Wavelet-based motion artifact removal for electrodermal activity

Electrodermal activity (EDA) recording is a powerful, widely used tool for monitoring psychological or physiological arousal. However, analysis of EDA is hampered by its sensitivity to motion artifacts. We propose a method for removing motion artifacts from EDA, measured as skin conductance (SC), using a stationary wavelet transform (SWT). We modeled the wavelet coefficients as a Gaussian mixture distribution corresponding to the underlying skin conductance level (SCL) and skin conductance responses (SCRs). The goodness-of-fit of the model was validated on ambulatory SC data. We evaluated the proposed method in comparison with three previous approaches. Our method achieved a greater reduction of artifacts while retaining motion-artifact-free data

Dynamic Adaptive System for Robot-Assisted Motion Rehabilitation

This paper presents a dynamic adaptive system for administration of robot-assisted therapy. The main novelty of the proposed approach is to close patient in the loop and use multisensory data (such as motion, forces, voice, muscle activity, heart rate, and skin conductance) to adaptively and dynamically change the complexity of the therapy and real-time displays of an immersive virtual reality system in accordance with specific patient requirements. The proposed rehabilitation system can be considered as a complex system that is composed of the following subsystems: data acquisition, multimodal human–machine interface, and adaptable control system. This paper shows the description of the developed fuzzy controller used as the core of the adaptable control subsystem. Finally, experimental results with ten subjects are reported to show the performance of the proposed solution

Treat me well : affective and physiological feedback for wheelchair users

This work reports a electrocardiograph and skin conductivity hardware architecture, based on E-textile electrodes, attached to a wheelchair for affective and physiological computing. Appropriate conditioning circuits and a microcontroller platform that performs acquisition, primary processing, and communication using Bluetooth were designed and implemented. To increase the accuracy and repeatability of the skin conductivity measuring channel, force measurement sensors were attached to the system certifying measuring contact force on the electrode level. Advanced processing including Rwave peak detector, adaptive filtering and autonomic nervous system analysis based on wavelets transform was designed and implemented on a server. A central design of affective recognition and biofeedback system is described.Fundação para a Ciência e a Tecnologia (FCT

Noninvasive Physiological Measures And Workload Transitions:an Investigation Of Thresholds Using Multiple Synchronized Sensors

The purpose of this study is to determine under what conditions multiple minimally intrusive physiological sensors can be used together and validly applied for use in areas which rely on adaptive systems including adaptive automation and augmented cognition. Specifically, this dissertation investigated the physiological transitions of operator state caused by changes in the level of taskload. Three questions were evaluated including (1) Do differences exist between physiological indicators when examined between levels of difficulty? (2) Are differences of physiological indicators (which may exist) between difficulty levels affected by spatial ability? (3) Which physiological indicators (if any) account for variation in performance on a spatial task with varying difficulty levels? The Modular Cognitive State Gauge model was presented and used to determine which basic physiological sensors (EEG, ECG, EDR and eye-tracking) could validly assess changes in the utilization of two-dimensional spatial resources required to perform a spatial ability dependent task. Thirty-six volunteers (20 female, 16 male) wore minimally invasive physiological sensing devices while executing a challenging computer based puzzle task. Specifically, participants were tested with two measures of spatial ability, received training, a practice session, an experimental trial and completed a subjective workload survey. The results of this experiment confirmed that participants with low spatial ability reported higher subjective workload and performed poorer when compared to those with high spatial ability. Additionally, there were significant changes for a majority of the physiological indicators between two difficulty levels and most importantly three measures (EEG, ECG and eye-tracking) were shown to account for variability in performance on the spatial task

Sex differences in emotional concordance.

