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Home / Equine Research Bank / Animals (Basel) / Sympathetic Arousal Detection in Horses Using Electrodermal ...
Animals : an open access journal from MDPI2023; 13(2); 229; doi: 10.3390/ani13020229

Sympathetic Arousal Detection in Horses Using Electrodermal Activity.

Abstract: The continuous monitoring of stress, pain, and discomfort is key to providing a good quality of life for horses. The available tools based on observation are subjective and do not allow continuous monitoring. Given the link between emotions and sympathetic autonomic arousal, heart rate and heart rate variability are widely used for the non-invasive assessment of stress and pain in humans and horses. However, recent advances in pain and stress monitoring are increasingly using electrodermal activity (EDA), as it is a more sensitive and specific measure of sympathetic arousal than heart rate variability. In this study, for the first time, we have collected EDA signals from horses and tested the feasibility of the technique for the assessment of sympathetic arousal. Fifteen horses (six geldings, nine mares, aged 13.11 ± 5.4 years) underwent a long-lasting stimulus (Feeding test) and a short-lasting stimulus (umbrella Startle test) to elicit sympathetic arousal. The protocol was approved by the University of Connecticut. We found that EDA was sensitive to both stimuli. Our results show that EDA can capture sympathetic activation in horses and is a promising tool for non-invasive continuous monitoring of stress, pain, and discomfort in horses.
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Publication Date: 2023-01-07 PubMed ID: 36670768PubMed Central: PMC9855141DOI: 10.3390/ani13020229Google Scholar: Lookup
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Summary

This research summary has been generated with artificial intelligence and may contain errors and omissions. Refer to the original study to confirm details provided. Submit correction.

This research was conducted to test the feasibility of using Electrodermal Activity (EDA) signals as a means of detecting sympathetic arousal in horses—an indication of stress, pain, and discomfort.

Objective and Background

  • The study aimed to develop a more objective, continuous monitoring method for assessing horses’ quality of life, using EDA as a gauge for sympathetic arousal.
  • Previously, heart rate and heart rate variability were the main non-invasive measures used to assess horses’ stress and pain, but these are less sensitive and specific than EDA.
  • Existing observational tools were deemed subjective and do not allow consistent monitoring, which created a demand for a more reliable, continuous method.

Methodology

  • In this pioneer research, EDA signals from fifteen horses of different gender and age groups were collected to test the technique’s effectiveness.
  • Two stimuli were used to elicit sympathetic arousal: a long-lasting feeding test and a short-lasting umbrella startle test.
  • All procedures were carried out under the approval and oversight of the University of Connecticut.

Results and Conclusion

  • The study revealed that EDA is sensitive to both long-lasting and short-lasting stimuli in horses, proving its efficacy in capturing sympathetic activation.
  • This result leads the researchers to posit that EDA is a promising tool for the non-invasive, continuous monitoring of stress, pain, and discomfort in horses.

In conclusion, this trailblazing research asserts the potential of EDA as a more precise and reliable tool for assessing stress, pain, and discomfort in horses. Its sensitivity to different stimuli supports the notion of continuous and non-invasive monitoring, contributing significantly to improving horses’ quality of life.

Cite This Article

APA
Golzari K, Kong Y, Reed SA, Posada-Quintero HF. (2023). Sympathetic Arousal Detection in Horses Using Electrodermal Activity. Animals (Basel), 13(2), 229. https://doi.org/10.3390/ani13020229

Publication

Animals : an open access journal from MDPI
ISSN: 2076-2615
NlmUniqueID: 101635614
Country: Switzerland
Language: English
Volume: 13
Issue: 2
PII: 229

Researcher Affiliations

Golzari, Kia
  • Department of Biomedical Engineering, University of Connecticut, Storrs, CT 06269, USA.
Kong, Youngsun
  • Department of Biomedical Engineering, University of Connecticut, Storrs, CT 06269, USA.
Reed, Sarah A
  • Department of Animal Science, University of Connecticut, Storrs, CT 06269, USA.
Posada-Quintero, Hugo F
  • Department of Biomedical Engineering, University of Connecticut, Storrs, CT 06269, USA.

Conflict of Interest Statement

The authors declare no conflict of interest.

