Sympathetic Arousal Detection in Horses Using Electrodermal Activity

Simple Summary Monitoring stress in horses continuously can help us improve their quality of life. Currently, the detection of stress in horses relies on the observation of their behavior. This cannot be implemented continuously, as it is impossible to have someone looking at the horse all the time. One way to monitor stress in a continuous and automatic way is collecting the heart rate. The heart rate detects the arousal caused by stress, but it can be affected by physical activity and other emotions. Another way to assess the arousal caused by stress is measuring the changes in the conductance of the skin, called electrodermal activity (EDA). EDA can detect stress and pain in humans better than the heart rate. We have collected EDA in horses for the first time and evaluated its capability to detect arousal. We caused arousal in the horses using two tests. First, we collected EDA while the horses were being fed, which causes continuous arousal. Second, we used an umbrella to cause a startle and short-lasting arousal. EDA was sensitive to both tests. This shows that EDA is sensitive to arousal in horses and can be potentially used to detect stress and pain continuously. 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.

[1]  E. Scilingo,et al.  Acute Stress State Classification Based on Electrodermal Activity Modeling , 2023, IEEE Transactions on Affective Computing.

[2]  P. Andersen,et al.  Performance of four equine pain scales and their association to movement asymmetry in horses with induced orthopedic pain , 2022, Frontiers in Veterinary Science.

[3]  Hugo F. Posada-Quintero,et al.  A Deep Convolutional Autoencoder for Automatic Motion Artifact Removal in Electrodermal Activity , 2022, IEEE Transactions on Biomedical Engineering.

[4]  Hugo F. Posada-Quintero,et al.  Comparison of Electrodermal Activity from Multiple Body Locations Based on Standard EDA Indices’ Quality and Robustness against Motion Artifact , 2022, Sensors.

[5]  H. Ohmura,et al.  Effect of restraint inside the transport vehicle on heart rate and heart rate variability in Thoroughbred horses , 2022, Journal of equine science.

[6]  M. Granados,et al.  Parasympathetic Tone Changes in Anesthetized Horses after Surgical Stimulation, and Morphine, Ketamine, and Dobutamine Administration , 2022, Animals : an open access journal from MDPI.

[7]  Riley Q. McNaboe,et al.  Automatic motion artifact detection in electrodermal activity data using machine learning , 2022, Biomed. Signal Process. Control..

[8]  Hugo F. Posada-Quintero,et al.  Seizures Caused by Exposure to Hyperbaric Oxygen in Rats Can Be Predicted by Early Changes in Electrodermal Activity , 2022, Frontiers in Physiology.

[9]  W. Montelpare,et al.  An Observational Evaluation of Stress in Horses During Therapeutic Riding Sessions , 2021, Journal of Veterinary Behavior.

[10]  Hugo F. Posada-Quintero,et al.  Time-varying Spectral Index of Electrodermal Activity to Predict Central Nervous System Oxygen Toxicity Symptoms in Divers: Preliminary results , 2021, 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC).

[11]  Hugo F. Posada-Quintero,et al.  Objective Pain Stimulation Intensity and Pain Sensation Assessment Using Machine Learning Classification and Regression Based on Electrodermal Activity. , 2021, American journal of physiology. Regulatory, integrative and comparative physiology.

[12]  Ki H. Chon,et al.  Real-Time High-Level Acute Pain Detection Using a Smartphone and a Wrist-Worn Electrodermal Activity Sensor , 2021, Sensors.

[13]  Youngsun Kong,et al.  Sensitive Physiological Indices of Pain Based on Differential Characteristics of Electrodermal Activity , 2021, IEEE Transactions on Biomedical Engineering.

[14]  K. Mitchell,et al.  Heart rate variability analysis in horses for the diagnosis of arrhythmias. , 2020, Veterinary journal.

[15]  B. Allaouchiche,et al.  Performance of the Parasympathetic Tone Activity (PTA) index to predict changes in mean arterial pressure in anaesthetized horses with different health conditions. , 2020, Research in veterinary science.

