Differences

This shows you the differences between two versions of the page.

Link to this comparison view

Both sides previous revision Previous revision
Next revision
Previous revision
sensors:galvanic_skin_response [2021/03/22 01:23]
charles.reimer
sensors:galvanic_skin_response [2021/03/24 15:39] (current)
charles.reimer [Available Sensors & Specifications]
Line 15: Line 15:
 ===== Origins, Theory, & Physiology ===== ===== Origins, Theory, & Physiology =====
  
-EDA measurement has a long history, dating back to experiments conducted by DuBois-Reymond in Germany in the mid-1800s, in which individuals placed hands or feet into a zinc sulphate (ZnSO4) solution. DuBois-Reymond observed a current flowing from a resting limb to a limb contracted by the participant, and attributed this to muscular action potentials. In 1881, Hermann repeated this voluntary movement experiment, noting that areas with stronger sweating response showed a higher magnitude electrical current, providing a link between sweat glands and electrodermal phenomena. These phenomena were further studied by numerous other researchers during the 19th and 20th centuries.+EDA measurement has a long history, dating back to experiments conducted by DuBois-Reymond in Germany in the mid-1800s, in which individuals placed hands or feet into a zinc sulphate (ZnSO<sub>4</sub>) solution. DuBois-Reymond observed a current flowing from a resting limb to a limb contracted by the participant, and attributed this to muscular action potentials. In 1881, Hermann repeated this voluntary movement experiment, noting that areas with stronger sweating response showed a higher magnitude electrical current, providing a link between sweat glands and electrodermal phenomena. These phenomena were further studied by numerous other researchers during the 19th and 20th centuries.
  
 While the exact origins and physiological mechanisms of EDA are complex and still being investigated, three principal physiological theories offer accounts for for the basis of EDA phenomena: muscular activity, vascular changes, and secretory changes. Out of these three theories, the first two are primarily supported by correlational evidence, while the strongest support for a causal relationship is related to secretory changes. While the exact origins and physiological mechanisms of EDA are complex and still being investigated, three principal physiological theories offer accounts for for the basis of EDA phenomena: muscular activity, vascular changes, and secretory changes. Out of these three theories, the first two are primarily supported by correlational evidence, while the strongest support for a causal relationship is related to secretory changes.
Line 25: Line 25:
 ===== Electrodermal Measurement Principles & Data Components ===== ===== Electrodermal Measurement Principles & Data Components =====
  
-Measurement of EDA is based on the fundamental electrical principle of Ohm’s Law (//V = IR//), which states that the current (//I//flowing through a conductor between two points is directly proportional to the voltage (//V//across the two points and inversely proportional to the resistance (//R//of the conductor. If current is held constant between two electrodes, voltage will vary in proportion to the varying resistance of the skin, producing an output proportional to skin conductance. Likewise, if voltage is held constant between two electrodes applied to the skin, the current will vary in proportion to the varying resistance of the skin, producing an output proportional to skin resistance.+Measurement of EDA is based on the fundamental electrical principle of **[[https://en.wikipedia.org/wiki/Ohm's_law\|Ohm’s Law]]** //(V = IR)//, which states that the current //(I)// flowing through a conductor between two points is directly proportional to the voltage //(V)// across the two points and inversely proportional to the resistance //(R)// of the conductor. If current is held constant between two electrodes, voltage will vary in proportion to the varying resistance of the skin, producing an output proportional to skin conductance. Likewise, if voltage is held constant between two electrodes applied to the skin, the current will vary in proportion to the varying resistance of the skin, producing an output proportional to skin resistance.
  
-Skin electrical activity can be measured using endosomatic or exosomatic methods. +Skin electrical activity can be measured using **endosomatic** or **exosomatic methods**
  
-Endosomatic methods measure potential differences at various points on the skin surface without application of external electrical current. Endosomatic methods are not commonly used, given that they often produce bipolar signals that are complex waveforms, rendering the measurements taken difficult to score and interpret.+**Endosomatic methods** measure potential differences at various points on the skin surface without application of external electrical current. **Endosomatic methods** are not commonly used, given that they often produce bipolar signals that are complex waveforms, rendering the measurements taken difficult to score and interpret.
  