References

This article includes 66 references
  1. Möstl E, Palme R. Hormones as indicators of stress.. Domest Anim Endocrinol 2002 Jul;23(1-2):67-74.
    doi: 10.1016/S0739-7240(02)00146-7pubmed: 12142227google scholar: lookup
  2. Sanmartín Sánchez L, Blanco-Penedo I, Perea Muñoz J.M., Quiñones Pérez C, Delgado J.V., Vega-Pla J.L.. Welfare assessment at a Spanish Army Equine Breeding Centre. Ital. J. Anim. Sci. 2020;19:137–146.
    doi: 10.1080/1828051X.2019.1706433google scholar: lookup
  3. Kaufman J.M.. Investigation of Pain in Equine Patients Using Heart Rate Variability, Salivary Cortisol Concentration, and Behavioural Pain Scores. 2022.
  4. Lesimple C. Indicators of Horse Welfare: State-of-the-Art.. Animals (Basel) 2020 Feb 13;10(2).
    doi: 10.3390/ani10020294pmc: PMC7070675pubmed: 32069888google scholar: lookup
  5. Visser EK, van Reenen CG, van der Werf JT, Schilder MB, Knaap JH, Barneveld A, Blokhuis HJ. Heart rate and heart rate variability during a novel object test and a handling test in young horses.. Physiol Behav 2002 Jun 1;76(2):289-96.
    doi: 10.1016/S0031-9384(02)00698-4pubmed: 12044602google scholar: lookup
  6. Physick-Sheard PW, Marlin DJ, Thornhill R, Schroter RC. Frequency domain analysis of heart rate variability in horses at rest and during exercise.. Equine Vet J 2000 May;32(3):253-62.
    doi: 10.2746/042516400776563572pubmed: 10836482google scholar: lookup
  7. Posada-Quintero HF, Florian JP, Orjuela-Cañón ÁD, Chon KH. Highly sensitive index of sympathetic activity based on time-frequency spectral analysis of electrodermal activity.. Am J Physiol Regul Integr Comp Physiol 2016 Sep 1;311(3):R582-91.
    doi: 10.1152/ajpregu.00180.2016pubmed: 27440716google scholar: lookup
  8. Shaffer F, Ginsberg JP. An Overview of Heart Rate Variability Metrics and Norms.. Front Public Health 2017;5:258.
    doi: 10.3389/fpubh.2017.00258pmc: PMC5624990pubmed: 29034226google scholar: lookup
  9. Mitchell KJ, Schwarzwald CC. Heart rate variability analysis in horses for the diagnosis of arrhythmias.. Vet J 2021 Feb;268:105590.
    doi: 10.1016/j.tvjl.2020.105590pubmed: 33468305google scholar: lookup
  10. Calvert CA, Jacobs GJ. Heart rate variability in Doberman Pinschers with and without echocardiographic evidence of dilated cardiomyopathy.. Am J Vet Res 2000 May;61(5):506-11.
    doi: 10.2460/ajvr.2000.61.506pubmed: 10803644google scholar: lookup
  11. Spier AW, Meurs KM. Assessment of heart rate variability in Boxers with arrhythmogenic right ventricular cardiomyopathy.. J Am Vet Med Assoc 2004 Feb 15;224(4):534-7.
    doi: 10.2460/javma.2004.224.534pubmed: 14989545google scholar: lookup
  12. Abbott JA. Heart rate and heart rate variability of healthy cats in home and hospital environments.. J Feline Med Surg 2005 Jun;7(3):195-202.
    doi: 10.1016/j.jfms.2004.12.003pubmed: 15922226google scholar: lookup
  13. Rowan WH 3rd, Campen MJ, Wichers LB, Watkinson WP. Heart rate variability in rodents: uses and caveats in toxicological studies.. Cardiovasc Toxicol 2007;7(1):28-51.
    doi: 10.1007/s12012-007-0004-6pubmed: 17646680google scholar: lookup
  14. von Borell E, Langbein J, Després G, Hansen S, Leterrier C, Marchant J, Marchant-Forde R, Minero M, Mohr E, Prunier A, Valance D, Veissier I. Heart rate variability as a measure of autonomic regulation of cardiac activity for assessing stress and welfare in farm animals -- a review.. Physiol Behav 2007 Oct 22;92(3):293-316.
    doi: 10.1016/j.physbeh.2007.01.007pubmed: 17320122google scholar: lookup
