Skin Conductance Research Articles

A Review on the Use of Physiological Signals for Assessing Postoperative Pain

The assessment of pain intensity after surgery is important for guiding pain management. Due to the limitations of current pain evaluation tools, there is increasing interest in using objective methods to assess pain in clinical settings. This literature review aims to provide an overview of physiological methods for postoperative pain evaluation. The Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) guidelines were followed to perform a literature search on the Scopus database from 2002 to March 2024. Sixty-one studies were included in this review investigating parameters derived from six physiological signals, including Electrocardiogram (ECG), Photoplethysmogram (PPG), Skin Conductance (SC), Electroencephalogram (EEG), Electromyogram (EMG), and pupil size and reflexes. Parameters extracted from ECG, PPG, and SC signals were the most commonly studied. While there is evidence to support the use of physiological parameters as measures for postoperative pain evaluation, further research is needed to establish the reliability and generalizability of these parameters to develop an indicator that can be consistently applied across various clinical settings. For this purpose, this review describes current research findings and identifies limitations and directions for future work that should be considered in upcoming research on postoperative pain assessment.

Effects of epileptic seizures on the quality of biosignals recorded from wearables.

Wearable nonelectroencephalographic biosignal recordings captured from the wrist offer enormous potential for seizure monitoring. However, signal quality remains a challenging factor affecting data reliability. Models trained for seizure detection depend on the quality of recordings in peri-ictal periods in performing a feature-based separation of ictal periods from interictal periods. Thus, this study aims to investigate the effect of epileptic seizures on signal quality, ensuring accurate and reliable monitoring. This study assesses the signal quality of wearable data during peri-ictal phases of generalized tonic-clonic and focal to bilateral tonic-clonic seizures (TCS), focal motor seizures (FMS), and focal nonmotor seizures (FNMS). We evaluated accelerometer (ACC) activity and the signal quality of electrodermal activity (EDA) and blood volume pulse (BVP) data. Additionally, we analyzed the influence of peri-ictal movements as assessed by ACC (ACC activity) on signal quality and examined intraictal subphases of focal to bilateral TCS. We analyzed 386 seizures from 111 individuals in three international epilepsy monitoring units. BVP signal quality and ACC activity levels differed between all seizure types. We found the largest decrease in BVP signal quality and increase in ACC activity when comparing the ictal phase to the pre- and postictal phases for TCS. Additionally, ACC activity was strongly negatively correlated with BVP signal quality for TCS and FMS, and weakly for FNMS. Intraictal analysis revealed that tonic and clonic subphases have the lowest BVP signal quality and the highest ACC activity. Motor elements of seizures significantly impair BVP signal quality, but do not have significant effect on EDA signal quality, as assessed by wrist-worn wearables. The results underscore the importance of signal quality assessment methods and careful selection of robust modalities to ensure reliable seizure detection. Future research is needed to explain whether seizure detection models' decisions are based on signal responses induced by physiological processes as opposed to artifacts.

Combined Method Comprising Low Burden Physiological Measurements with Dry Electrodes and Machine Learning for Classification of Visually Induced Motion Sickness in Remote-Controlled Excavator

The construction industry is actively developing remote-controlled excavators to address labor shortages and improve work safety. However, visually induced motion sickness (VIMS) remains a concern in the remote operation of construction machinery. To predict the occurrence and severity of VIMS, we developed a prototype system that acquires multiple physiological signals with different mechanisms under a low burden and detects VIMS from the collected data. Signals during VIMS were recorded from nine healthy adult males operating excavator simulators equipped with multiple displays and a head-mounted display. Light gradient-boosting machine-based VIMS detection binary classification models were constructed using approximately 30,000 s of time-series data, comprising 23 features derived from the physiological signals. These models were validated using leave-one-out cross-validation on seven participants who experienced severe VIMS and evaluated through area under the curve (AUC) scores. The mean receiver operating characteristic curve AUC score was 0.84, and the mean precision–recall curve AUC score was 0.71. All features were incorporated into the models, with saccade frequency and skin conductance response identified as particularly important. These trends aligned with subjective assessments of VIMS severity. This study contributes to advancing the use of remote-controlled machinery by addressing a critical challenge to operator performance and safety.

Empatica E4 Assessment of Child Physiological Measures of Listening Effort During Remote and In-Person Communication.

