Electrodermal responses to discrete stimuli measured by skin conductance, skin potential, and skin susceptance

Task-state skin potential abnormalities can distinguish major depressive disorder and bipolar depression from healthy controls

Early detection of bipolar depression (BPD) and major depressive disorder (MDD) has been challenging due to the lack of reliable and easily measurable biological markers. This study aimed to investigate the accuracy of discriminating patients with mood disorders from healthy controls based on task state skin potential characteristics and their correlation with individual indicators of oxidative stress. A total of 77 patients with BPD, 53 patients with MDD, and 79 healthy controls were recruited. A custom-made device, previously shown to be sufficiently accurate, was used to collect skin potential data during six emotion-inducing tasks involving video, pictorial, or textual stimuli. Blood indicators reflecting individual levels of oxidative stress were collected. A discriminant model based on the support vector machine (SVM) algorithm was constructed for discriminant analysis. MDD and BPD patients were found to have abnormal skin potential characteristics on most tasks. The accuracy of the SVM model built with SP features to discriminate MDD patients from healthy controls was 78% (sensitivity 78%, specificity 82%). The SVM model gave an accuracy of 59% (sensitivity 59%, specificity 79%) in classifying BPD patients, MDD patients, and healthy controls into three groups. Significant correlations were also found between oxidative stress indicators in the blood of patients and certain SP features. Patients with depression and bipolar depression have abnormalities in task-state skin potential that partially reflect the pathological mechanism of the illness, and the abnormalities are potential biological markers of affective disorders.

Factors Affecting Workers' Mental Stress in Handover Activities During Human-Robot Collaboration

OBJECTIVE

This study investigated the effects of different approach directions, movement speeds, and trajectories of a co-robot's end-effector on workers' mental stress during handover tasks.

BACKGROUND

Human-robot collaboration (HRC) is gaining attention in industry and academia. Understanding robot-related factors causing mental stress is crucial for designing collaborative tasks that minimize workers' stress.

METHODS

Mental stress in HRC tasks was measured subjectively through self-reports and objectively through galvanic skin response (GSR) and electromyography (EMG). Robot-related factors including approach direction, movement speed, and trajectory were analyzed.

RESULTS

Movement speed and approach direction had significant effects on subjective ratings, EMG, and GSR. High-speed and approaching from one side consistently resulted in higher fear, lower comfort, and predictability, as well as increased EMG and GSR signals, indicating higher mental stress. Movement trajectory affected GSR, with the sudden stop condition eliciting a stronger response compared to the constrained trajectory. Interaction effects between speed and approach direction were observed for "surprise" and "predictability" subjective ratings. At high speed, approach direction did not significantly differ, but at low speeds, approaching from the side was found to be more surprising and unpredictable compared to approaching from the front.

CONCLUSION

The mental stress of workers during HRC is lower when the robot's end effector (1) approaches a worker within the worker's field of view, (2) approaches at a lower speed, or (3) follows a constrained trajectory.

APPLICATION

The outcome of this study can serve as a guide to design HRC tasks with a low level of workers' mental stress.

An Individualized Approach to Skin Conductance Assessment during Execution of Tasks of Different Complexities

Researchers use different approaches to analyze changes in skin conductance. At the same time, individual differences observed in both the initial values of skin conductance and response to stimuli do not allow comparing the responses of different subjects to the same impact. An individualized approach to the assessment of psycho-emotional stress has been developed using the real-time skin conductance index during continuous performance of a task with different levels of complexity. The participants, 18 second-year students at the actors' high school, performed a simple task (expressive reading aloud of a simple text) and a difficult task (expressive reading aloud of the text inverted 180°). During the task, the skin conductance in the participants was continuously recorded. We revealed a change in the parameters of skin conductivity depending on the complexity of the task, both in comparison with resting state (baseline) and with simple and complex stages of the study. However, the individual skin conduction curves in the subjects differed greatly. A method for assessing the individual differences in parameters of skin conductance was proposed based on ranking by categories of values during continuous performance of tasks with different levels of complexity. This method allows comparing the levels of cognitive load in participants with different initial levels of skin conductance due to transition from the absolute to relative values at time intervals that are important for the researcher.

