Galvanic Skin Response Sensor Research Articles

Gauging the effectiveness of music and yoga for reducing stress among engineering students: An investigation based on Galvanic Skin Response

The purpose of this research is to examine the influence of music and yogic breathing for the management and control of stress. To discover the most effective stimuli to handle stress by measuring the effect of types of musical drills and yogic breathing on engineering students using the Galvanic Skin Response Sensor Meter (GSRSM). The present study attempts to study the effectiveness of music and yoga drills for relieving and managing stress. The study used a stratified random sampling method selecting engineering students from four streams. The GSRSM was used as a tool to record the responses after 300 seconds for the experimental and the control groups of 200 students each. Each group was comprised of 52 females (26%) and 148 males (74%). The experimental group reported reduction in mean value in Galvanic Skin Response (GSR) when they underwent deep yogic breathing, listened to religious hymns and listened to flute music. On the basis of the results, the researchers suggest that all three techniques i.e practicing yogic breathing, listening to religious hymns and listening to flute music were effective in reducing the stress level of engineering students. Listening to flute music emerged from these three drills, as the most effective stimulus for stress management.

Neuromarketing for a better understanding of consumer needs and emotions

In this paper we are talking about the fact that marketing and publicity specialists have become aware of the limitations of traditional market research methods for decades, but only in recent years science has allowed the development of a more effective mechanism by which consumers' thoughts can be deciphered: neuromarketing. This term refers to the use of techniques developed by cognitive neuroscience and psychology specialists to analyze and understand people's reactions to products and promotions, which allows refining marketing efforts to make them more effective. In the article we are talking about the tools used for this purpose, which include magnetic resonance imaging (MRI), brain scanners that identify brain parts that react to different stimuli, and electroencephalography (EEG), devices that measure electrical activity in the brain. By tracking brain reactions to different stimuli, researchers can discover the marketing mechanisms that are most likely to lead to the desired outcome: selling the product. For this, in parallel with the EEG measurements, an eye-tracking device is used, which allows the exact identification of the stimulus that produces the reaction from that moment. Also, some neuromarketing companies also use GSR (galvanic skin response) sensors to measure the electrical conductivity of the skin, which is another element that provides information about the consumer's response to various commercial messages. The purpose of our article is to show the role played by neuromarketing in the correct understanding of consumer needs, words and emotions.

Stress management of engineering students through deep breathing yoga

Stress disturbs the normal physiological or psychological functioning of a person. The stratified random sampling interventional experimental study design was used to measure galvanic skin response (GSR). The experimental (n = 200) and control groups (n = 200) comprised of 52 females (26%) and 148 males (74%). GSR sensor meter (GSRSM) was used to record skin conductivity (pre and post drill). The experimental group were exposed to deep breathing yoga (DBY); whereas the control group was not exposed to it. The experimental group experiencing stress conveyed higher mean reduction at times (t = 0 sec and t = 300 sec) after DBY as compared to the control group, and the results were significant (p < 0.01). These findings support that DBY reduces stress by cognitive appraisal of measurable skin conductivity through GSRSM biofeedback.

Stress Management of engineering students through Deep Breathing Yoga

Stress disturbs the normal physiological or psychological functioning of a person. The stratified random sampling interventional experimental study design was used to measure galvanic skin response (GSR). The experimental (n = 200) and control groups (n = 200) comprised of 52 females (26%) and 148 males (74%). GSR sensor meter (GSRSM) was used to record skin conductivity (pre and post drill). The experimental group were exposed to deep breathing yoga (DBY); whereas the control group was not exposed to it. The experimental group experiencing stress conveyed higher mean reduction at times (t = 0 sec and t = 300 sec) after DBY as compared to the control group, and the results were significant (p < 0.01). These findings support that DBY reduces stress by cognitive appraisal of measurable skin conductivity through GSRSM biofeedback.

Evaluation of driver stress level with survey, galvanic skin response sensor data, and force-sensing resistor data

Thousands of lives are lost in traffic accidents every year, and most traffic accidents are caused by driver errors. Causes and impairments such as fatigue, inattentiveness, alcohol usage, stress, and drugs are the main factors of these accidents. When a driver is subject to changing and complicated driving tasks in traffic, he or she should be able to assure driving authority to prevent potential hazards and accidents. In this context, the purpose of this study is to determine the stress level of the driver when driving in urban traffic in such situations requiring delegation of driving authority. Thus, the work combines stress questionnaire and galvanic skin response sensor to validate results and fuses with a force-sensing resistor. In this study, a prototype electric vehicle is equipped with sensors providing various drivers’ data including the responses of a force-sensing resistor sensor while galvanic skin is being collected on a specified route. At the end of the trip, the stress level of the drivers is determined by the collected data. Results indicate that the galvanic skin sensor stress results are consistent with the results of the survey with an average accuracy of 87.5%. The force-sensing resistor sensor is only used to determine gender stress. And the force-sensing resistor sensor gender-stress results are consistent with results of the survey with an accuracy of 100%. These results are used to validate the results of post-driving stress survey evaluated by SPSS 23.0 windows statistics software. Data analysis is particularly focused on demographic properties of participators, factor analysis, reliability tests, correlation, T-test, and one-way analysis of variance.