  15. Moïse NS, Gladuli A, Hemsley SA, Otani NF. "Zone of avoidance": RR interval distribution in tachograms, histograms, and Poincaré plots of a Boxer dog.. J Vet Cardiol 2010 Dec;12(3):191-6.
    doi: 10.1016/j.jvc.2010.07.001pmc: PMC3184837pubmed: 21036115google scholar: lookup
  16. Rasmussen CE, Falk T, Zois NE, Moesgaard SG, Häggström J, Pedersen HD, Ablad B, Nilsen HY, Olsen LH. Heart rate, heart rate variability, and arrhythmias in dogs with myxomatous mitral valve disease.. J Vet Intern Med 2012 Jan-Feb;26(1):76-84.
    doi: 10.1111/j.1939-1676.2011.00842.xpubmed: 22151356google scholar: lookup
  17. Rasmussen CE, Falk T, Domanjko Petrič A, Schaldemose M, Zois NE, Moesgaard SG, Ablad B, Nilsen HY, Ljungvall I, Höglund K, Häggström J, Pedersen HD, Bland JM, Olsen LH. Holter monitoring of small breed dogs with advanced myxomatous mitral valve disease with and without a history of syncope.. J Vet Intern Med 2014 Mar-Apr;28(2):363-70.
    doi: 10.1111/jvim.12290pmc: PMC4857997pubmed: 24417236google scholar: lookup
  18. Blake RR, Shaw DJ, Culshaw GJ, Martinez-Pereira Y. Poincaré plots as a measure of heart rate variability in healthy dogs.. J Vet Cardiol 2018 Feb;20(1):20-32.
    doi: 10.1016/j.jvc.2017.10.006pubmed: 29277470google scholar: lookup
  19. Moïse NS, Flanders WH, Pariaut R. Beat-to-Beat Patterning of Sinus Rhythm Reveals Non-linear Rhythm in the Dog Compared to the Human.. Front Physiol 2019;10:1548.
    doi: 10.3389/fphys.2019.01548pmc: PMC6990411pubmed: 32038271google scholar: lookup
  20. Thayer JF, Hahn AW, Sollers JJ, van Doornen L, Johnson PJ. Heart rate variability in the horse by ambulatory monitoring.. Biomed Sci Instrum 1997;33:482-5.
    pubmed: 9731407
  21. Rietmann TR, Staﾬher M, Bernasconi P, Auer JA, Weishaupt MA. The association between heart rate, heart rate variability, endocrine and behavioural pain measures in horses suffering from laminitis.. J Vet Med A Physiol Pathol Clin Med 2004 Jun;51(5):218-25.
    doi: 10.1111/j.1439-0442.2004.00627.xpubmed: 15315700google scholar: lookup
  22. Villas-Boas J.D., Dias D.P.M., Trigo P.I., dos Santos Almeida N.A., Queiroz de Almeida F., Alves de Medeiros M. Behavioural, endocrine and cardiac autonomic responses to a model of startle in horses. Appl. Anim. Behav. Sci. 2016;174:76–82.
    doi: 10.1016/j.applanim.2015.10.005google scholar: lookup
  23. Ohmura H, Hiraga A. Effect of restraint inside the transport vehicle on heart rate and heart rate variability in Thoroughbred horses.. J Equine Sci 2022 Apr;33(1):13-17.
    doi: 10.1294/jes.33.13pmc: PMC9018462pubmed: 35510074google scholar: lookup
  24. McD￮ L., Carr L., Montelpare W. An observational evaluation of stress in horses during therapeutic riding sessions. J. Vet. Behav. 2022;49:53–64.
    doi: 10.1016/j.jveb.2021.11.009google scholar: lookup
  25. Rietmann T.R., Stuart A.E.A., Bernasconi P., Staﾬher M., Auer J.A., Weishaupt M.A.. Assessment of mental stress in warmblood horses: Heart rate variability in comparison to heart rate and selected behavioural parameters. Appl. Anim. Behav. Sci. 2004;88:121–136.
    doi: 10.1016/j.applanim.2004.02.016google scholar: lookup
  26. Jansen F, Van der Krogt J, Van Loon K, Avezzù V, Guarino M, Quanten S, Berckmans D. Online detection of an emotional response of a horse during physical activity.. Vet J 2009 Jul;181(1):38-42.
    doi: 10.1016/j.tvjl.2009.03.017pubmed: 19375961google scholar: lookup
  27. Boucsein W. Electrodermal Activity. 2012.