Telepractice is a growing service model that delivers aural rehabilitation to deaf and hard-of hearing children via telecommunications technology. Despite known benefits of telepractice, this delivery approach may increase patients' listening effort (LE) characterized as an allocation of cognitive resources toward an auditory task. The study tested techniques for collecting physiological measures of LE in normal-hearing (NH) children during remote (referred to as tele-) and in-person communication using the wearable Empatica E4 wristband. Participants were 10 children (age range: 9-12 years old) who came to two tele- and two in-person weekly sessions, order counterbalanced. During each session, the children heard a short passage read by the clinical provider, completed an auditory passage comprehension task, and self-rated their effort as a part of the larger study. Measures of electrodermal activity and blood volume pulse amplitude were collected from the child E4 wristband. No differences in child subjective, physiological measures of LE or passage comprehension scores were found between in-person sessions and telesessions. However, an effect of treatment duration on subjective and physiological measures of LE was identified. Children self-reported a significant increase in LE over time. However, their physiological measures demonstrated a trend indicating a decrease in LE. A significant association between subjective measures and the passage comprehension task was found suggesting that those children who reported more effort demonstrated a higher proportion of correct responses. The study demonstrated the feasibility of collection of physiological measures of LE in NH children during remote and in-person communication using the E4 wristband. The results suggest that measures of LE are multidimensional and may reflect different sources of, or cognitive responses to, increased listening demand. https://doi.org/10.23641/asha.27122064.

Decoding pain: prediction under different emotional contexts through physiological signals

AbstractPain recognition is a challenging yet crucial problem. Common methods used to measure pain are based on self-reported tools; however, not every person can communicate it. Therefore, automatic pain detection methods have emerged. Since pain is related to the emotional state of an individual, this variable must be considered. Thus, this work proposes pain prediction under different emotional contexts. For this purpose, data were collected during a protocol designed for pain induction with previous emotional elicitation. Emotions were elicited through videos composed of excerpts of documentaries, horror and comedy films, while the pain was induced through a Cold Pressor Test. Physiological signals, such as electrocardiogram, electrodermal activity and surface electromyogram, were collected during the protocol. Furthermore, several questionnaires were answered and pain reports were also registered. Two problems were addressed: pain classification and estimation of the Pain Tolerance score. The algorithm with the best performance for each problem was found using only data from the neutral session and nested cross-validation strategy. Using only physiological data from the neutral session, a F1-score of 99.32% was obtained for pain recognition and a mean absolute error (MAE) of 0.29 was obtained for Pain Tolerance estimation. When considering all the emotional sessions, the physiological data were merged with scores of the Visual Analogue Scale questionnaire, achieving a F1-score of 98.60% and a MAE of 0.41, for the first and second problems, respectively. These results are promising and stress out the key role that the emotional context of the individuals plays in pain prediction.

Vibration annoyance due to turbulences in an airplane : subjective and physiological assessments

Turbulence phenomena in an aircraft create important vibrations, at frequencies of between 0.5 and 10 Hz. An experimental design was used to assess the influence of different signal parameters (frequency band, vertical and lateral vibration levels), and the task the participant in which the participant was involved (resting, watching a movie on a tablet computer, working by typing and using the trackpad of a computer). Thirty-three participants were subjected to around twenty signals, each lasting 45 s, using a multi-directional excitation device available in Airbus facilities. Physiological parameters (electrodermal activity, heart rate) were measured continuously. After each signal, the participant was asked to assess the discomfort of the situation. The results showed the influence of different signal characteristics or task assigned to the participant. As a general rule, subjective assessments correspond to physiological measurements. The experiment revealed the influences of the signals physical factors and the task performed by the participant. Finally, the ISO2631 standard seems to provide a good representation of the subjective evaluation of discomfort in the different configurations presented.

The effects of noise on objective and subjective measures during speech recognition tasks as stress indicators: preliminary results

Objective indicators of stress associated with annoyance scales are essential tools to advance knowledge in the area. Electrodermal activity (EDA) can be used to evaluate physiological responses, providing a picture of autonomic nervous system. Twenty-five adults were evaluated at three situations of speech recognition tasks with monosyllables: in quiet, competitive noise at 65 dBA and 75 dBA. After each situation with noise, the annoyance scale was applied. After, low-pass filtering was used, and phasic phase was analyzed. Results showed that the percentage of speech recognition hits decreased significantly with noise at 75 dBA (p<0.01), when compared to the situation without noise. Furthermore, it was found that annoyance increased significantly as noise at 75 dBA (p<0.01), when compared to 65 dBA. In relation to EDA, there was a significant increase in the number of peaks when comparing speech recognition situations without noise and with noise at 75 dBA (p<0.01), but not for noise at 65 dBA. Regarding the amplitude of the first skin conductance response peak, there was no significant difference between the three situations. These findings suggest that higher noise levels impact on speech recognition and annoyance, causing greater listening effort and increasing stress levels.