-Exosomatic methods use an external electrical source to pass a small alternating current (AC) or direct current (DC) through the skin to measure the electric resistance to this current. The most commonly used method is an exosomatic one in which skin conductance (the reciprocal of skin resistance) is measured. Generally, exosomatic methods that use DC are most commonly used, and measurement of skin conductance is more common than measurement of resistance.+**Exosomatic methods** use an external electrical source to pass a small alternating current (AC) or direct current (DC) through the skin to measure the electric resistance to this current. The most commonly used method is an **exosomatic** one in which skin conductance (the reciprocal of skin resistance) is measured. Generally, exosomatic methods that use DC are most commonly used, and measurement of skin conductance is more common than measurement of resistance.
  
-EDA data consists of two primary components: Tonic Skin Conductance Level (SCL) and Phasic Skin Conductance Response (SCR).+EDA data consists of two primary components: **Tonic Skin Conductance Level (SCL)** and **Phasic Skin Conductance Response (SCR)**.
  
-SCL shows patterns of slow variation over tens of seconds to minutes, and is constantly changing based on individuals’ hydration, skin moisture, and autonomic regulation. SCL varies notably across individuals, and may not be useful when examined independent of SCR.+**SCL** shows patterns of slow variation over tens of seconds to minutes, and is constantly changing based on individuals’ hydration, skin moisture, and autonomic regulation. **SCL** varies notably across individuals, and may not be useful when examined independent of **SCR**.
  
-SCR alternates more quickly, showing characteristic EDA bursts or peaks (Event-Related SCR; ER-SCR), and is sensitive to emotional stimulus events. Peaks typically follow the presentation of emotional stimuli within the range of 1 to 5 seconds. SCR can also be spontaneous, non-specific, and unrelated to external stimuli. These spontaneous responses (Non-Specific SCR; NS-SCR) occur approximately one to three times per minute.+**SCR** alternates more quickly, showing characteristic EDA bursts or peaks (**Event-Related SCR****ER-SCR**), and is sensitive to emotional stimulus events. Peaks typically follow the presentation of emotional stimuli within the range of 1 to 5 seconds. **SCR** can also be spontaneous, non-specific, and unrelated to external stimuli. These spontaneous responses (**Non-Specific SCR****NS-SCR**) occur approximately one to three times per minute.
  
-{{ :sensors:eda-01-typicalmeasures.png?400 |https://sensorwiki.org/?ns=sensors%3A&image=sensors%3Aeda-01-typicalmeasures.png&do=media}} +{{:sensors:eda-01-typicalmeasures.png?600|}}
-//Typical electrodermal measures, definitions, and values (Dawson et al., 2012)//+
  
 +//Typical electrodermal measures, definitions, and values [[https://www.cambridge.org/core/books/handbook-of-psychophysiology/electrodermal-system/90AB2EBAA435385B2FC2BB6C05D4B880\|(Dawson et al., 2012)]]//
  
-https://sensorwiki.org/?ns=sensors%3A&image=sensors%3Aeda-02-phasic_tonic.png&do=media + 
-//Phasic & Tonic Conductance Components (iMotions, 2017)//+{{:sensors:eda-02-phasic_tonic.png?600|}} 
 + 
 +//Phasic & Tonic Conductance Components [[https://imotions.com/guides/eda-gsr\|(iMotions, 2017)]]//
  
 ===== Measuring EDA ===== ===== Measuring EDA =====
  
-EDA is measured using two electrodes placed on the surface of the skin, often in the form of a patch sticker (which requires conductive gel) or embedded within a velcro strap. Electrodes are often made of Silver/Silver-Chloride (Ag/AgCl; most common) or Zinc/Zinc Sulphate (Zn/ZnSO4). The Ag/AgCl electrode pair is reversible, minimizing concerns related to bias potentials and polarization, which could potentially induce artifacts in the output signal.+EDA is measured using two electrodes placed on the surface of the skin, often in the form of a patch sticker (which requires conductive gel) or embedded within a velcro strap. Electrodes are often made of Silver/Silver-Chloride (Ag/AgCl; most common) or Zinc/Zinc Sulphate (Zn/ZnSO<sub>4</sub>). The Ag/AgCl electrode pair is reversible, minimizing concerns related to bias potentials and polarization, which could potentially induce artifacts in the output signal.
  
-EDA sensors typically include two electrodes, an amplifier to increase signal amplitude, and an analog-to-digital converter. Wireless sensor systems will also contain modules for data transmission. Various sensors exist with different technical specifications, sensor placement options, and software compatibility. While some systems will allow arbitrary sensor placement, others will be more restrictive, such as those in which electrodes are embedded in finger or wrist straps. Sensors have even been created using the LEGO MINDSTORMS robotics system.+EDA sensors typically include two electrodes, an amplifier to increase signal amplitude, and an analog-to-digital converter. Wireless sensor systems will also contain modules for data transmission. Various sensors exist with different technical specifications, sensor placement options, and software compatibility. While some systems will allow arbitrary sensor placement, others will be more restrictive, such as those in which electrodes are embedded in finger or wrist straps. Sensors have even been created using the [[https://www.lego.com/en-us/themes/mindstorms/about\|LEGO MINDSTORMS]] robotics system.
  