Autonomic responses to pressure sensitivity of head, face and neck: Heart rate and skin conductance

Subjective scales are frequently used in the design process of head-related products to assess pressure discomfort. Nevertheless, some users lack fundamental cognitive and motor abilities (e.g., paralyzed patients). Therefore, it is vital to find non-verbal measurements of pressure discomfort and pressure pain. This study gathered the autonomic response data (heart rate and skin conductance) of 30 landmarks in head, neck and face from 31 participants experiencing pressure discomfort and pressure pain. The results indicate that pressure stimulation can change heart rate (HR) and skin conductance (SC). SC can be more useful in assessing pressure discomfort than HR for specific landmarks, and SC also possesses a faster arousal rate than HR. Moreover, HR decreased in response to pressure stimulation, while SC decreased followed by an increase. In comparisons between genders, the subjective pressure discomfort threshold (PDT) and pressure pain threshold (PPT) of women were lower than those of men, but men's autonomic responses (HR and SC) were more intense. Furthermore, there was no linear correlation between subjective pressure thresholds (PDT and PPT) and autonomic response intensity. This study has significant implications for resolving ergonomic issues (pressure discomfort and pain) associated with head-related products.

The Five Basic Human Senses Evoke Electrodermal Activity

Electrodermal activity (EDA) usually relates to variations in the electrical properties of palmar or plantar skin sites. EDA responses, namely skin conductance responses (SCRs), skin potential responses (SPRs) and skin susceptance responses (SSRs) are shown to be sensitive indexes of sympathetic nervous system activation and are studied in many research projects. However, the association between EDA responses and the five basic human senses has not been investigated yet. Our study aimed to explore the relationship between the three EDA responses (SCRs, SSRs and SPRs) and the five basic human senses. These three EDA responses were measured simultaneously at the same skin site on each of the 38 volunteers. The tested five senses were sight, hearing, touch, taste and smell. The results showed that the different tested senses led to different degrees of EDA responses due to activation of the sympathetic nervous system and corresponding secretion of sweat. Although a controlled study on the degree of EDA as a function of the strength of each stimulus was not performed, we noted that the largest EDA responses were typically associated with the smell sense test. We conclude that EDA responses could be utilized as measures for examining the sensitivity of the human senses. Hence, EDA devices may have important roles in sensory systems for future clinical applications.

Native and non-native language contexts differently modulate mood-driven electrodermal activity

Bilingual speakers have been consistently observed to experience reduced emotional sensitivity to their non-native (L2) relative to native (L1) language, particularly to the negatively-valenced L2 content. Yet, little is known about how the L1 and L2 contexts physiologically influence bilinguals' affective states, such as moods. Here, we show that bilinguals may be less physiologically sensitive to mood changes in the L2 compared to the L1 context. Polish-English bilinguals operating in either the L1 or the L2 mode (elicited via reading L1 and L2 sentences) watched positive and negative mood-inducing films while their electrodermal activity was measured. We observed a greater number of skin conductance responses in the negative compared to positive mood condition in the L1 context only, indexing decreased sensitivity to mood changes in the L2 relative to the L1 mode in bilinguals. Also, skin conductance amplitudes were overall increased in the L2 compared to the L1 context, pointing to increased cognitive load when operating in L2. These findings together suggest that bilinguals experience decreased sensitivity to mood changes in their less dominant language due to L2 processing requiring greater cognitive engagement.

Mental stress and safety awareness during human-robot collaboration - Review

Human-robot collaboration (HRC) is an emerging research area that has gained tremendous attention in both academia and industry. Yet, the feature that humans and robots sharing the workplace has led to safety concerns. In particular, the mental stress or safety awareness of human teammates during HRC remains unclear but is also of great importance to workplace safety. In this manuscript, we reviewed twenty-five studies for understanding the relationships between HRC and workers' mental stress or safety awareness. Specifically, we aimed to understand: (1) robot-related factors that may affect human workers' mental stress or safety awareness, (2) a number of measurements that could be used to evaluate workers' mental stress in HRC, and (3) various methods for measuring safety awareness that had been adopted or could be applied in HRC. According to our literature review, robot-related factors including robot characteristics, social touching and trajectory have relationships with workers' mental stress or safety awareness. For the measurement of mental stress and safety awareness, each method mentioned has its validity and rationality. Additionally, a discussion related to the potential co-robot actions to lower mental stress or improve safety awareness as well as future implications were provided.