Implementation and Performance Analysis of Interoperable and Heterogeneous IoT-Edge Gateway for Pervasive Wellness Care

In recent years, interoperability has become a burning issue in current consumer-centric Internet of Things (IoT) ecosystem where heterogenous devices, protocols and things communicate with each other via locally available gateways. The problem becomes more stringent when consumers depend on the protocol-specific vertical silos that are engaged with the e-healthcare or consumer’ wellness care domain in the IoT-based scenario, thus resulting into a vulnerable system to be fail-affected by causing problems for the consumers. To solve this issue, we propose a novel IoT-gateway system that incorporates the heterogeneity perspective to assure the interoperability via utilizing the message queuing broker services to assist in the consumer’ wellness service provisioning for the consumers. In this study, we implement a novel interoperable IoT-gateway test-bed that involves 2.4 GHz industrial, scientific, and medical (ISM) radio signal, IEEE 802.11b/g/n and Bluetooth protocols to get seamlessly translated in interchangeable formats. We implemented the IoT-gateway and three IoT-motes physically to establish a proof-of-concept e-health message service while implying real-life pulse sensor, pulse-oximeter (SPO2) sensor and galvanic skin response (GSR) sensors. We also developed two virtual IoT-motes and embedded within the novel IoT-gateway hardware platform to simulate and test the possibility of further indulgent of more protocols to get associated with the proposed IoT-gateway framework. The proposed IoT-gateway is tested against the various quality factors to compare with available gold-standards to meet the quality of service for envisaged consumers. The results have shown the promising direction of futuristic application of smart edge-based IoT-gateway for possible consumer’ wellness care supports toward all classes of consumers in the world.

Impact of Physiological Signals Acquisition in the Emotional Support Provided in Learning Scenarios.

Physiological sensors can be used to detect changes in the emotional state of users with affective computing. This has lately been applied in the educational domain, aimed to better support learners during the learning process. For this purpose, we have developed the AICARP (Ambient Intelligence Context-aware Affective Recommender Platform) infrastructure, which detects changes in the emotional state of the user and provides personalized multisensorial support to help manage the emotional state by taking advantage of ambient intelligence features. We have developed a third version of this infrastructure, AICARP.V3, which addresses several problems detected in the data acquisition stage of the second version, (i.e., intrusion of the pulse sensor, poor resolution and low signal to noise ratio in the galvanic skin response sensor and slow response time of the temperature sensor) and extends the capabilities to integrate new actuators. This improved incorporates a new acquisition platform (shield) called PhyAS (Physiological Acquisition Shield), which reduces the number of control units to only one, and supports both gathering physiological signals with better precision and delivering multisensory feedback with more flexibility, by means of new actuators that can be added/discarded on top of just that single shield. The improvements in the quality of the acquired signals allow better recognition of the emotional states. Thereof, AICARP.V3 gives a more accurate personalized emotional support to the user, based on a rule-based approach that triggers multisensorial feedback, if necessary. This represents progress in solving an open problem: develop systems that perform as effectively as a human expert in a complex task such as the recognition of emotional states.

Use of neurometrics to choose optimal advertisement method for omnichannel business

ABSTRACTThe omnichannel business has deeply affected retail practices and promotional strategies. This paper presents an empirical evaluation of omnichannel advertisement channels using neurometric response of the viewers. High precision camera and Galvanic Skin Response sensors were used to record neurometric information of respondents. The response of forty volunteers against a set of cosmetic advertisements was recorded to train a computer for predicting expected neurometric response for an advertisement channel. The recorded neurometric data was further analyzed to develop a set of business rules to measure the effectiveness of any advertisement channel. Later, comparative analysis of various advertisement channels was done.