[16]  Hugo F. Posada-Quintero,et al.  Using electrodermal activity to validate multi-level pain stimulation in healthy volunteers evoked by thermal grills. , 2020, American journal of physiology. Regulatory, integrative and comparative physiology.

[17]  C. Lesimple Indicators of Horse Welfare: State-of-the-Art , 2020, Animals : an open access journal from MDPI.

[18]  J. Delgado,et al.  Welfare assessment at a Spanish Army Equine Breeding Centre , 2020 .

[19]  Hugo F Posada-Quintero,et al.  Innovations in Electrodermal Activity Data Collection and Signal Processing: A Systematic Review , 2020, Sensors.

[20]  R. Pariaut,et al.  Beat-to-Beat Patterning of Sinus Rhythm Reveals Non-linear Rhythm in the Dog Compared to the Human , 2020, Frontiers in Physiology.

[21]  D. Hebesberger,et al.  Testing for Behavioral and Physiological Responses of Domestic Horses (Equus caballus) Across Different Contexts – Consistency Over Time and Effects of Context , 2019, Front. Psychol..

[22]  Kyandoghere Kyamakya,et al.  A Deep-Learning Model for Subject-Independent Human Emotion Recognition Using Electrodermal Activity Sensors , 2019, Sensors.

[23]  Ki H. Chon,et al.  Analysis of Reproducibility of Noninvasive Measures of Sympathetic Autonomic Control Based on Electrodermal Activity and Heart Rate Variability , 2019, IEEE Access.

[24]  D. Shaw,et al.  Poincaré plots as a measure of heart rate variability in healthy dogs. , 2017, Journal of veterinary cardiology : the official journal of the European Society of Veterinary Cardiology.

[25]  F. Shaffer,et al.  An Overview of Heart Rate Variability Metrics and Norms , 2017, Front. Public Health.

[26]  Mohanasankar Sivaprakasam,et al.  Differential effects of physical and psychological stressors on electrodermal activity , 2017, 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

[27]  Hugo F Posada-Quintero,et al.  Highly sensitive index of sympathetic activity based on time-frequency spectral analysis of electrodermal activity. , 2016, American journal of physiology. Regulatory, integrative and comparative physiology.

[28]  Hugo F. Posada-Quintero,et al.  Power Spectral Density Analysis of Electrodermal Activity for Sympathetic Function Assessment , 2016, Annals of Biomedical Engineering.

[29]  Luca Citi,et al.  cvxEDA: A Convex Optimization Approach to Electrodermal Activity Processing , 2016, IEEE Transactions on Biomedical Engineering.

[30]  Norma A S Almeida,et al.  Behavioural, endocrine and cardiac autonomic responses to a model of startle in horses , 2016 .

[31]  C. Lindegaard,et al.  Recognition and quantification of pain in horses: A tutorial review , 2016 .

[32]  J. V. van Loon,et al.  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. , 2016, Veterinary journal.

[33]  M. G. Ruse,et al.  Measuring heart rate variability in horses to investigate the autonomic nervous system activity - Pros and cons of different methods , 2015 .

[34]  J. V. van Loon,et al.  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. , 2015, Veterinary journal.

[35]  M. Minero,et al.  Development of the Horse Grimace Scale (HGS) as a Pain Assessment Tool in Horses Undergoing Routine Castration , 2014, PloS one.

[36]  J. Bland,et al.  Holter Monitoring of Small Breed Dogs with Advanced Myxomatous Mitral Valve Disease with and without a History of Syncope , 2014, Journal of veterinary internal medicine.

[37]  W. Boucsein Electrodermal activity, 2nd ed. , 2012 .

[38]  H. Pedersen,et al.  Heart rate, heart rate variability, and arrhythmias in dogs with myxomatous mitral valve disease. , 2012, Journal of veterinary internal medicine.

