniently deal with both these issues. This paper presents a biophysical model for EDA implemented in an extended Kalman filter. Employing the filter on data from Physionet along with simulated noise and artifacts demonstrates noise and artifact suppression while implicitly providing estimates of model states and parameters such as the sudomotor nerve activation.

Peripheral neuropathy in patients with multiple sclerosis

OBJECTIVES

To determine the prevalence and severity of neuropathic pain, sudomotor dysfunction and abnormal vibration perception in patients with MS.

METHODS

73 patients with MS and 32 age-matched healthy controls underwent assessment of expanded disability severity score (EDSS), DN4 to assess neuropathic pain, electrochemical skin conductance (ESC) to assess sudomotor function and vibration perception threshold (VPT).

RESULTS

Patients with MS had a higher DN4 score (p < 0.001) with 14% fulfilling the criteria for neuropathic pain elevated VPT (p < 0.001) and lower ESC on the feet (p < 0.001) and hands (p < 0.001) compared to control participants. ESC on the feet (32% of MS patients) and hands (30% of MS patients) were lower, and DN4 (77% of MS patients) and VPT (64% of MS patients) were greater than 2SD of the healthy control values, respectively. EDSS correlated with the number of relapses (r = 0.564, p < 0.001), VPT (r = -0.457, < 0.001) and ESC on the feet (r = -0.268, p = 0.023).

CONCLUSIONS

Patients with multiple sclerosis have evidence of sudomotor dysfunction and elevated vibration perception, which were associated with neurological disability from MS.

Generalization of learned pain modulation depends on explicit learning

The experience of pain is strongly influenced by contextual and socio-affective factors, including learning from previous experiences. Pain is typically perceived as more intense when preceded by a conditioned cue (CS_HIGH) that has previously been associated with higher pain intensities, compared to cues associated with lower intensities (CS_LOW). In three studies (total N=134), we tested whether this learned pain modulation generalizes to perceptually similar cues (Studies 1 and 2) and conceptually similar cues (Study 3). The results showed that participants report higher pain when heat stimulation was preceded by novel stimuli that were either perceptually (Studies 1 and 2) or conceptually (Study 3) similar to the previously conditioned CS_HIGH. In all three studies, the strength of this generalization effect was strongly correlated with individual differences in explicitly learned expectations. Together, these findings suggest an important role of conscious expectations and higher-order conceptual inference during generalization of learned pain modulation. We discuss implications for the understanding of placebo and nocebo effects as well as for chronic pain and anxiety.

Contributions of Observed Parent Socialization of Coping and Skin Conductance Level Reactivity to Childhood Adjustment

This research examined the longitudinal association between parent socialization of coping and child adjustment, as well as the moderating role of children's skin conductance level reactivity (SCLR). Participants were a community sample of children (n = 64, M age = 9.02, 54.5% females, 93.2% Caucasian) and their parent(s). Parent coping suggestions were observed while their child engaged in a stressful challenge task, during which the child's SCLR, a measure of children's physiological reactivity to stress, was also measured. Parent(s) completed the Child Behavior Checklist (Achenbach & Rescorla, 2001) at baseline and a 6-month follow-up to assess internalizing and externalizing problems. Results revealed that secondary control engagement suggestions predicted fewer internalizing problems over time. In addition, disengagement suggestions predicted fewer externalizing problems over time among children with high SCLR. This study provides evidence that parent coping suggestions serve as a resource that protects youth from developing adjustment problems.

The effects of exercise and passive heating on the sweat glands ion reabsorption rates

The sweat glands maximum ion reabsorption rates were investigated (n = 12, 21.7 ± 3.0 years, 59.4 ± 9.8 kg, 166.9 ± 10.4 cm and 47.1 ± 7.5 mL/kg/min) during two separate endogenous protocols; cycling at 30% (LEX) and 60% VO2max (MEX) and one exogenous trial; passive heating (PH) (43°C water lower leg immersion) in 27°C, 50%RH. Oesophageal temperature (Tes ), skin temperature (Tsk ), and forearm, chest and lower back sweat rate (SR) and galvanic skin conductance (GSC) were measured. Salivary aldosterone was measured pre-and postheating (n = 3). Using the ∆SR threshold for an increasing ∆GSC to identify maximum sweat ion reabsorption rate revealed higher reabsorption rates during MEX compared to PH (mean of all regions: 0.63 ± 0.28 vs. 0.44 ± 0.3 mg/cm2 /min, P < 0.05). It was not possible to identify the ion reabsorption rate during LEX for some participants. Tes and mean Tsk were different between conditions but mean body temperature (Tb ) and local Tsk (forearm, chest and back) were similar (P > 0.05). Aldosterone increased more during MEX (72.8 ± 36.6 pg/mL) compared to PH (39.2 ± 17.5 pg/mL) and LEX (1.8 ± 9.7 pg/mL). The back had a higher threshold than the forearm (P < 0.05) but it was similar to the chest (P > 0.05) (mean of all conditions; 0.64 ± 0.33, 0.42 ± 0.25, 0.54 ± 0.3 mg/cm2 /min, respectively). Although the differences between conditions may be influenced by thermal or nonthermal mechanism, our results indicate a possibility that the sweat glands maximum ion reabsorption rates may be different between exercise and passive heating without mediating skin regional differences.