Exploring emotions beyond the laboratory: A review of emotional and physiological ecological momentary assessment methods in children and youth.

Recent advancements in methodologies such as ecological momentary assessment (EMA) and ambulatory physiology devices have enhanced our ability to measure emotions experienced in daily life. Despite the feasibility of EMA for assessing children's and youth's emotional self-reports, the feasibility of combining it with physiological measurements in a real-life context has yet to be established. Our scoping review evaluates the feasibility and usability of implementing emotional and physiological EMA in children and youth. Due to the complexities of physiological EMA data, this review also synthesized existing methodological and statistical practices of existing studies. Following the PRISMA-ScR guidelines, we searched and screened PsycINFO, PubMed, and Web of Science electronic databases for studies that assessed children's and youth's subjective emotions and cardiac or electrodermal physiological responses outside the laboratory. Our initial search resulted in 4174 studies, 13 of which were included in our review. Findings showed significant variability in the feasibility of physiological EMA, with physiology device wear-time averaging 58.77% of study periods and data loss due to quality issues ranging from 0.2% to 77% across signals. Compliance for emotional EMA was approximately 60% of study periods when combined with physiological EMA. The review points to a lack of standardized procedures in physiological EMA and suggests a need for guidelines in designing, processing, and analyzing such data collected in real-life contexts. We offer recommendations to enhance participant engagement and develop standard practices for employing physiological EMA with children and youth for emotion, developmental, and psychophysiology researchers.

Physiological responses to soundscape recordings in a laboratory experiment

The evaluation of acoustic environments using the soundscape approach offers the possibility of a holistic analysis. Physiological measurements can complement this approach in order to provide continuous information on the listener's physiological response to the acoustic environment and also record unconscious responses. However, it is essential to clarify which differences in the soundscape characteristics can induce significant changes in the physiological response of the listener. In addition to physiological measurements, listening tests in virtual reality can complement the approach to include soundscape context in laboratory studies to a greater extent. The study conducted in this paper therefore represents a preliminary study for experiments in virtual reality and investigates the reaction of the participants' skin conductance to various soundscape recordings in a laboratory setting. The analysis of the physiological data reveals aspects of soundscapes that are more likely to elicit a stress response or relaxation and shows how much soundscape recordings need to differentiate from each other such that physiological measurements can add value to the holistic soundscape approach.

EEG Dataset for the Recognition of Different Emotions Induced in Voice-User Interaction

Electroencephalography (EEG)-based open-access datasets are available for emotion recognition studies, where external auditory/visual stimuli are used to artificially evoke pre-defined emotions. In this study, we provide a novel EEG dataset containing the emotional information induced during a realistic human-computer interaction (HCI) using a voice user interface system that mimics natural human-to-human communication. To validate our dataset via neurophysiological investigation and binary emotion classification, we applied a series of signal processing and machine learning methods to the EEG data. The maximum classification accuracy ranged from 43.3% to 90.8% over 38 subjects and classification features could be interpreted neurophysiologically. Our EEG data could be used to develop a reliable HCI system because they were acquired in a natural HCI environment. In addition, auxiliary physiological data measured simultaneously with the EEG data also showed plausible results, i.e., electrocardiogram, photoplethysmogram, galvanic skin response, and facial images, which could be utilized for automatic emotion discrimination independently from, as well as together with the EEG data via the fusion of multi-modal physiological datasets.