-https://sensorwiki.org/?ns=sensors%3A&image=sensors%3Aeda-03-mindstorms.png&do=media +{{:sensors:eda-03-mindstorms.png?600|}} 
-//EDA measurement using LEGO MINDSTORMS (Sharma et al., 2016)//+ 
 +//EDA measurement using [[https://www.lego.com/en-us/themes/mindstorms/about\|LEGO MINDSTORMS]] [[https://doi.org/10.21276/ijmrp.2016.2.6.003 |(Sharma et al., 2016)]]//
  
 EDA sensors are often combined with other biometric sensors such as eye tracking, facial expression analysis, electroencephalography, electromyography, and electrocardiography in larger sensing interfaces. These multi-sensing devices can provide more detail related to individual experience and psychophysical response than EDA alone. EDA sensors are often combined with other biometric sensors such as eye tracking, facial expression analysis, electroencephalography, electromyography, and electrocardiography in larger sensing interfaces. These multi-sensing devices can provide more detail related to individual experience and psychophysical response than EDA alone.
Line 59: Line 62:
 ===== EDA Sensor Setup & Calibration ===== ===== EDA Sensor Setup & Calibration =====
  
-The areas of skin most responsive to emotional stimuli are good candidates for EDA measurement electrode placement. These areas include the fingers, the palms of the hands, and the soles of the feet. In a study of EDA electrode placement on different parts of the body, Van Dooren et al. (2012) suggest a number of other positions for electrodes, including the forehead, shoulders, neck, calf, wrist, and chest, which may be more suitable for situations in which an individual is ambulatory.+The areas of skin most responsive to emotional stimuli are good candidates for EDA measurement electrode placement. These areas include the fingers, the palms of the hands, and the soles of the feet. In a study of EDA electrode placement on different parts of the body, [[https://doi.org/10.1016/j.physbeh.2012.01.020|Van Dooren et al. (2012)]] suggest a number of other positions for electrodes, including the forehead, shoulders, neck, calf, wrist, and chest, which may be more suitable for situations in which an individual is ambulatory.
  
 When placing electrodes on the fingers, it is common to take measurements from the index and middle finger of an individual’s non-dominant hand, such that the individual can still perform tasks with their dominant hand. In cases where users require full use of both hands, electrodes placed on the palm can be a good choice. When individuals must use both hands extensively, it can be preferable to take measurements from the feet. In these cases, electrodes should be placed on the side of the foot since the soles can be significantly affected by pressure when individuals are standing or walking. When placing electrodes on the fingers, it is common to take measurements from the index and middle finger of an individual’s non-dominant hand, such that the individual can still perform tasks with their dominant hand. In cases where users require full use of both hands, electrodes placed on the palm can be a good choice. When individuals must use both hands extensively, it can be preferable to take measurements from the feet. In these cases, electrodes should be placed on the side of the foot since the soles can be significantly affected by pressure when individuals are standing or walking.
  
-https://sensorwiki.org/?ns=sensors%3A&image=sensors%3Aeda-04-palmfingers.png&do=media +{{:sensors:eda-04-palmfingers.png?600|}} 
-//Electrode placement for palm and fingers (iMotions. 2017)//+ 
 +//Electrode placement for palm and fingers [[https://imotions.com/guides/eda-gsr|(iMotions. 2017)]]// 
 + 
 +{{:sensors:eda-05-foot.png?600|}}
  
-https://sensorwiki.org/?ns=sensors%3A&image=sensors%3Aeda-05-foot.png&do=media +//Electrode placement for the sole of the foot [[https://imotions.com/guides/eda-gsr|(iMotions, 2017)]]//
-//Electrode placement for the sole of the foot (iMotions, 2017)//+
  
 It can also be useful to treat the skin area where the electrodes are to be applied. In cases of oily skin, it can be useful to use 70% isopropanol for cleaning to optimize sensor stability. In cases of very dry skin, adding skin moisturizer can be beneficial. It can also be useful to treat the skin area where the electrodes are to be applied. In cases of oily skin, it can be useful to use 70% isopropanol for cleaning to optimize sensor stability. In cases of very dry skin, adding skin moisturizer can be beneficial.
Line 75: Line 80:
 In order to avoid muscular artifacts, individuals should breathe normally, minimize unnecessary limb movements, and avoid talking. They should be seated in a comfortable position with feet flat on the ground, thighs parallel to the floor, and adequate lumbar support.  In order to avoid muscular artifacts, individuals should breathe normally, minimize unnecessary limb movements, and avoid talking. They should be seated in a comfortable position with feet flat on the ground, thighs parallel to the floor, and adequate lumbar support. 
  