Hunger and stress monitoring system using galvanic skin response

In the world, roughly more than 3 million people are affected by muscle power loss diseases which cause lack of communication. Further, this lack of communication is a severe problem with hunger and stress, which sometimes proves to be fatal. It is essential to monitor physical parameters such as hunger and mental stress of the patient. To observe hunger and stress, galvanic skin response (GSR) sensor is a most preferred method because it measures the conductance of skin due to sweating. We have designed new hunger and stress monitoring system (HS-MS) that helps patients and their caretakers to monitor stress and hunger level. HS-MS is two electrodes system that attaches to two fingers (index and middle) of the patient and monitors starvation and tension. According to the response of the sensor, caretakers can identify hunger and even the mental stress conditions of the patient. In all, 35 patients were examined using HS-MS system and 20 of them were used as a control. Overall system accuracy was found out to be 86.6% and response time of HS-MS 5 seconds. Sensitivity with respect to hunger and stress was about 99.9% and 73.3% respectively. Thus HS-MS can be identified as a helpful tool to provide comfort to the patient easily and can be used in hospitals or homes with lonely elderly people.

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.

Flexible galvanic skin response sensor based on vertically aligned silver nanowires

Skin conductance is an important bio-signal and generally measured between two fingers using a commercial Galvanic Skin Response (GSR) sensor. In this study, an ultra-thin (6 μm thick) and highly flexible GSR (f-GSR) sensor was developed for application to wearable devices. The f- GSR sensor consists of a Ag-Au core-shell nanowire array embedded in polyimide matrix. Since the nanowire array is vertically aligned in the matrix, the f-GSR sensor has anisotropic electrical conductivity, i.e., electrically conducting in the thickness-direction and electrically insulating in the in-plane direction. Results show that after the nanowire tips contacted skin they did not degrade during repeated measurement for three months, indicating the mechanical and chemical stability of the f-GSR sensor. The f-GSR sensor exhibits significantly better sensitivity than a commercial sensor: the f-GSR sensor can detect an NaCl solution mimicking human sweat in the concentration range of 10−6 to 1 M. The f-GSR sensor is expected to be used in wearable or patch healthcare devices.

Emotion Based Music Recommendation System Using Wearable Physiological Sensors

Most of the existing music recommendation systems use collaborative or content based recommendation engines. However, the music choice of a user is not only dependent to the historical preferences or music contents. But also dependent to the mood of that user. This paper proposes an emotion based music recommendation framework that learns the emotion of a user from the signals obtained via wearable physiological sensors. In particular, the emotion of a user is classified by a wearable computing device which is integrated with a galvanic skin response (GSR) and photo plethysmography (PPG) physiological sensors. This emotion information is feed to any collaborative or content based recommendation engine as a supplementary data. Thus, existing recommendation engine performances can be increased using these data. Therefore, in this paper emotion recognition problem is considered as arousal and valence prediction from multi-channel physiological signals. Experimental results are obtained on 32 subjects' GSR and PPG signal data with/out feature fusion using decision tree, random forest, support vector machine and k-nearest neighbors algorithms. The results of comprehensive experiments on real data confirm the accuracy of the proposed emotion classification system that can be integrated to any recommendation engine.

Prototype development for real-time epilepsy seizures detector using three parameters

This paper proposes a prototype for real-time epilepsy seizures detection using skin conductance, temperature and sense movement. This proposed work is expected to help epilepsy patients to receive immediate help from the people around when seizures happen. This prototype is wearable and developed using Arduino Nano, Galvanic Skin Response (GSR) sensor, accelerometer, temperature sensor and pulse sensor. Epilepsy patients can wear this prototype just like a watch. The prototype is connected to the mobile application via Bluetooth and can alert the people around by buzzing alarm as well as sending text message to the doctor or family member. Details development and results are discussed in this paper.

Stress monitoring through non-invasive instrumental analysis of skin conductivity.

This paper envelops the notion of yogic breathing and its applications as one of the techniques for stress management through regulation of skin conductivity among Indian engineering students. Stress perturbs the normal physiological or psychological functioning of an individual. Thus, it is extremely vital to manage stress. To explore the consequence of yogic breathing on skin conductivity using galvanic skin response sensor meter (GSRSM) on engineering students, of different universities. The study uses stratified random sampling technique for the experimental study undertaken to measure skin conductivity. 471 Engineering students, in the age group of 18-22 years who gave informed written consent were screened, of which 71 (15%) dropped out and 400 students (84.9%) completed the study. The GSRSM was used to record skin conductivity (pre and post) among experimental (n = 200) and Control group (n = 200) each comprising of 52 females (26%) and 148 males (74%). The Experimental group underwent yogic breathing whereas the Control group did not do so. The experimental group reported reduction in mean value in skin conductivity after deep breathing for the time period (t = 300 sec) as compared to the control group, and this was significant (p < 0.01 and p < 0.05). It is recommended that, this uncomplicated and yet extremely effectual ancient technique of yogic breathing could be included in core curriculum to reduce and manage stress among engineering students. The paper thus highlights the use of yogic technique as an effective mode for Stress Management amongst Indian Engineering students.