Enhancing User Experience on Social Media Platforms: A Flow Theory-Based Approach

In recent years, social media platforms, such as Facebook and Twitter have seen rapid growth and are favored by users of all ages. However, in the age of information overload, the quality of interactions on social media platforms varies significantly, leading to negative feelings among users and affecting their overall experience and loyalty. This study takes the Flow theory as its starting point and investigates the needs of social media users at various stages of the flow experience. We propose modifications to the flow theory model with the aim of enhancing user experience and satisfaction. Firstly, based on literature review, we identify micro-level issues of the product, propose hypotheses, and construct validation experiments in the context of social media. The experiment collects Electrodermal Activity (EDA) and heart rate variability (HRV) data of 31 participants using a multi-channel physiological instrument and collects their emotional experience data using the Pleasure-Arousal-Dominance (PAD) scale. Results indicate that a combined textual-graphical interface layout is superior to other layouts in positively inducing flow and emotional experiences. Positive content tonality is more effective at eliciting positive flow and emotional experiences than negative or neutral content. Video presentations have a stronger sense of immersion and emotional expression, making them more conducive to inducing flow experiences and positive emotional feedback. This study, grounded in user psychology, provides a theoretical framework based on flow and emotional experiences for social media product design, quantitatively examining the positive psychological activities of users when using social media.

Sniffing out a solution: How emotional body odors can improve mindfulness therapy for social anxiety

BackgroundHuman body odors (BOs) serve as an effective means of social communication, with individuals exposed to emotional BOs experiencing a partial replication of the sender's affective state. This phenomenon may be particularly relevant in conditions where social interactions are impaired, such as social anxiety. Our study aimed to investigate if emotional human BOs could augment the benefits of mindfulness-based interventions. MethodsWe enrolled 48 women with social anxiety symptoms and assigned them to groups exposed to happiness BO, fear BO, or clean air. Participants engaged in mindfulness practice over two consecutive days, which included breathing, meditation, and relaxation exercises. During these interventions, the odor specific to each group was presented. Affective symptoms were assessed at the beginning and end of each day, with heart rate variability (HRV) and skin conductance level (SCL) recorded during the intervention. ResultsSelf-reported anxiety level revealed a significant reduction in anxiety on the second day for both happiness and fear conditions, but not for the clean air group. However, on a physiological level, fear BO exposure compared to clean air led to decreased HRV, indicating that fear BO may induce a less physiological relaxed state. No significant differences were observed in SCL between odor conditions. ConclusionsThese findings suggest that exposure to BOs triggers the perception of a “social presence”, improving the ecological validity of a psychological treatment. If replicated and expanded, these findings could pave the way for using BOs as catalysts in existing therapies.

Evaluating the Effects of Different Cognitive Tasks on Autonomic Nervous System Responses: Implementation of a High-Precision, Low-Cost Complementary Method.

We developed a low-cost, user-friendly complementary research tool to evaluate autonomic nervous system (ANS) activity at varying levels of cognitive workload. This was achieved using visual stimuli as cognitive tasks, administered through a specially designed computer-based test battery. To assess sympathetic stress responses, skin conductance response (SCR) was measured, and electrocardiograms (ECG) were recorded to evaluate heart rate variability (HRV), an indicator of cardiac vagal tone. Twenty-five healthy adults participated in the study. SCR and ECG recordings were made during both tonic and phasic phases using a computer-based system designed for visual stimuli. Participants performed a button-pressing task upon seeing the target stimulus, and the relationship between reaction time (RT) and cognitive load was evaluated. Analysis of the data showed higher skin conductance levels (SCLs) during tasks compared to baseline, indicating successful elicitation of sympathetic responses. RTs differed significantly between simple and cognitive tasks, increasing with mental load. Additionally, significant changes in vagally mediated HRV parameters during tasks compared to baseline highlighted the impact of cognitive load on the parasympathetic branch of the ANS, thereby influencing the brain-heart connection. Our findings indicate that the developed research tool can successfully induce cognitive load, significantly affecting SCL, RTs, and HRV. This validates the tool's effectiveness in evaluating ANS responses to cognitive tasks.

Effect of Relaxation-Based Virtual Reality on Psychological and Physiological Stress of Substance Abusers Under Detoxification: A Randomized Controlled Trial.

Substance abuse is a widespread problem, with high rates of treatment dropout. Stress plays a crucial role in this problem, so innovative interventions with stressed patients can assist them in completing treatment. This study is a randomized controlled trial with 60 participants who have substance abuse disorder undergoing detoxification at a residency facility in Tehran, Iran. Participants were randomly assigned to one of three groups: watching a 360° video of nature, a 360° video of a city environment, or no virtual experience. The intervention was performed only for one session. Psychological stress was measured using the Positive and Negative Affect Schedule and Perceived Stress Scale before and after the intervention. Physiological stress was assessed through respiratory rate, skin conductance, and heart rate recordings during the virtual reality (VR) experience. Data analysis was performed using R software (version 4.2). Paired t-test results indicated significant psychological differences before and after virtual nature experiences, but not in the control and city groups. The repeated measure ANOVA showed a significant reduction in skin conductance (p<0.01) and respiratory rate (p<0.01) scores in the nature group. The findings suggest that VR relaxation could be a potentially beneficial intervention for reducing stress in patients during detoxification.