  28. Ellaway PH, Kuppuswamy A, Nicotra A, Mathias CJ. Sweat production and the sympathetic skin response: improving the clinical assessment of autonomic function.. Auton Neurosci 2010 Jun 24;155(1-2):109-14.
    doi: 10.1016/j.autneu.2010.01.008pubmed: 20129828google scholar: lookup
  29. Benedek M, Kaernbach C. A continuous measure of phasic electrodermal activity.. J Neurosci Methods 2010 Jun 30;190(1):80-91.
    doi: 10.1016/j.jneumeth.2010.04.028pmc: PMC2892750pubmed: 20451556google scholar: lookup
  30. Illigens BM, Gibbons CH. Sweat testing to evaluate autonomic function.. Clin Auton Res 2009 Apr;19(2):79-87.
    doi: 10.1007/s10286-008-0506-8pmc: PMC3046462pubmed: 18989618google scholar: lookup
  31. Setz C, Arnrich B, Schumm J, La Marca R, Tröster G, Ehlert U. Discriminating stress from cognitive load using a wearable EDA device.. IEEE Trans Inf Technol Biomed 2010 Mar;14(2):410-7.
    doi: 10.1109/TITB.2009.2036164pubmed: 19906598google scholar: lookup
  32. Healey J.A., Picard R.W.. Detecting stress during real-world driving tasks using physiological sensors. IEEE Trans. Intell. Transp. Syst. 2005;6:156–166.
    doi: 10.1109/TITS.2005.848368google scholar: lookup
  33. Greenfield N.S., Sternbach R.A.. Handbook of Psychophysiology. 1972.
  34. Anaesthesia UK: Autonomic Nervous System. [(accessed on 3 January 2023)]. Available online: https://www.frca.co.uk/article.aspx?articleid=100506.
  35. Posada-Quintero HF, Florian JP, Orjuela-Cañón AD, Aljama-Corrales T, Charleston-Villalobos S, Chon KH. Power Spectral Density Analysis of Electrodermal Activity for Sympathetic Function Assessment.. Ann Biomed Eng 2016 Oct;44(10):3124-3135.
    doi: 10.1007/s10439-016-1606-6pubmed: 27059225google scholar: lookup
  36. Kong Y, Posada-Quintero HF, Chon KH. Sensitive Physiological Indices of Pain Based on Differential Characteristics of Electrodermal Activity.. IEEE Trans Biomed Eng 2021 Oct;68(10):3122-3130.
    doi: 10.1109/TBME.2021.3065218pmc: PMC8483589pubmed: 33705307google scholar: lookup
  37. Posada-Quintero HF, Kong Y, Nguyen K, Tran C, Beardslee L, Chen L, Guo T, Cong X, Feng B, Chon KH. Using electrodermal activity to validate multilevel pain stimulation in healthy volunteers evoked by thermal grills.. Am J Physiol Regul Integr Comp Physiol 2020 Sep 1;319(3):R366-R375.
    doi: 10.1152/ajpregu.00102.2020pmc: PMC7509251pubmed: 32726157google scholar: lookup
  38. Kong Y, Posada-Quintero HF, Chon KH. Real-Time High-Level Acute Pain Detection Using a Smartphone and a Wrist-Worn Electrodermal Activity Sensor.. Sensors (Basel) 2021 Jun 8;21(12).
    doi: 10.3390/s21123956pmc: PMC8227650pubmed: 34201268google scholar: lookup
  39. Greco A., Valenza G., Lazaro J., Garzon-Rey J.M., Aguilo J., De-la-Camara C., Bailon R., Scilingo E.P.. Acute stress state classification based on electrodermal activity modeling. IEEE Trans. Affect. Comput. 2021:1.
    doi: 10.1109/TAFFC.2021.3055294google scholar: lookup
  40. Posada-Quintero HF, Landon CS, Stavitzski NM, Dean JB, Chon KH. Seizures Caused by Exposure to Hyperbaric Oxygen in Rats Can Be Predicted by Early Changes in Electrodermal Activity.. Front Physiol 2021;12:767386.
    doi: 10.3389/fphys.2021.767386pmc: PMC8767060pubmed: 35069238google scholar: lookup
  41. Posada-Quintero HF, Derrick BJ, Winstead-Derlega C, Gonzalez SI, Claire Ellis M, Freiberger JJ, Chon KH. Time-varying Spectral Index of Electrodermal Activity to Predict Central Nervous System Oxygen Toxicity Symptoms in Divers: Preliminary results.. Annu Int Conf IEEE Eng Med Biol Soc 2021 Nov;2021:1242-1245.