-For circumstances in which EDA measurement quality is adversely affected by vigorous movement, Westyn et al. (2006) developed a galvanic-skin response accelerometer (ActionEDA), designed to separate desired signals from extraneous motion artifacts.+For circumstances in which EDA measurement quality is adversely affected by vigorous movement, [[https://doi.org/10.1109/ISWC.2006.286360|Westyn et al. (2006)]] developed a galvanic-skin response accelerometer (ActionEDA), designed to separate desired signals from extraneous motion artifacts.
  
 ===== Sensor Use Considerations ===== ===== Sensor Use Considerations =====
  
-Boucsein (2012) suggests a standard methodology for skin conductance recording using a Silver/Silver Chloride (Ag/AgCl) electrode pair with an electrode surface area of 0.5 cm2 to 1 cm2. This methodology uses DC with a 0.5 V constant voltage or a constant current of 10 μA/cm2.+[[https://doi.org/10.1007/978-1-4614-1126-0|Boucsein (2012)]] suggests a standard methodology for skin conductance recording using a Silver/Silver Chloride (Ag/AgCl) electrode pair with an electrode surface area of 0.5 cm<sup>2</sup> to 1 cm<sup>2</sup>. This methodology uses DC with a 0.5 V constant voltage or a constant current of 10 μA/cm<sup>2</sup>.
  
 EDA measurements can be affected by a number of technical, environmental, and individual factors including density of applied current, electrode composition and size, contact medium, electronic circuitry, ambient temperature, skin temperature, skin cuts, and abrasions. These factors can contribute additional variance to the EDA output signal, and should be considered and controlled for, if possible. EDA measurements can be affected by a number of technical, environmental, and individual factors including density of applied current, electrode composition and size, contact medium, electronic circuitry, ambient temperature, skin temperature, skin cuts, and abrasions. These factors can contribute additional variance to the EDA output signal, and should be considered and controlled for, if possible.
Line 107: Line 112:
 More complex data can also be calculated and examined, including number of response peaks, peak amplitude, rise duration, peak area, accumulative EDA, and frequency power. More complex data can also be calculated and examined, including number of response peaks, peak amplitude, rise duration, peak area, accumulative EDA, and frequency power.
  
-https://sensorwiki.org/?ns=sensors%3A&image=sensors%3Aeda-06-responsepeak.png&do=media +{{:sensors:eda-06-responsepeak.png?600|}} 
-//EDA response peak components (iMotions, 2017)//+ 
 +//EDA response peak components [[https://imotions.com/guides/eda-gsr|(iMotions, 2017)]]//
  
 ===== Signal Processing ===== ===== Signal Processing =====
Line 117: Line 123:
  
 When measuring biosignals, there is typically a need to remove noise from a measurement in order to increase the signal-to-noise ratio. For EDA, a basic median filter can be used to smooth the EDA data and remove the tonic component of the signal which is unrelated to the stimulus-response peaks. When measuring biosignals, there is typically a need to remove noise from a measurement in order to increase the signal-to-noise ratio. For EDA, a basic median filter can be used to smooth the EDA data and remove the tonic component of the signal which is unrelated to the stimulus-response peaks.
 +
 Automatic detection algorithms can be used to identify peak amplitudes, onsets, and offsets using various thresholds. Automatic detection algorithms can be used to identify peak amplitudes, onsets, and offsets using various thresholds.
  
-Various software solutions exist to collect process EDA data, including iMotionss Biometric Research Platform, BioPac AcqKnowledge, Ledalab and PsPM toolboxes for Matlab, and AdInstruments PowerLab and LabChart. The Society for Psychophysiological Research also hosts a software repository with a selection of programs for scoring EDA.+Various software solutions exist to collect process EDA data, including [[https://imotions.com/platform|iMotions Biometric Research Platform]][[https://imotions.com/platform|BioPac AcqKnowledge]][[http://www.ledalab.de|Ledalab]] and [[https://bachlab.github.io/PsPM|PsPM]] toolboxes for Matlab, and AdInstruments [[https://www.adinstruments.com/products/labchart|LabChart]]. The [[https://sprweb.org|Society for Psychophysiological Research]] also hosts a [[https://sprweb.org/page/Resources|software repository]] with a selection of programs for scoring EDA.
  