Trait self-compassion enhances activation in the medial prefrontal cortex during fear extinction: An fNIRS study

Fear acquisition and fear extinction are the most widely used experimental models to study anxiety related disorders, with the medial prefrontal cortex (mPFC) playing an important role in this process. Previous research suggests that trait self-compassion is associated with lower anxiety, but the neural mechanisms underlying this relationship remain unclear. Women generally exhibit lower self-compassion than men, making them more vulnerable to fear and anxiety. In this study, female participants were divided into two groups - high and low trait self-compassion, based on their scores on the Self-Compassion Scale-Short Form (SCS-SF). Both groups completed fear acquisition and fear extinction tasks, during which conditioned responses (CRs) were measured using self-reported unconditioned stimulus (US) expectancy ratings, skin conductance response (SCR), and functional near-infrared spectroscopy (fNIRS). The results showed that in the fear acquisition phase, all participants successfully acquired fear, showing greater responses to threat stimuli than safety stimuli. However, participants with high trait self-compassion exhibited lower SCR than those with low trait self-compassion. In the fear extinction phase, compared to individuals with low trait self-compassion, individuals with high trait self-compassion exhibited more effective fear extinction learning, characterized by lower US expectancy ratings, lower SCR, and higher mPFC activation. Moreover, trait self-compassion was significantly correlated with the behavioral extinction ability and the mPFC activation during the late phase of fear extinction, and behavioral extinction ability was significantly correlated with mPFC activation. The findings of this study suggest individuals with high trait self-compassion have better physiological flexibility during fear acquisition and fear extinction, and may through enhancing mPFC activation to facilitate fear extinction. The results provide new insights into the pathological mechanisms of anxiety.

Physiological, behavioral, and self-report outcomes of acceptance- and regulation-based exposure for intrusive thoughts

Leading theories regarding the mechanisms of exposure for OCD focus on Pavlovian fear reduction more than operant processes. Acceptance-based exposure directly targets operant behavior. Integrating these perspectives could lead to a more robust understanding of mechanisms of change in exposure and more effective and enduring treatments. The current study investigated acceptance and regulation of distress during exposure. Participants with intrusive thoughts were randomized into three groups, Acceptance (n = 23), Regulation (n = 20), and Control (n = 21), and completed two behavioral avoidance tests (BATs) 1 week apart. Active conditions completed a 30-min exposure plus 6 days of 10-min exposures at home; Control participants watched videos of the same durations. Self-report measures were collected at both sessions, and behavioral, subjective, and physiological repeated measures data were collected during both BATs. Compared to Control, active conditions decreased OCD symptom severity, rituals, and skin conductance levels, while Acceptance showed lower skin conductance levels than Regulation and Control. Acceptance showed greater willingness and psychological flexibility than Control, while Regulation did not. Results support theorized mechanisms of change in acceptance-based exposure and suggest willingness to experience distress may paradoxically lead to decreased physiological arousal, which has important implications for treatment and future research.

Effects of a sedentary behaviour intervention in emergency dispatch centre phone operators: a study protocol for the SECODIS randomised controlled cross-over trial

IntroductionSedentary behaviour is a public health problem. We mainly have sedentary behaviour at work, transforming them into occupational risk. To our knowledge, there is no intervention study on the reduction...

Comparison of feature learning methods for non-invasive interstitial glucose prediction using wearable sensors in healthy cohorts: a pilot study