Emotions involve response synchronization across experiential, physiological, and behavioral systems, referred to as concordance or coherence. Women are thought to be more emotionally aware and expressive than men and may therefore display stronger response concordance; however, research on this topic is scant. Using a random-order film-average design, we assessed concordance among experiential (arousal, valence), autonomic (electrodermal activity, heart rate, preejection period, respiratory sinus arrhythmia), respiratory (respiratory rate), and behavioral (corrugator and zygomatic electromyography) responses to 15 two-minute films varying in valence and arousal. We then calculated for each participant and pair of measures a within-subject correlation index using averages from the 15 films. Pronounced individual concordance of up to 0.9 was observed. Arousal-physiology and valence-behavior concordances were particularly pronounced. Women displayed higher concordance than men for almost all pairs of measures. Findings indicate stronger psychophysiological response coupling in women than men and provide novel insights into affective differences between the sexes

Development of Galvanic Skin Response Sensor System to Measure Mental Stress

Stress is a very normal reaction when a person is feel threaten or upset in some way. Generally, stress happen when a person ability is not able to meet with the situational demands. It can be either positive or negative. Stress can give a person to have high concentration to face certain circumstances as well as better reaction to handle difficult situation. On the other side, it can also cause sickness to a person if one is suffer from overstress. A person will have health issues like the risk of depression and neurological disorders like stroke if mental stress level is too high. Thus, a device is necessary to measure the stress level so that the stress level can be regulate before it is out of control. Although there are several of methods in the market that are able to measure the stress level, but there are all expensive and complicated. Thus, this project will be focusing on developing a Galvanic Skin Response Sensor that are able to measure stress level based on the skin conductivity. GSR sensor is an economical tool to measure stress level with simpler analysis. Complete methodology and findings are shown as we go through the report

Advances in point process filters and their application to sympathetic neural activity

This thesis is concerned with the development of techniques for analyzing the sequences of stereotypical electrical impulses within neurons known as spikes. Sequences of spikes, also called spike trains, transmit neural information; decoding them often provides details about the physiological processes generating the neural activity. Here, the statistical theory of event arrivals, called point processes, is applied to human muscle sympathetic spike trains, a peripheral nerve signal responsible for cardiovascular regulation. A novel technique that uses observed spike trains to dynamically derive information about the physiological processes generating them is also introduced. Despite the emerging usage of individual spikes in the analysis of human muscle sympathetic nerve activity, the majority of studies in this field remain focused on bursts of activity at or below cardiac rhythm frequencies. Point process theory applied to multi-neuron spike trains captured both fast and slow spiking rhythms. First, analysis of high-frequency spiking patterns within cardiac cycles was performed and, surprisingly, revealed fibers with no cardiac rhythmicity. Modeling spikes as a function of average firing rates showed that individual nerves contribute substantially to the differences in the sympathetic stressor response across experimental conditions. Subsequent investigation of low-frequency spiking identified two physiologically relevant frequency bands, and modeling spike trains as a function of hemodynamic variables uncovered complex associations between spiking activity and biophysical covariates at these two frequencies. For example, exercise-induced neural activation enhances the relationship of spikes to respiration but does not affect the extremely precise alignment of spikes to diastolic blood pressure. Additionally, a novel method of utilizing point process observations to estimate an internal state process with partially linear dynamics was introduced. Separation of the linear components of the process model and reduction of the sampled space dimensionality improved the computational efficiency of the estimator. The method was tested on an established biophysical model by concurrently computing the dynamic electrical currents of a simulated neuron and estimating its conductance properties. Computational load reduction, improved accuracy, and applicability outside neuroscience establish the new technique as a valuable tool for decoding large dynamical systems with linear substructure and point process observations

Prerequisites for Affective Signal Processing (ASP)

Although emotions are embraced by science, their recognition has not reached a satisfying level. Through a concise overview of affect, its signals, features, and classification methods, we provide understanding for the problems encountered. Next, we identify the prerequisites for successful Affective Signal Processing: validation (e.g., mapping of constructs on signals), triangulation, a physiology-driven approach, and contributions of the signal processing community. Using these directives, a critical analysis of a real-world case is provided. This illustrates that the prerequisites can become a valuable guide for Affective Signal Processing (ASP)