Influence of ambient temperature on tonic and phasic electrodermal activity components

OBJECTIVE

Electrodermal Activity (EDA) is a reliable indicator for variations in the skin electrical properties attributed to sympathetic nerve system activity. EDA recordings can be influenced by various internal and external factors including environmental ones. Ambient temperature can be considered as one of the possible factors which might influence EDA recordings. Hence, this study aimed to precisely investigate influence of ambient temperature on tonic and phasic EDA components by employing a new EDA measurement technique, which depends on simultaneously recording of several EDA parameters.

APPROACH

Tonic and phasic EDA components during three different ambient temperature levels were recorded from 36 healthy participants. In addition, for evoking electrodermal responses, participants were exposed to cognitive, visual and breathing external stimuli.

MAIN RESULTS

Significant effects of temperature on tonic skin conductance (SC), skin susceptance (SS) and skin potential (SP) were obtained, whereas such significant effects were not observed with phasic SC, SS and SP. Tonic EDA parameters were increased as a function of temperature, but changes in phasic component were fluctuating.

SIGNIFICANCE

This should mean that, keeping recording of tonic EDA component in normal room temperature is highly crucial, but for recording or analysis of phasic component it is not important as they are more robust in this context. This is important in applications of EDA instruments, particularly in wearable devices where environmental temperature typically cannot be controlled.

Spirometry has added value over electrodermal activity as a physiological marker of mental load in male subjects

The objective distinction of different types of mental demands as well as their intensity is relevant for research and practical application but poses a challenge for established physiological methods. We investigated whether respiratory gases (oxygen uptake and carbon dioxide output) are suitable to distinguish between emotional stress and cognitive load. To this end, we compared the application of spirometry with an established procedure, namely electrodermal activity (EDA). Our results indicate that electrodermal activity shows a strong responsivity to emotional stress induction, which was highly correlated with its responsivity to cognitive load. Respiratory gases were both sensitive and specific to cognitive load and had the advantage of being predictive for cognitive performance as well as self-reported emotional state. These results support the notion that respiratory gases are a valuable complement to common physiological procedures in the detection and discrimination of different mental demands.

Analysis of Physiological Signals for Stress Recognition with Different Car Handling Setups

When designing a car, the vehicle dynamics and handling are important aspects, as they can satisfy a purpose in professional racing, as well as contributing to driving pleasure and safety, real and perceived, in regular drivers. In this paper, we focus on the assessment of the emotional response in drivers while they are driving on a track with different car handling setups. The experiments were performed using a dynamic professional simulator prearranged with different car setups. We recorded various physiological signals, allowing us to analyze the response of the drivers and analyze which car setup is more influential in terms of stress arising in the subjects. We logged two skin potential responses (SPRs), the electrocardiogram (ECG) signal, and eye tracking information. In the experiments, three car setups were used (neutral, understeering, and oversteering). To evaluate how these affect the drivers, we analyzed their physiological signals using two statistical tests (t-test and Wilcoxon test) and various machine learning (ML) algorithms. The results of the Wilcoxon test show that SPR signals provide higher statistical significance when evaluating stress among different drivers, compared to the ECG and eye tracking signals. As for the ML classifiers, we count the number of positive or “stress” labels of 15 s SPR time intervals for each subject and each particular car setup. With the support vector machine classifier, the mean value of the number of positive labels for the four subjects is equal to 13.13% for the base setup, 44.16% for the oversteering setup, and 39.60% for the understeering setup. In the end, our findings show that the base car setup appears to be the least stressful, and that our system enables us to effectively recognize stress while the subjects are driving in the different car configurations.

Current trends and opportunities in the methodology of electrodermal activity measurement

Electrodermal activity (EDA) has been measured in the laboratory since the late 1800s. Although the influence of sudomotor nerve activity and the sympathetic nervous system on EDA is well established, the mechanisms underlying EDA signal generation are not completely understood. Owing to simplicity of instrumentation and modern electronics, these measurements have recently seen a transfer from the laboratory to wearable devices, sparking numerous novel applications while bringing along both challenges and new opportunities. In addition to developments in electronics and miniaturization, current trends in material technology and manufacturing have sparked innovations in electrode technologies, and trends in data science such as machine learning and sensor fusion are expanding the ways that measurement data can be processed and utilized. Although challenges remain for the quality of wearable EDA measurement, ongoing research and developments may shorten the quality gap between wearable EDA and standardized recordings in the laboratory. In this topical review, we provide an overview of the basics of EDA measurement, discuss the challenges and opportunities of wearable EDA, and review recent developments in instrumentation, material technology, signal processing, modeling and data science tools that may advance the field of EDA research and applications over the coming years.

