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sensors:galvanic_skin_response [2021/03/22 02:00]
charles.reimer
sensors:galvanic_skin_response [2021/03/24 15:39] (current)
charles.reimer [Available Sensors & Specifications]
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 {{:sensors:eda-02-phasic_tonic.png?600|}} {{:sensors:eda-02-phasic_tonic.png?600|}}
  
-//Phasic & Tonic Conductance Components [[https://imotions.com/guides/eda-gsr/\|(iMotions, 2017)]]//+//Phasic & Tonic Conductance Components [[https://imotions.com/guides/eda-gsr\|(iMotions, 2017)]]//
  
 ===== Measuring EDA ===== ===== Measuring EDA =====
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 {{:sensors:eda-03-mindstorms.png?600|}} {{:sensors:eda-03-mindstorms.png?600|}}
  
-//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 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.
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 ===== 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, [[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.+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.
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 {{:sensors:eda-04-palmfingers.png?600|}} {{:sensors:eda-04-palmfingers.png?600|}}
  
-//Electrode placement for palm and fingers [[https://imotions.com/guides/eda-gsr/\|(iMotions. 2017)]]//+//Electrode placement for palm and fingers [[https://imotions.com/guides/eda-gsr|(iMotions. 2017)]]//
  
 {{:sensors:eda-05-foot.png?600|}} {{:sensors:eda-05-foot.png?600|}}
  
-//Electrode placement for the sole of the foot [[https://imotions.com/guides/eda-gsr/\|(iMotions, 2017)]]//+//Electrode placement for the sole of the foot [[https://imotions.com/guides/eda-gsr|(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.
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 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, [[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.+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 =====
  
-[[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 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.
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 {{:sensors:eda-06-responsepeak.png?600|}} {{:sensors:eda-06-responsepeak.png?600|}}
  
-//EDA response peak components [[https://imotions.com/guides/eda-gsr/\|(iMotions, 2017)]]//+//EDA response peak components [[https://imotions.com/guides/eda-gsr|(iMotions, 2017)]]//
  
 ===== Signal Processing ===== ===== Signal Processing =====
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 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 [[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.+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 =====
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 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 [[https://www.media.mit.edu\|MIT Media Lab]]. [[https://doi.org/10.1109/ISWC.1998.729528 \|Healey & Picard’s (1998) 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 [[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]], developed at the [[https://www.media.mit.edu\|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.
  
-[[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.+[[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 [[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.+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 [[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.+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, [[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.+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 =====
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 |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
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 |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]]
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 |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]]
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 |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]]
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 |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]]
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 |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
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 |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 240: 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]]
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 |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]]
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   * 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]]   * 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]]+  * 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.   * Picard, R. W. (1997).// Affective Computing//. The MIT Press.