Objective Measurement of Clinical Competency in Surgical Education Using Electrodermal Activity

Within the realm of surgical education, there is a need for objective means to determine surgical competence and resident readiness to operate independently. We propose a novel, objective method of assessing resident confidence and clinical competence based on measurement of electrodermal activity (EDA) during live surgical procedures. We hypothesized that with progressive training, EDA responses to the stress of performing surgery would exhibit decline, elucidating an objective correlate of clinical competence. EDA was measured using galvanic skin response sensors worn by residents performing laparoscopic cholecystectomy on sequential live human patients over an 8-month period. Baseline, phasic (peak) and tonic EDA responses were measured as a fractional change from baseline. University of Missouri, Columbia, Missouri, an academic tertiary care facility. Fourteen categorical general surgery residents and 5 faculty surgeons were voluntarily enrolled and participated through completion. Tonic fractional change (FCTONIC) was highest in PGY3 residents compared with postgraduate year (PGY) 1 and 2 residents (7.199 vs. 2.100, p = 0.004, 95% CI: 8.58-1.61 and PGY4 and 5 residents (7.199 vs. 2.079, p = 0.002, 95% CI: 8.38-0.29). Phasic fractional change in EDA (FCPHASIC) exhibited a progressive decline across resident training levels, with PGY1 and 2 residents having the highest response, and faculty displaying the lowest FCPHASIC responses. Statistical differences were seen between FCPHASIC faculty and PGY4 and 5 (3.596 vs. 6.180, p = 0.004, 95% CI: 0.80-4.36), PGY4 and 5, and PGY3 (6.180 vs. 15.998, p = 0.003, 95% CI: 3.33-16.3), as well as among all residents and faculty (13.057 vs. 3.596, p = 0.004, 95% CI: 15.8-3.1). Phasic EDA changes decrease with increasing clinical competence. For those participants with the lowest and highest levels of competence, tonic EDA changes are minimal. Tonic EDA changes follow an inverse-U shape with differing levels of clinical competence.

Study and analysis of human mental stress detection using galvanic skin response and heart rate sensors in wired and wireless environments

It is an infeasible task for psychoanalysts to monitor the chronic mental stress of patients. Due to topical and innovative developments in wireless sensor technology and physiological sensors, researchers have been attracted to pursue research in wireless body area sensor networks (WBASN) or wireless body area networks (WBSN). As a result, the wireless sensor technology has enabled medical science in enhancing real-time health monitoring and maintaining a better healthcare scenario. In our previous work, the mental stress sensor presented was able to detect the stress condition based on the Galvanic Skin Response (GSR) only with an average accuracy of about 76%. In this article, a system has been presented for sensing human mental stress by acquisition, processing and analysing the GSR and heart rate or pulse rate signals from human body. This system is proficient in detection of the mental stress condition using the GSR and heart rate signals assimilated by wearable physiological sensors in wired or wireless environments. For evaluation of the system performance, well-known supervised binary classifiers have been selected for classifying the GSR and heart rate data from the physiological dataset available and the results are discussed. This multi-sensor stress detection system has average accuracy more than the previous stress detection system using GSR.

Physiological Responses to Affective Tele-Touch during Induced Emotional Stimuli

The human touch has long been recognized to promote physical, emotional, social, and spiritual comfort. There are situations, however, when touch cannot be exchanged. Although mobile phones and web-based communication are ubiquitous, touch-a communication modality that conveys powerful messages-is inexistent in modern communications media. This paper describes a tele-touch device that transfers affective touch to another person through the internet. Commands for vibration, warmth, and tickle were sent over the internet to a haptic device at the subjects' forearm. With a heart rate (HR) monitor and a galvanic skin response (GSR) sensor, the physiological effect of the tele-touch device was evaluated as the subjects watched an emotionally-laden movie. We compared these to one group of subjects who were touched by their spouse or girlfriend and to subjects of a control group where no touch was provided. Results show that the HR of the subjects with the tele-touch device was not significantly different from those subjects who were touched by their loved ones. These results were in contrast to the subjects who were not provided with any form of touch. On the other hand, the GSR results revealed that all the three touch conditions were different from one another.