 ===== Applications & Uses ===== ===== Applications & Uses =====
Line 135: Line 142:
 The use of EDA measures and other biosensors can allow for non-invasive measurement of individuals of cognitive and affective states while not interrupting the performance of other tasks. This can allow for the development of affective computing systems that dynamically respond to users’ cognitive and affective state in real time. In many cases, feature extraction alone may be all that is required from EDA data; however, machine learning algorithms are useful when considering systems that need to adapt and respond to changing EDA measurements in real-time. The use of EDA measures and other biosensors can allow for non-invasive measurement of individuals of cognitive and affective states while not interrupting the performance of other tasks. This can allow for the development of affective computing systems that dynamically respond to users’ cognitive and affective state in real time. In many cases, feature extraction alone may be all that is required from EDA data; however, machine learning algorithms are useful when considering systems that need to adapt and respond to changing EDA measurements in real-time.
  
-One notable affective computing application comes from the MIT Media Lab. Healey & Picard’s StartleCam is a wearable camera uses EDA data to determine startle responses. When a startle response is detected, images recently captured by the wearable camera are downloaded or transmitted to a web server, providing a technological metaphor for flashbulb memories.+One notable affective computing application is [[https://doi.org/10.1109/ISWC.1998.729528|Healey & Picard’s (1998) StartleCam]], a wearable camera uses EDA data to determine startle responses. When a startle response is detected, images recently captured by the wearable camera are downloaded or transmitted to a web server, providing a technological metaphor for flashbulb memories.
  
-EDA sensors have been used in number of musical applications. One notable example is Teresa Marrin Nakra’s Conductor’s Jacket, developed at the MIT Media Lab in order to collect gestural and physiological data from orchestral conductors during musical performances.+EDA sensors have been used in number of musical applications. One notable example is [[https://www.researchgate.net/publication/2344811_The_Conductor%27s_Jacket_A_Device_For_Recording_Expressive_Musical_Gestures|Teresa Marrin Nakra’s (2000) Conductor’s Jacket]]which collects gestural and physiological data from orchestral conductors during musical performances.
  
-Knapp & Bortz’ (2011) MobileMuse is a custom hardware technology that can be linked to a mobile device for biometric emotion sensing that combines measurements of EDA with oximetry, temperature, and accelerometer sensors for gestural and emotional control of musical sound generation.+[[http://doi.org/10.5281/zenodo.1178073|Knapp & Bortz’ (2011) MobileMuse]] is a custom hardware technology that can be linked to a mobile device for biometric emotion sensing that combines measurements of EDA with oximetry, temperature, and accelerometer sensors for gestural and emotional control of musical sound generation.
  
-EDA sensors were also used in Müller et al.’s (2011) Skintimacy system to provide values to be mapped to sound variables in an interface for collaborative music performance.+EDA sensors were also used in [[https://doi.org/10.1145/1935701.1935801|Müller et al.’s (2011) Skintimacy]] system to provide values to be mapped to sound variables in an interface for collaborative music performance.
  
-With the rise of wearable technology, EDA sensors are also becoming more prevalent in fitness and wellness technologies, such as the Fitbit Sense, which utilizes an EDA sensor to measure stress levels. EDA sensors are particularly well-suited to wearable technology, given that they must be in physical contact with the skin. Sensors can also be embedded into clothing.+With the rise of wearable technology, EDA sensors are also becoming more prevalent in fitness and wellness technologies, such as the [[https://www.fitbit.com/global/us/products/smartwatches/sense|Fitbit Sense]], which utilizes an EDA sensor to measure stress levels. EDA sensors are particularly well-suited to wearable technology, given that they must be in physical contact with the skin. Sensors can also be embedded into clothing.
  
 ===== Further Reading ===== ===== Further Reading =====
  
-For those seeking a more detailed resource on this topic, Wolfram Boucsein (2012) has written an extensive book on electrodermal activity, describing the history of EDA measurement, underlying biological and electrical phenomena, measurement methods, and applications. A shorter primer on the topic by Dawson et al. (2016) provide a more condensed overview of EDA mechanisms and measurement.+For those seeking a more detailed resource on this topic, [[https://doi.org/10.1007/978-1-4614-1126-0|Wolfram Boucsein (2012)]] has written an extensive book on electrodermal activity, describing the history of EDA measurement, underlying biological and electrical phenomena, measurement methods, and applications. A shorter primer on the topic by [[https://doi.org/10.1017/9781107415782.010|Dawson et al. (2016)]] provide a more condensed overview of EDA mechanisms and measurement.
  