BackgroundAlterations in glucose metabolism, especially the postprandial glucose response (PPGR), are crucial contributors to metabolic dysfunction, which underlies the pathogenesis of metabolic syndrome (MetSyn). Personalized low-glycemic diets (PLGD) have shown promise in reducing postprandial glucose spikes. However, current methods such as invasive continuous glucose monitoring (CGM) or multi-omics data integration to assess PPGR come with limitations, including cost and invasiveness, hindering widespread adoption in primary disease prevention. Our aim is to assess machine-learning algorithms for predicting individual PPGR using non-invasive wearable data, thereby circumventing the limitations associated with existing approaches. By identifying the most accurate model, we seek to provide a more accessible and efficient method for managing glucose metabolism. MethodsThis data-driven analysis utilized the experimental dataset from the SENSE (”Systemische Ernährungsmedizin”) study. Healthy participants used an Empatica E4 wristband and Abbott Freestyle Libre 3 CGM for ten days. Blood volume pulse (BVP), electrodermal activity (EDA), heart rate (HR), skin temperature (TEMP), and the corresponding CGM values were measured. Subsequently, four data-driven deep learning (DL) model-convolutional neural network (CNN), lightweight transformer (LTF), long short-term memory with attention (LSTM-A), and Bi-directional LSTM (BiLSTM)-were implemented and compared to determine the potential of DL in predicting interstitial glucose levels without involving food and activity logs. ResultsThe proposed BiLSTM achieved the best interstitial glucose prediction performance, with an average root mean squared error (RMSE) of 13.42 mg/dL, an average mean absolute percentage error (MAPE) of 0.12, and only 3.01% values falling within area D in Clarke error grid analysis (CEGA), incorporating the leave-one-out cross-validation (LOOCV) strategy for a five-minute prediction horizon. ConclusionThe findings of this study may demonstrate the feasibility of transferring knowledge gained from invasive glucose monitoring devices to non-invasive approaches. Furthermore, it emphasizes the promising prospects of combining deep learning with wearable technologies to predict glucose levels in healthy individuals.

Between Scylla and Charybdis: Fixed-Ratio Avoidance Response Effort and Unavoidable Shock Extinction in Humans

Avoidance of potential threat may become maladaptive when it is indiscriminate and resistant to change. Here, we investigated the resistance to change of high and low avoidance response effort when avoidance extinction involved unavoidable presentations of the aversive event (shock) in humans. Following fear conditioning, participants prevented upcoming shock delivery by responding on high (i.e., fixed ratio, FR-20) and low (FR-5) negative reinforcement schedules. Next, noneliminable shock was used for an avoidance extinction procedure whereby responding was followed by, rather than prevented, shock. During a subsequent standard extinction and response prevention test phase, we found that High effort (FR-20) avoidance would be more readily extinguished than Low effort (FR-5) avoidance. It was also predicted that fear, threat expectancy, and psychophysiological (skin conductance) responses would decrease on avoidable trials and increase on unavoidable trials before extinguishing to low levels. It was found that in the final extinction re-test phase when avoidance was possible, responding increased, particularly for low effort cues. Both fear and expectancy remained high. Individual differences on clinically relevant measures of trait anxiety, intolerance of uncertainty and experiential avoidance were associated with greater levels of fear and threat expectancy. Overall, unavoidable shock extinction may hold promise for further translational investigations of avoidance learning, extinction, and clinical treatment development.

Stochastic Analysis of Epithelial/Absorbed Power Density in Multilayered Planar Skin Model With Uncertain Tissue Electric Properties

AbstractStochastic analysis of the absorbed power density (APD) on skin surface exposed to radiation of halfwave dipole at 10, 30 and 90 GHz and for different antenna‐body distances is presented. Skin tissue is modeled as a half‐space consisting of one layer (skin) or three layers (skin, fat and muscle) whose permittivities and conductivities are uncertain. Deterministic part is based on numerical solution of Pocklington equation via Galerkin Bubnov Indirect Boundary Element method (GB‐IBEM) and numerical integration of the corresponding field integrals. Uncertainty from tissue electric parameters is propagated to APD via non‐intrusive Stochastic Collocation method (SCM) in order to compute stochastic moments of APD. For 1‐layered model APD stochastic moments are computed with 3 deterministic simulations. On the other hand APD mean and variance for 3 layered model are successfully computed with 13 deterministic simulations while skewness and kurtosis require 85 deterministic simulations. The ratio of APD standard deviation and mean decreases with frequency thus indicating that the uncertainty in the tissue electric properties has smaller effect on APD uncertainty at higher frequencies. Finally, sensitivity analysis carried out for both 1‐layered and 3‐layered models indicates the same conclusions. At 10 GHz skin permittivity and conductivity are the two most important parameters. However, as frequency increases the impact of skin conductivity prevails. This indicates that in frequency range 10–90 GHz the APD uncertainty quantification and sensitivity analysis can be carried out by using only 2‐dimensional stochastic model.