    pubmed: 34891512doi: 10.1109/embc46164.2021.9629924google scholar: lookup
  42. Safryghin A, Hebesberger DV, Wascher CAF. Testing for Behavioral and Physiological Responses of Domestic Horses (Equus caballus) Across Different Contexts - Consistency Over Time and Effects of Context.. Front Psychol 2019;10:849.
    doi: 10.3389/fpsyg.2019.00849pmc: PMC6482254pubmed: 31057468google scholar: lookup
  43. Boucsein W, Fowles DC, Grimnes S, Ben-Shakhar G, roth WT, Dawson ME, Filion DL. Publication recommendations for electrodermal measurements.. Psychophysiology 2012 Aug;49(8):1017-34.
    doi: 10.1111/j.1469-8986.2012.01384.xpubmed: 22680988google scholar: lookup
  44. Posada-Quintero HF, Chon KH. Innovations in Electrodermal Activity Data Collection and Signal Processing: A Systematic Review.. Sensors (Basel) 2020 Jan 15;20(2).
    doi: 10.3390/s20020479pmc: PMC7014446pubmed: 31952141google scholar: lookup
  45. Greco A, Valenza G, Lanata A, Scilingo EP, Citi L. cvxEDA: A Convex Optimization Approach to Electrodermal Activity Processing.. IEEE Trans Biomed Eng 2016 Apr;63(4):797-804.
    doi: 10.1109/TBME.2015.2474131pubmed: 26336110google scholar: lookup
  46. Massey F.J., Jr.. The Kolmogorov-Smirnov test for goodness of fit. J. Am. Stat. Assoc. 1951;46:68–78.
    doi: 10.1080/01621459.1951.10500769google scholar: lookup
  47. Miller L.H.. Table of percentage points of Kolmogorov statistics. J. Am. Stat. Assoc. 1956;51:111–121.
    doi: 10.1080/01621459.1956.10501314google scholar: lookup
  48. Wang J., Tsang W.W., Marsaglia G.. Evaluating Kolmogorov’s distribution. J. Stat. Softw. 2003;8:1–4.
  49. Posada-Quintero H.F., Dimitrov T., Moutran A., Park S., Chon K.H.. Analysis of Reproducibility of Noninvasive Measures of Sympathetic Autonomic Control Based on Electrodermal Activity and Heart Rate Variability. IEEE Access 2019;7:22523–22531.
    doi: 10.1109/ACCESS.2019.2899485google scholar: lookup
  50. Posada-Quintero HF, Kong Y, Chon KH. Objective pain stimulation intensity and pain sensation assessment using machine learning classification and regression based on electrodermal activity.. Am J Physiol Regul Integr Comp Physiol 2021 Aug 1;321(2):R186-R196.
    doi: 10.1152/ajpregu.00094.2021pmc: PMC8409909pubmed: 34133246google scholar: lookup
  51. Dalla Costa E, Minero M, Lebelt D, Stucke D, Canali E, Leach MC. Development of the Horse Grimace Scale (HGS) as a pain assessment tool in horses undergoing routine castration.. PLoS One 2014;9(3):e92281.
    doi: 10.1371/journal.pone.0092281pmc: PMC3960217pubmed: 24647606google scholar: lookup
  52. van Loon JP, Van Dierendonck MC. Monitoring acute equine visceral pain with the Equine Utrecht University Scale for Composite Pain Assessment (EQUUS-COMPASS) and the Equine Utrecht University Scale for Facial Assessment of Pain (EQUUS-FAP): A scale-construction study.. Vet J 2015 Dec;206(3):356-64.
    doi: 10.1016/j.tvjl.2015.08.023pubmed: 26526526google scholar: lookup
  53. VanDierendonck MC, van Loon JP. Monitoring acute equine visceral pain with the Equine Utrecht University Scale for Composite Pain Assessment (EQUUS-COMPASS) and the Equine Utrecht University Scale for Facial Assessment of Pain (EQUUS-FAP): A validation study.. Vet J 2016 Oct;216:175-7.
    doi: 10.1016/j.tvjl.2016.08.004pubmed: 27687948google scholar: lookup
  54. Gleerup K.B., Lindegaard C.. Recognition and quantification of pain in horses: A tutorial review. Equine Vet. Educ. 2016;28:47–57.
    doi: 10.1111/eve.12383google scholar: lookup