 ===== Available Sensors & Specifications ===== ===== Available Sensors & Specifications =====
Line 156: Line 163:
 |company=BioPac |company=BioPac
 |model=SS57LA |model=SS57LA
-|sources=[[https://www.biopac.com/product/eda-lead-bsl/\|BioPac]]+|sources=[[https://www.biopac.com/product/eda-lead-bsl/\|BioPac]] 252.00 - 318.00 USD
 |description=EDA Electrode Leads |description=EDA Electrode Leads
 |datasheet=None |datasheet=None
Line 167: Line 174:
 |company=Biosignalsplux |company=Biosignalsplux
 |model=Electrodermal Activity (EDA) |model=Electrodermal Activity (EDA)
-|sources=[[https://biosignalsplux.com/products/sensors/electrodermal-activity.html\|Biosignalsplux]]+|sources=[[https://biosignalsplux.com/products/sensors/electrodermal-activity.html\|Biosignalsplux]] 95.00 EUR
 |description=EDA Electrode Leads |description=EDA Electrode Leads
 |datasheet=[[https://biosignalsplux.com/downloads/docs/datasheets/Electrodermal_Activity_(EDA)_Datasheet.pdf\|Datasheet]] |datasheet=[[https://biosignalsplux.com/downloads/docs/datasheets/Electrodermal_Activity_(EDA)_Datasheet.pdf\|Datasheet]]
Line 178: Line 185:
 |company=BITalino |company=BITalino
 |model=EDA Sensor |model=EDA Sensor
-|sources=[[https://plux.info/sensors/11-electrodermal-activity-eda-sensor.html\|BITalino]]+|sources=[[https://plux.info/sensors/11-electrodermal-activity-eda-sensor.html\|BITalino]] 25.00 EUR
 |description=Arduino-compatible EDA sensor |description=Arduino-compatible EDA sensor
 |datasheet=[[https://bitalino.com/storage/uploads/media/eda-sensor-datasheet-assembled.pdf\|Datasheet]] |datasheet=[[https://bitalino.com/storage/uploads/media/eda-sensor-datasheet-assembled.pdf\|Datasheet]]
Line 189: Line 196:
 |company=Empatica |company=Empatica
 |model=E4 |model=E4
-|sources=[[https://www.empatica.com/en-eu/research/e4/\|Empatica]]+|sources=[[https://www.empatica.com/en-eu/research/e4/\|Empatica]] 1,690.00 USD
 |description=Wearable bracelet with sensors for EDA and other physiological phenomena |description=Wearable bracelet with sensors for EDA and other physiological phenomena
 |datasheet=[[https://support.empatica.com/hc/en-us/articles/202581999-E4-wristband-technical-specifications\|Datasheet]] |datasheet=[[https://support.empatica.com/hc/en-us/articles/202581999-E4-wristband-technical-specifications\|Datasheet]]
Line 200: Line 207:
 |company=Infusion Systems |company=Infusion Systems
 |model=BioEmo |model=BioEmo
-|sources=[[https://infusionsystems.com/catalog/product_info.php/products_id/203%7CI-CubeX%20BioEmo%20skin%20resistance%20sensor\|Infusion Systems]]+|sources=[[https://infusionsystems.com/catalog/product_info.php/products_id/203%7CI-CubeX%20BioEmo%20skin%20resistance%20sensor\|Infusion Systems]] 46.42 USD
 |description=GSR impedance sensor |description=GSR impedance sensor