[39]  Ming-Zher Poh,et al.  Continuous assessment of epileptic seizures with wrist-worn biosensors , 2011 .

[40]  N. Otani,et al.  "Zone of avoidance": RR interval distribution in tachograms, histograms, and Poincaré plots of a Boxer dog. , 2010, Journal of veterinary cardiology : the official journal of the European Society of Veterinary Cardiology.

[41]  M. Benedek,et al.  A continuous measure of phasic electrodermal activity , 2010, Journal of Neuroscience Methods.

[42]  P. Ellaway,et al.  Sweat production and the sympathetic skin response: Improving the clinical assessment of autonomic function , 2010, Autonomic Neuroscience.

[43]  Gerhard Tröster,et al.  Discriminating Stress From Cognitive Load Using a Wearable EDA Device , 2010, IEEE Transactions on Information Technology in Biomedicine.

[44]  S Quanten,et al.  Online detection of an emotional response of a horse during physical activity. , 2009, Veterinary journal.

[45]  Christopher H. Gibbons,et al.  Sweat testing to evaluate autonomic function , 2009, Clinical Autonomic Research.

[46]  J. Cacioppo,et al.  Handbook Of Psychophysiology , 2019 .

[47]  Armelle Prunier,et al.  Heart rate variability as a measure of autonomic regulation of cardiac activity for assessing stress and welfare in farm animals — A review , 2007, Physiology & Behavior.

[48]  M. Campen,et al.  Heart rate variability in rodents: uses and caveats in toxicological studies , 2007, Cardiovascular Toxicology.

[49]  F. Ashley,et al.  Behavioural assessment of pain in horses and donkeys: application to clinical practice and future studies. , 2010, Equine veterinary journal.

[50]  J. Abbott Heart rate and heart rate variability of healthy cats in home and hospital environments⋆ , 2005, Journal of feline medicine and surgery.

[51]  Jennifer Healey,et al.  Detecting stress during real-world driving tasks using physiological sensors , 2005, IEEE Transactions on Intelligent Transportation Systems.

[52]  Jörg A Auer,et al.  Assessment of mental stress in warmblood horses: heart rate variability in comparison to heart rate and selected behavioural parameters , 2004 .

[53]  J. Auer,et al.  The association between heart rate, heart rate variability, endocrine and behavioural pain measures in horses suffering from laminitis. , 2004, Journal of veterinary medicine. A, Physiology, pathology, clinical medicine.

[54]  K. Meurs,et al.  Assessment of heart rate variability in Boxers with arrhythmogenic right ventricular cardiomyopathy. , 2004, Journal of the American Veterinary Medical Association.

[55]  G. Marsaglia,et al.  Evaluating Kolmogorov's distribution , 2003 .

[56]  R. Palme,et al.  Hormones as indicators of stress. , 2002, Domestic animal endocrinology.

[57]  E. K. Visser,et al.  Heart rate and heart rate variability during a novel object test and a handling test in young horses , 2002, Physiology & Behavior.

[58]  R. Schroter,et al.  Frequency domain analysis of heart rate variability in horses at rest and during exercise. , 2010, Equine veterinary journal.

[59]  G. Jacobs,et al.  Heart rate variability in Doberman Pinschers with and without echocardiographic evidence of dilated cardiomyopathy. , 2000, American journal of veterinary research.

[60]  J. Thayer,et al.  Heart rate variability in the horse by ambulatory monitoring. , 1997, Biomedical sciences instrumentation.

[61]  T. Hada,et al.  Assessment of autonomic nervous function by power spectral analysis of heart rate variability in the horse. , 1996, Journal of the autonomic nervous system.

[62]  C. Milne AUTONOMIC NERVOUS SYSTEM , 1957, Nursing standard (Royal College of Nursing (Great Britain) : 1987).

[63]  L. H. Miller Table of Percentage Points of Kolmogorov Statistics , 1956 .

[64]  F. Massey The Kolmogorov-Smirnov Test for Goodness of Fit , 1951 .