Exploring Physiological Signal Responses to Traffic-Related Stress in Simulated Driving

In this paper, we propose a relatively noninvasive system that can automatically assess the impact of traffic conditions on drivers. We analyze the physiological signals recorded from a set of individuals while driving in a simulated urban scenario in two different traffic scenarios, i.e., with traffic and without traffic. The experiments were carried out in a laboratory located at the University of Udine, employing a driving simulator equipped with a moving platform. We acquired two Skin Potential Response (SPR) signals from the hands of the drivers, and an electrocardiogram (ECG) signal from their chest. In the proposed scheme, the SPR signals are then processed through a Motion Artifact (MA) removal algorithm such that possible motion artifacts arising during the drive are reduced. An analysis considering the scalogram of the single cleaned SPR signal is presented. This signal, along with the ECG, is then fed to various Machine Learning (ML) algorithms. More specifically, some statistical features are extracted from each signal segment which, after being analyzed through a binary ML model, are labeled as corresponding to a stressful situation or not. Our results confirm the applicability of the proposed approach to identify stress in the two scenarios. This is also in accordance with our findings considering the SPR signal scalograms.

Evaluation of tractor driving vibration fatigue based on multiple physiological parameters

The vibration generated by tractor field operations will seriously affect the comfort and health of the driver. The low frequency vibration generated by the engine and ground excitation is similar to the natural frequency of human organs. Long term operation in this environment will resonate with the organs and affect drivers’ health. To investigate this possibility, in this paper we carried out a collection experiment of human physiological indicators relevant to vibration fatigue. Four physiological signals of surface electromyography, skin electricity, skin temperature, and photoplethysmography signal were collected while the subjects experienced vibration. Several features of physiological signals as well as the law of signal features changing with fatigue are studied. The test results show that with the increase of human fatigue, the overall physiological parameters show the following trends: The median frequency of the human body surface electromyography and the slope of skin surface temperature decreases, the value of skin conductivity and the mean value of the photoplethysmography signal increases. Furthermore, this paper proposes a vibration comfort evaluation method based on multiple physiological parameters of the human body. An artificial neural network model is trained with test samples, and the prediction accuracy rate reaches 88.9%. Finally, the vibration conditions are changed by the shock-absorbing suspension of a tractor, verifying the effectiveness of the physiological signal changing with the vibration of the human body. The established prediction model can also be used to objectively reflect the discomfort of the human body under different working conditions and provide a basis for structural design optimization.

Elementary integrate-and-fire process underlies pulse amplitudes in Electrodermal activity

Electrodermal activity (EDA) is a direct read-out of sweat-induced changes in the skin’s electrical conductance. Sympathetically-mediated pulsatile changes in skin sweat measured as EDA resemble an integrate-and-fire process, which yields an inverse Gaussian model as the inter-pulse interval distribution. We have previously showed that the inter-pulse intervals in EDA follow an inverse Gaussian distribution. However, the statistical structure of EDA pulse amplitudes has not yet been characterized based on the physiology. Expanding upon the integrate-and-fire nature of sweat glands, we hypothesized that the amplitude of an EDA pulse is proportional to the excess volume of sweat produced compared to what is required to just reach the surface of the skin. We modeled this as the difference of two inverse Gaussian models for each pulse, one which represents the time required to produce just enough sweat to rise to the surface of the skin and one which represents the time requires to produce the actual volume of sweat. We proposed and tested a series of four simplifications of our hypothesis, ranging from a single difference of inverse Gaussians to a single simple inverse Gaussian. We also tested four additional models for comparison, including the lognormal and gamma distributions. All models were tested on EDA data from two subject cohorts, 11 healthy volunteers during 1 hour of quiet wakefulness and a different set of 11 healthy volunteers during approximately 3 hours of controlled propofol sedation. All four models which represent simplifications of our hypothesis outperformed other models across all 22 subjects, as measured by Akaike’s Information Criterion (AIC), as well as mean and maximum distance from the diagonal on a quantile-quantile plot. Our broader model set of four simplifications offered a useful framework to enhance further statistical descriptions of EDA pulse amplitudes. Some of the simplifications prioritize fit near the mode of the distribution, while others prioritize fit near the tail. With this new insight, we can summarize the physiologically-relevant amplitude information in EDA with at most four parameters. Our findings establish that physiologically based probability models provide parsimonious and accurate description of temporal and amplitude characteristics in EDA.