Study and Analysis of Human Stress Detection using Galvanic Skin Response (GSR) Sensor in Wired and Wireless Environments

Continuous monitoring of the chronic stress is an infeasible task for physicians and hence its diagnosis is also nontrivial. Recent development in biological sensor and wireless technology has attracted researchers to carry out research in wireless body sensor networks (WBSN). This has enabled medical science in improving real-time monitoring and maintaining human health in a better way. In this work, a system has been developed for sensing human stress, based on acquisition, processing and analysis of the Galvanic Skin Response (GSR) signal collected from human bodies. The system detects human stress condition using the GSR signal acquired by wearable biological sensing devices when the person is in sitting, standing or sleeping conditions using a wired environment. Also the system is capable of remotely sensing human stress (while the person is in remote place within the range of wireless medium) with wireless sensor network technology. Popular supervised binary classifiers have been used for classifying the GSR data from the physiological dataset available in literature into binary classes, i.e., stress condition or relaxed condition and the results are presented.

Patient-centered design criteria for wearable seizure detection devices.

Epilepsy is a common neurological condition. Seizure diary reports and patient- or caregiver-reported seizure counts are often inaccurate and underestimated. Many caregivers express stress and anxiety about the patient with epilepsy having seizures when they are not present. Therefore, a need exists for the ability to recognize and/or detect a seizure in the home setting. However, few studies have inquired on detection device features that are important to patients and their caregivers. A survey instrument utilizing a population of patients and caregivers was created to obtain information on the design criteria most desired for patients with epilepsy in regard to wearable devices. One thousand one hundred sixty-eight responses were collected. Respondents thought that sensors for muscle signal (61.4%) and heart rate (58.0%) would be most helpful followed by the O2 sensor (41.4%). There was more interest in these three sensor types than for an accelerometer (25.5%). There was very little interest in a microphone (8.9%), galvanic skin response sensor (8.0%), or a barometer (4.9%). Based on a rating scale of 1-5 with 5 being the most important, respondents felt that "detecting all seizures" (4.73) is the most important device feature followed by "text/email alerts" (4.53), "comfort" (4.46), and "battery life" (4.43) as an equally important group of features. Respondents felt that "not knowing device is for seizures" (2.60) and "multiple uses" (2.57) were equally the least important device features. Average ratings differed significantly across age groups for the following features: button, multiuse, not knowing device is for seizures, alarm, style, and text ability. The p-values were all<0.002. Eighty-two point five percent of respondents [95% confidence interval: 80.0%, 84.7%] were willing to pay more than $100 for a wearable seizure detection device, and 42.8% of respondents [95% confidence interval: 39.8%, 45.9%] were willing to pay more than $200. Our survey results demonstrated that patients and caregivers have design features that are important to them in regard to a wearable seizure detection device. Overall, the ability to detect all seizures rated highest among respondents which continues to be an unmet need in the community with epilepsy in regard to seizure detection. Additional uses for a wearable were not as important. Based on our results, it is important that an alert (via test and/or email) for events be a portion of the system. A reasonable price point appears to be around $200 to $300. An accelerometer was less important to those surveyed when compared with the use of heart rate, oxygen saturation, or muscle twitches/signals. As further products become developed for use in other health arenas, it will be important to consider patient and caregiver desires in order to meet the need and address the gap in devices that currently exist.

Walking and health: an enactive affective system

ABSTRACTThis essay presents a transdisciplinary project whose objective is to create a sensorised insole built with latex (Hevea brasiliensis) to measure physiological variations of the human body, as well as to graphically represent affective reciprocal exchanges of the human behaviour with the environment. The purpose is to improve our enactive system through the use of various physiological sensors (e.g. pressure, galvanic skin response and temperature sensors), which can be processed and visualised by revealing the affective exchanges of the body while walking in the city, pinned on a map as data visualisation. Inspired by the enaction theories, the output of sensors and devices application that models the perception as a laboratory phenomenon, as proposed by Dr Ted Krueger, the investigation directed by Dr Domingues is conceived for the expanded sensorium and for the reengineering of life. The artwork is inserted in the domain of aesthetic investigation of art as experiences related to topics on art and technoscience for innovation in health. The created prototype was tested in the city at different locations and the results demonstrated its use as a kind of personal assistant for vital signals by configuring an enactive system added of affective qualities which possibilities to reveal the ‘pathos’, or the affective narratives experienced in the emergent reciprocity with the city. The insole biomaterial, created by Dr Suelia Rodrigues (BioEngeLab), has been successfully used to measure the foot pressure and to serve as a health assistant, especially for people with diabetes. The signal-processing approaches, explored in Biomedical engineering by Dr Cristiano Miosso, were empowered by data visualisation approaches developed by Dr Ricardo Torres (University of Campinas). Finally, we consider this prototype a creative technology for mhealth, which is a disruptive innovation, by providing other forms of existence.