 |datasheet=Technical Specifications can be found at [[https://infusionsystems.com/catalog/product_info.php/products_id/203%7CI-CubeX%20BioEmo%20skin%20resistance%20sensor\|Infusion Systems]] |datasheet=Technical Specifications can be found at [[https://infusionsystems.com/catalog/product_info.php/products_id/203%7CI-CubeX%20BioEmo%20skin%20resistance%20sensor\|Infusion Systems]]
Line 211: Line 218:
 |company=Mindfield Biosystems |company=Mindfield Biosystems
 |model=eSense Skin Response |model=eSense Skin Response
-|sources=[[https://mindfield-shop.com/en/product/esense-skin-response/\|Mindfield Biosystems]]+|sources=[[https://mindfield-shop.com/en/product/esense-skin-response/\|Mindfield Biosystems]] 149.00 EUR
 |description=Skin conductance sensor which can send data through phone/tablet microphone jack |description=Skin conductance sensor which can send data through phone/tablet microphone jack
 |datasheet=See [[https://www.mindfield.de/pdf/phocadownload/eSense/English/eSense_Skin_Response_Manual_EN.pdf \|User Manual]] (p. 49-50) for technical specifications |datasheet=See [[https://www.mindfield.de/pdf/phocadownload/eSense/English/eSense_Skin_Response_Manual_EN.pdf \|User Manual]] (p. 49-50) for technical specifications
Line 222: Line 229:
 |company=Movisens |company=Movisens
 |model=EdaMove 4 |model=EdaMove 4
-|sources=[[https://www.movisens.com/en/products/eda-and-activity-sensor/\|Movisens]]+|sources=[[https://www.movisens.com/en/products/eda-and-activity-sensor/\|Movisens]] Price not listed. Request quote on website.
 |description=Bluetooth sensor for collecting various physiological data |description=Bluetooth sensor for collecting various physiological data
 |datasheet=[[https://docs.movisens.com/Sensors/EdaMove4/#technical-data\|Datasheet]] |datasheet=[[https://docs.movisens.com/Sensors/EdaMove4/#technical-data\|Datasheet]]
Line 233: Line 240:
 |company=Seeed Studio |company=Seeed Studio
 |model=GSR Sensor |model=GSR Sensor
-|sources=[[https://wiki.seeedstudio.com/Grove-GSR_Sensor/\|Seeed Studio]]+|sources=[[https://wiki.seeedstudio.com/Grove-GSR_Sensor/\|Seeed Studio]] 9.90 USD
 |description=Arduino-/Raspberry Pi-compatible GSR sensor |description=Arduino-/Raspberry Pi-compatible GSR sensor
 |datasheet=Brief technical specifications are available at [[https://wiki.seeedstudio.com/Grove-GSR_Sensor/\|Seeed Studio]] |datasheet=Brief technical specifications are available at [[https://wiki.seeedstudio.com/Grove-GSR_Sensor/\|Seeed Studio]]
Line 244: Line 251:
 |company=Shimmer Sensing |company=Shimmer Sensing
 |model=Shimmer3 EDA+ |model=Shimmer3 EDA+
-|sources=[[https://www.shimmersensing.com/products/shimmer3-wireless-gsr-sensor\|Shimmer Sensing]]+|sources=[[https://www.shimmersensing.com/products/shimmer3-wireless-gsr-sensor\|Shimmer Sensing]] 428.00 EUR
 |description=Wireless GSR and pulse-sensing system |description=Wireless GSR and pulse-sensing system
 |datasheet=[[https://www.shimmersensing.com/images/uploads/docs/GSR_Plus_Spec_Sheet_v3_4_-.pdf\|Datasheet]] |datasheet=[[https://www.shimmersensing.com/images/uploads/docs/GSR_Plus_Spec_Sheet_v3_4_-.pdf\|Datasheet]]
Line 254: Line 261:
  