Electrodermal activity (EDA) is an indirect read-out of the body’s sympathetic nervous system, or fight-or-flight response, measured as sweat-induced changes in the electrical conductance properties of the skin. Interest is growing in using EDA to track physiological conditions such as stress levels, sleep quality, and emotional states. Our previous worked showed that the times in between EDA pulses obeyed a specific statistical distribution, the inverse Gaussian, that arises from the physiology of EDA production. In this work, we build on that insight to analyze the amplitudes of EDA pulses. In an analysis of EDA data recorded in 11 healthy volunteers during quiet wakefulness and 11 different healthy volunteers during controlled propofol sedation, we establish that the amplitudes of EDA pulses also have specific statistical structure, as the differences of inverse Gaussians, that arises from the physiology of sweat production. We capture that structure using a series of progressively simpler models that each prioritize different parts of the pulse amplitude distribution. Our findings show that a physiologically-based statistical model provides a parsimonious and accurate description of EDA. This enables increased reliability and robustness in analyzing EDA data collected under any circumstance.

Altered Autonomic Functions and Gut Microbiome in Individuals with Autism Spectrum Disorder (ASD): Implications for Assisting ASD Screening and Diagnosis

Autism spectrum disorder (ASD) is a complex neurological and developmental disorder, and a growing body of literature suggests the presence of autonomic nervous system (ANS) dysfunction in individuals with ASD. ANS is part of the "gut brain axis", which consists of an intricate interplay between the gut microbiome, mucosal immune system, enteric nervous system, ANS, and central processes receiving input from the vagus nerve. Measurements of the gut microbiome and the autonomic indices can serve as non-invasive markers of the status of the gut-brain axis in ASD. To our knowledge, no previous studies have explored the relationship between ANS and gut microbiome in individuals with ASD. Furthermore, while previous studies investigated the use of autonomic indices and gut microbiome independently as markers of ASD-related comorbidities, such as anxiety, cardiovascular issues, and gastrointestinal dysfunction, the use of combined autonomic indices and gut microbiome factors to classify ASD and control subjects has not been explored. In this study, we characterized autonomic function of a group of individuals with ASD in comparison to their paired, first-degree relative controls. Second, we explored the ASD gut-brain-axis through the relationship between gut microbiome markers and autonomic indices, as well as the correlation between the gut-brain-axis and clinical presentation of ASD. Lastly, this study explores the predictive capability of gut-brain-axis biomarkers (including autonomic and microbiome indices) in subtyping ASD cases, serving as a starting point to investigate the possibility of assisting in ASD screening and diagnosis that still heavily relies on psychological testing, which may be based on highly subjective standards.

The correlations among the skin conductance features responding to physiological stress stimuli

BACKGROUND/AIM

The skin conductance responses (SCRs) are a well-accepted indicator of physiological arousal for both research purposes and clinical approaches. The shape of SCRs is analyzed by various features. However, the estimation of how much (in %) one feature can explain another is still an open issue. The aim of this study was to assess whether variation in one SCR feature predicts changes in other features.

METHODS

Skin conductance (SC) was measured during relaxation and mental stress in 40 subjects. SCRs were induced by three external stimuli, which were deep breath, a mental arithmetic, task and a visual task.

RESULTS

The findings of this study showed that about 55% (R²  = 0.55) of the variation in the half recovery time (SCRs_rec 50%) can be explained by the rise time (SCRs_ris), whereas variation in amplitude of the skin conductance responses (SCRs_amp) and the skin conductance level (SCL) is independent and cannot be explained by the other features, as R² values obtained from all analyses among these SCR features in average were lower 0.19.

CONCLUSIONS

The study results suggest that the two timing phases (SCRs_rec and SCRs_ris) are not completely independent from each other, although they might be governed by different sweating mechanisms (secretion and reabsorption). However, SCRs_amp and SCL were independent. These findings can help in choosing the optimal set of features of an automated system for processing EDA, which reflect the alterations in the activation level generated during an emotional episode.

Car Driver's Sympathetic Reaction Detection Through Electrodermal Activity and Electrocardiogram Measurements

OBJECTIVE

in this paper we propose a system to detect a subject's sympathetic reaction, which is related to unexpected or challenging events during a car drive.