Adaptation and Conditioning of the Galvanic Skin Response in Psychiatric Patients

There is a considerable literature dealing with the relation of anxiety to conditioning performance in human subjects. When compared with normal subjects, those with marked anxiety have been observed to show more rapid conditioning and slower extinction of certain responses. Typical observations have been those of Taylor (17) concerning conditioned eyelid responses, and of Welch (20), and Bitterman and Holtzman (3), concerning the galvanic skin response. In contrast, Bindra et al. (2) found no difference in the conditioning of salivary responses between anxious and non-anxious subjects.

Galvanic Skin Response Studies of Sex Responsiveness in Sex Offenders and Others

The assessment of sex responsiveness is a recurring problem in the field of conduct disorders and psychopathy, particularly when it is desirable to determine the effectiveness of therapy on the behaviour of the sex offender. Previous studies have indicated certain test differences in emotional disturbance and stress reactivity in subjects of known delinquent history, but it has been observed that sex responsiveness may be an additional (separate) factor to consider for the patient who is a known sex offender (19, 20, 21, 22).

Wearable Driver Distraction Identification On-The-Road via Continuous Decomposition of Galvanic Skin Responses

One of the main reasons for fatal accidents on the road is distracted driving. The continuous attention of an individual driver is a necessity for the task of driving. While driving, certain levels of distraction can cause drivers to lose their attention, which might lead to an accident. Thus, the number of accidents can be reduced by early detection of distraction. Many studies have been conducted to automatically detect driver distraction. Although camera-based techniques have been successfully employed to characterize driver distraction, the risk of privacy violation is high. On the other hand, physiological signals have shown to be a privacy preserving and reliable indicator of driver state, while the acquisition technology might be intrusive to drivers in practical implementation. In this study, we investigate a continuous measure of phasic Galvanic Skin Responses (GSR) using a wristband wearable to identify distraction of drivers during a driving experiment on-the-road. We first decompose the raw GSR signal into its phasic and tonic components using Continuous Decomposition Analysis (CDA), and then the continuous phasic component containing relevant characteristics of the skin conductance signals is investigated for further analysis. We generated a high resolution spectro-temporal transformation of the GSR signals for non-distracted and distracted (calling and texting) scenarios to visualize the associated behavior of the decomposed phasic GSR signal in correlation with distracted scenarios. According to the spectrogram observations, we extract relevant spectral and temporal features to capture the patterns associated with the distracted scenarios at the physiological level. We then performed feature selection using support vector machine recursive feature elimination (SVM-RFE) in order to: (1) generate a rank of the distinguishing features among the subject population, and (2) create a reduced feature subset toward more efficient distraction identification on the edge at the generalization phase. We employed support vector machine (SVM) to generate the 10-fold cross validation (10-CV) identification performance measures. Our experimental results demonstrated cross-validation accuracy of 94.81% using all the features and the accuracy of 93.01% using reduced feature space. The SVM-RFE selected set of features generated a marginal decrease in accuracy while reducing the redundancy in the input feature space toward shorter response time necessary for early notification of distracted state of the driver.

Patients' autonomic activation during clinical interaction: A review of empirical studies

OBJECTIVE

To investigate how patients' autonomic responses are related to verbal or non-verbal communication during clinical encounters.

METHODS

The SCOPUS database was searched to identify papers. Studies were included if measures of autonomic arousal were related to patients' emotions or patient-clinician interaction during clinical consultations such as psychotherapy, counseling or medical interviews. The search was conducted according to PRISMA criteria. The included studies were assessed using the 16 item quality assessment tool QATSDD.

RESULTS

A total of 24 publications were identified. The studies varied greatly in design and quality. However, a few trends could be observed across studies. Patients' expressions of emotions were associated with significant autonomic arousal. Clinician behavior affected arousal levels; and in a few studies, a patient centered way of presenting information was found to attenuate arousal level, interpreted as stress reduction. There was a general, but not consistent, trend in the reduction of arousal level over time within the consultation. Examples of individual differences in autonomic responses were found.

CONCLUSION AND PRACTICE IMPLICATIONS

Increased awareness of potential impact of clinician behavior on patient' arousal level may be helpful for clinicians, in particular how different communication styles may augment or attenuate arousal in response to stressors.