 ===== References ===== ===== References =====
 +  * BIOPAC Systems Inc. (2021). //Skin Conductance Response Analysis//. [[https://www.biopac.com/
 +application/electrodermal-activity/advanced-feature/skin-conductance-response-analysis/]]
 +
 +  * Boucsein, W. (2012). //Electrodermal Activity// (2nd ed.). Springer US. [[https://doi.org/10.1007/978-1-4614-1126-0]]
 +
 +  * Braithwaite, J. J., Watson, D. G., Jones, R., & Rowe, M. (2013). //A Guide for Analyzing Electrodermal Activity (EDA) and Skin Conductance Response (SCRs) for Psychological Experiments//. [[https://www.biopac.com/wp-content/uploads/EDA-SCR-Analysis.pdf]]
 +
 +  * Dawson, M. E., Schell, A. M., & Filion, D. L. (2016). The electrodermal system. In Cacioppo, J. T., Tassinary, L. G., Berntson, G. G. (Eds.), //Systematic Psychophysiology// (pp. 217-243). Cambridge University Press. [[https://doi.org/10.1017/9781107415782.010]]
 +
 +  * Edelberg, R. & Burch, N. R. (1962). Skin resistance and galvanic skin response. //Archives of General Psychiatry, 7//(3), 163-169. [[https://doi.org/10.1001/archpsyc.1962.01720030009002]]
 +
 +  * Electrodermal activity (2021, February 13). In Wikipedia. [[https://en.wikipedia.org/wiki/Electrodermal_activity]]
 +
 +  * Essl, G. & Won Lee, S. (2018). Mobile devices as musical instruments - State of the art and future prospects. In //International Symposium on Computer Music Multidisciplinary Research//. (pp. 525-539). Matosinhos, Portugal. [[https://doi.org/10.1007/978-3-030-01692-0]]
 +
 +  * Healey, J. & Picard, R. W. (1998). StartleCam: A cybernetic wearable camera. In //Digest of Papers, International Symposium on Wearable Computers//. (pp. 42-49). Pittsburgh, USA. [[https://doi.org/10.1109/ISWC.1998.729528]]
 +
 +  * iMotions (2017). //Galvanic Skin Response: The Complete Pocket Guide//. [[https://imotions.com/guides/eda-gsr/]]
 +
 +  * Knapp, R. B., & Bortz, B. (2011). MobileMuse: Integral music control goes mobile. In //Proceedings of the International Conference on New Interfaces for Musical Expression//. (pp. 203-206). Oslo, Norway. [[http://doi.org/10.5281/zenodo.1178073]]
 +
 +  * Marrin Nakra, T. (2000). Searching for meaning in gestural data: Interpretive feature extraction and signal processing for affective and expressive content. In Wanderley, M. M. & Battier, M. (Eds.). //Trends in Gestural Control of Music// (pp. 415-438). Paris: IRCAM, Centre Pompidou
 +
 +  * Miranda, E. R. & Wanderley, M. M. (2006). Biosignal interfaces. In Miranda, E. R. & Wanderley, M. M. (Eds.), //New Digital Musical Instruments: Control and Interaction Beyond the Keyboard// (pp. 173-217). A-R Editions. 
 +
 +  * Müller, A., Fuchs, J., & Röpke, K. (2011). Skintimacy: Exploring interpersonal boundaries through musical interactions. In //Proceedings of the International Conference on Tangible and Embedded Interaction//. (pp. 403-404). Funchal, Portugal. [[https://doi.org/10.1145/1935701.1935801]]
 +
 +  * Nourbakhsh, N., Chen, F., Wang, Y., & Calvo, R. A. (2017). Detecting users’ cognitive load by galvanic skin response with affective interference. //The ACM Transactions on Interactive Intelligent Systems, 7//(3), Article 12. [[https://doi.org/10.1145/2960413]]
 +
 +  * Picard, R. W. (1997).// Affective Computing//. The MIT Press.
 +
 +  * Sharma, M., Kacker, S., & Sharma, M. (2016). A brief introduction and review on galvanic skin response. //International Journal of Medical Research Professionals, 2//(6), 13-17. [[https://doi.org/10.21276/ijmrp.2016.2.6.003]]
 +
 +  * Van Dooren, M., de Vries, J. J. G., & Janssen, J. H. (2012). Emotional sweating across the body: Comparing 16 different skin conductance measurement locations. //Physiology & Behavior, 106//(2), 298-304. [[https://doi.org/10.1016/j.physbeh.2012.01.020]]
 +
 +  * Westyn, T., Presti, P., & Starner, T. (2006). ActionGSR: A combination galvanic skin response-accelerometer for physiological measurements in active environments. In //Proceedings of the IEEE International Symposium of Wearable Computers//. (pp. 129-130). Montreux, Switzerland. [[https://doi.org/10.1109/ISWC.2006.286360]]
 +
 +  * Yuksel, B. F., Oleson, K. B., Chang, R., & Jacob, R. J. K. (2019). Detecting and adapting to  users’ cognitive and affective state to develop intelligent musical interfaces. In Holland, S., Mudd, T., Wilkie-McKenna, K., McPherson, A., & Wanderley, M. M. (Eds.). //New Directions in Music and Human-Computer Interaction// (pp. 115-120). Springer Nature. [[https://doi.org/10.1007/978-3-319-92069-6_11]]
  
 +  * Zhou, F. & Jianxin Jiao, R. (2013). Eliciting, measuring, and predicting affect via physiological measures for emotional design. In Fukuda, S. (Eds.), //Emotional Engineering vol. 2// (41-62). Springer, London. [[https://doi.org/10.1007/978-1-4471-4984-2_4]]
  
  
 {{tag>Sensor Biosignal}} {{tag>Sensor Biosignal}}