METHODS

we use the Electrocardiogram (ECG) signal and the Skin Potential Response (SPR) signal, which has several advantages with respect to other Electrodermal (EDA) signals. We record one SPR signal for each hand, and use an algorithm that, selecting the smoother signal, is able to remove motion artifacts. We extract statistical features from the ECG and SPR signals in order to classify signal segments and identify the presence or absence of emotional events via a Supervised Learning Algorithm. The experiments were carried out in a company which specializes in driving simulator equipment, using a motorized platform and a driving simulator. Different subjects were tested with this setup, with different challenging events happening on predetermined locations on the track.

RESULTS

we obtain an Accuracy as high as 79.10% for signal blocks and as high as 91.27% for events.

CONCLUSION

results demonstrate the good performance of the presented system in detecting sympathetic reactions, and the effectiveness of the motion artifact removal procedure.

SIGNIFICANCE

our work demonstrates the possibility to classify the emotional state of the driver, using the ECG and EDA signals and a slightly invasive setup. In particular, the proposed use of SPR and of the motion artifact removal procedure are crucial for the effectiveness of the system.

Simultaneous measurement of electrodermal activity components correlated with age-related differences

Electrodermal activity (EDA) measurements are influenced by various factors. Age-related psychological and physiological changes may be considered as one of the possible factors which may influence EDA measurements. In order to properly investigate the effects of such factors on EDA, techniques of precisely and simultaneously recording more than one EDA parameter are recommended. This study aims to explore the impact of age-related differences on EDA components through employing a new measuring technique, which is composed of a small front-end electronic box, DAQ card, and a laptop running LabVIEW software. It is dependent on the simultaneous recording of three EDA parameters: skin conductance (SC), skin potential (SP), and skin susceptance (SS) at the same skin site. EDA components as results of breathing, mathematical tasks, and image stimuli were recorded from 60 healthy participants simultaneously at the same skin site. They were categorized by age into young adults (ages 18-25), middle-aged adults (ages 30-40), and old adults (ages 50-70) years. It was found that skin potential responses (SPRs), and skin conductance level (SCL) (p < 0.001), were significantly decreased due to aging, but changes in other EDA parameters were nonsignificant (p > 0.05). Moreover, both tonic and phasic SS were the least affected and found to be more robust than SC and SP with respect to aging. The study suggests that it is important to take age into account in research studies where the mean aim of the study is to compare EDA parameters; however, in the meantime, the results from our small number and specific study population cannot be generalized to clinical applications.

Wireless Sensors System for Stress Detection by Means of ECG and EDA Acquisition

This paper describes the design of a two channels electrodermal activity (EDA) sensor and two channels electrocardiogram (ECG) sensor. The EDA sensors acquire data on the hands and transmit them to the ECG sensor with wireless WiFi communication for increased wearability. The sensors system acquires two EDA channels to improve the removal of motion artifacts that take place if EDA is measured on individuals who need to move their hands in their activities. The ECG channels are acquired on the chest and the ECG sensor is responsible for aligning the two ECG traces with the received packets from EDA sensors; the ECG sensor sends via WiFi the aligned packets to a laptop for real time plot and data storage. The metrological characterization showed high-level performances in terms of linearity and jitter; the delays introduced by the wireless transmission from EDA to ECG sensor have been proved to be negligible for the present application.

Innovations in Electrodermal Activity Data Collection and Signal Processing: A Systematic Review

The electrodermal activity (EDA) signal is an electrical manifestation of the sympathetic innervation of the sweat glands. EDA has a history in psychophysiological (including emotional or cognitive stress) research since 1879, but it was not until recent years that researchers began using EDA for pathophysiological applications like the assessment of fatigue, pain, sleepiness, exercise recovery, diagnosis of epilepsy, neuropathies, depression, and so forth. The advent of new devices and applications for EDA has increased the development of novel signal processing techniques, creating a growing pool of measures derived mathematically from the EDA. For many years, simply computing the mean of EDA values over a period was used to assess arousal. Much later, researchers found that EDA contains information not only in the slow changes (tonic component) that the mean value represents, but also in the rapid or phasic changes of the signal. The techniques that have ensued have intended to provide a more sophisticated analysis of EDA, beyond the traditional tonic/phasic decomposition of the signal. With many researchers from the social sciences, engineering, medicine, and other areas recently working with EDA, it is timely to summarize and review the recent developments and provide an updated and synthesized framework for all researchers interested in incorporating EDA into their research.