  55. Ashley FH, Waterman-Pearson AE, Whay HR. Behavioural assessment of pain in horses and donkeys: application to clinical practice and future studies.. Equine Vet J 2005 Nov;37(6):565-75.
    doi: 10.2746/042516405775314826pubmed: 16295937google scholar: lookup
  56. Ask K, Andersen PH, Tamminen LM, Rhodin M, Hernlund E. Performance of four equine pain scales and their association to movement asymmetry in horses with induced orthopedic pain.. Front Vet Sci 2022;9:938022.
    doi: 10.3389/fvets.2022.938022pmc: PMC9411665pubmed: 36032285google scholar: lookup
  57. Anusha AS, Joy J, Preejith SP, Joseph J, Sivaprakasam M. Differential effects of physical and psychological stressors on electrodermal activity.. Annu Int Conf IEEE Eng Med Biol Soc 2017 Jul;2017:4549-4552.
    pubmed: 29060909doi: 10.1109/embc.2017.8037868google scholar: lookup
  58. Al Machot F, Elmachot A, Ali M, Al Machot E, Kyamakya K. A Deep-Learning Model for Subject-Independent Human Emotion Recognition Using Electrodermal Activity Sensors.. Sensors (Basel) 2019 Apr 7;19(7).
    doi: 10.3390/s19071659pmc: PMC6479880pubmed: 30959956google scholar: lookup
  59. Poh M.-Z.. Continuous Assessment of Epileptic Seizures with Wrist-Worn Biosensors. 2011.
  60. Mansour C, Mocci R, Santangelo B, Sredensek J, Chaaya R, Allaouchiche B, Bonnet-Garin JM, Boselli E, Junot S. Performance of the Parasympathetic Tone Activity (PTA) index to predict changes in mean arterial pressure in anaesthetized horses with different health conditions.. Res Vet Sci 2021 Oct;139:43-50.
    doi: 10.1016/j.rvsc.2021.07.005pubmed: 34246942google scholar: lookup
  61. Ruíz-López P, Morgaz J, Quirós-Carmona S, Navarrete-Calvo R, Domínguez JM, Gómez-Villamandos RJ, Granados MM. Parasympathetic Tone Changes in Anesthetized Horses after Surgical Stimulation, and Morphine, Ketamine, and Dobutamine Administration.. Animals (Basel) 2022 Apr 15;12(8).
    doi: 10.3390/ani12081038pmc: PMC9027407pubmed: 35454284google scholar: lookup
  62. Stucke D., Große Ruse M., Lebelt D. Measuring heart rate variability in horses to investigate the autonomic nervous system activity—Pros and cons of different methods. Appl. Anim. Behav. Sci. 2015;166:1–10.
    doi: 10.1016/j.applanim.2015.02.007google scholar: lookup
  63. Kuwahara M, Hashimoto S, Ishii K, Yagi Y, Hada T, Hiraga A, Kai M, Kubo K, Oki H, Tsubone H, Sugano S. Assessment of autonomic nervous function by power spectral analysis of heart rate variability in the horse.. J Auton Nerv Syst 1996 Aug 27;60(1-2):43-8.
    doi: 10.1016/0165-1838(96)00028-8pubmed: 8884694google scholar: lookup
  64. Hossain MB, Kong Y, Posada-Quintero HF, Chon KH. Comparison of Electrodermal Activity from Multiple Body Locations Based on Standard EDA Indices' Quality and Robustness against Motion Artifact.. Sensors (Basel) 2022 Apr 21;22(9).
    doi: 10.3390/s22093177pmc: PMC9104297pubmed: 35590866google scholar: lookup
  65. Hossain MB, Posada-Quintero HF, Kong Y, McNaboe R, Chon KH. A Preliminary Study on Automatic Motion Artifact Detection in Electrodermal Activity Data Using Machine Learning.. Annu Int Conf IEEE Eng Med Biol Soc 2021 Nov;2021:6920-6923.
    doi: 10.1016/j.bspc.2022.103483pubmed: 34892695google scholar: lookup
  66. Hossain MB, Posada-Quintero HF, Chon KH. A Deep Convolutional Autoencoder for Automatic Motion Artifact Removal in Electrodermal Activity.. IEEE Trans Biomed Eng 2022 Dec;69(12):3601-3611.
    doi: 10.1109/TBME.2022.3174509pubmed: 35544485google scholar: lookup

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