Psychological Correlates of Nonspecific Electrodermal Responses

Spontaneous fluctuations in electrodermal responses are known as nonspecific electrodermal responses (NS.EDRs). The use of NS.EDRs as a tool in applied psychophysiological research has resulted in a variety of publications. NS.EDRs are examined separately as associated with the (as a biomarker of) levels of anxiety. The aim of this study was to compare changes (in terms of amplitude, frequency and time components) in NS.EDRs at two different (pre and post of an external stimulus) resting phases. NS.EDRs (nonspecific skin conductance responses (NS.SCRs), nonspecific skin potential responses (NS.SPRs), and nonspecific skin susceptance responses (NS.SSRs)) were recorded from 50 apparently healthy volunteers simultaneously at the same skin area. They were scored as NS.SCRs and NS.SSRs for changes greater than 0.02 μS and NS.SPRs greater than 0.02 mV. It was found that NS.EDRs, in particular NS.SCRs and NS.SPRs, were significantly changed in the second resting period, following the specific stimulus. More specifically, the amplitude of NS.EDRs were significantly decreased for NS.SCRs (p<0.001) and for NS.SPRs (p<0.005), but NS.SSRs remained stable. Moreover, the rise time of NS.SCRs was decreased in the second resting time. Furthermore, the frequency of responses was also changed. The computed NS.EDRs, in particular NS.SCRs and NS.SPRs could be of psychological interest and be used to study the electrodermal responses in detail. NS.SSRs were found to be robust with respect to nonspecific stimuli at various relaxation periods and their role was found to be less important in analysis of NS.EDRs in comparison to NS.SCRs and NS.SPRs at low frequency (20 Hz AC current). This should be considered in analysis of NS.EDRs. The computed NS.EDRs, especially NS.SCRs and NS.SPRs may be used as a useful measure of arousal due to their fast response and sensitivity to nonspecific stimuli and may also be used in assessment of individual differences.

A Circuit for Simultaneous Measurements of Skin Electrical Conductance, Susceptance, and Potential

A circuit is presented that enables measurement of skin electrical conductance, susceptance, and potential simultaneously beneath the same monopolar electrode. Example measurements are shown to confirm the function of the circuit. The measurements are also in accordance with earlier findings that changes in skin conductance and potential do not always correspond and hence contain unique information.

EEG and autonomic responses to nociceptive stimulation in disorders of consciousness

Since behavioral responses to external stimuli of patients presenting disorders of consciousness (DoC) are often difficult to qualify, covert physiological correlates of responsivity are deemed as potentially valuable tools to help assessment procedures. While noxious stimuli seem good candidates to explore DoC patients' responsivity, autonomic and electrophysiological correlates of pain detection in DoC patients are still debated. This research aims at investigating autonomic and cortical activation as covert measure of residual somatosensory and nociceptive processes in patients in vegetative state. Twenty-one patients received touch- and pain-related stimulations while autonomic and cortical measures were recorded, with minimal stress for them. Results showed an increased frontal and parietal activation in response to both touch and pain stimuli. Pain-related stimulation was however associated with greater delta parietal response, lower left frontal activation, and increased electrodermal and heart rate measures. Present findings suggest that both somatic stimulations could induce measurable central responses, which might mirror basic attention orientation and perceptual processes. Nonetheless, the nociceptive stimulation in particular seemed to induce a more consistent and informative pattern of covert response even if we used a mild pain-induction procedure.

Electrodermal Activity Responses for Quantitative Assessment of Felt Pain

Accurate assessment of experienced pain is a well-known problem in the clinical practices. Therefore, a proper method for pain detection is highly desirable. Electrodermal activity (EDA) is known as a measure of the sympathetic nervous system activity, which changes during various mental stresses. As pain causes mental stress, EDA measures may reflect the felt pain. This study aims to evaluate changes in skin conductance responses (SCRs), skin potential responses (SPRs), and skin susceptance responses (SSRs) simultaneously as a result of sequences of electrical (painful) stimuli with different intensities. EDA responses as results of painful stimuli were recorded from 40 healthy volunteers. The stimuli with three different intensities were produced by using an electrical stimulator. EDA responses significantly changed (increased) with respect to the intensity of the stimuli. Both SCRs and SSRs showed linear relationship with the painful stimuli. It was found that the EDA responses, particularly SCRs (p < 0.001) and SSRs (p = 0.001) were linearly affected by the intensity of the painful stimuli. EDA responses, in particular SCRs, may be used as a useful indicator for assessment of experienced pain in clinical settings.