Analyzing Pain in Equine with Eye Syndrome: Advancements in Recognition and Assessment Systems

  • Surendra Yadav, Prerna Mahajan, Ravindra Kumar Pandey
Keywords: Equine eye syndrome (EES), horses, health concern, pain, HGM, PIB


Equine eye syndrome, or EES, is a serious health concern for horses that results in pain and suffering. The goal of this research is to improve the early detection and treatment of equine ocular discomfort by exploring novel methods for identifying and evaluating pain in horses suffering from EES. We performed a retrospective observational analysis on each horse treated for ophthalmologic disorders from October 2020 to October 2022. The clinical improvements of horses in the present investigation are divided into different categories: excision, ophthalmic operation and discharge with medical care. The Horse Grimace Measure (HGM) and the Pain Index for Behavior (PIB) are used to evaluate temporal patterns using linear regression. The relationships between slope, capture and development are found using the Kruskal-Wallis test. Out of the 114 horses that fulfilled the requirements for entry, 46 were released following solely medical treatment, 33 had eye surgery and 16 had excision. Two ophthalmology operations were conducted on five horses. When the horses were admitted, the PIB readings were greater in the medically managed horses than in the enucleated horses. Compared to horses under medicinal management, excision-requiring horses experienced a greater increase in HGM and PIB throughout their hospital stay. Additionally, PIB increased more in these cases than in cases of ocular eye surgery. When it comes to tracking the course and reaction to treatment, pain scoring could be a helpful tool for horses with eye conditions.


Neethirajan, S., (2023). Artificial Intelligence and Sensor Innovations: Enhancing Livestock Welfare with a Human-Centric Approach. Human-Centric Intelligent Systems, pp.1-16.

Kumar, S., Underwood, S.H., Masters, J.L., Manley, N.A., Konstantzos, I., Lau, J., Haller, R. and Wang, L.M., (2023). Ten questions concerning smart and healthy built environments for older adults. Building and Environment, 244, p.110720.

Ballou, M.E., Mueller, M.K. and Dowling-Guyer, S., (2020). Aging equines: understanding the experience of caring for a geriatric horse with a chronic condition. Journal of Equine Veterinary Science, 90, p.102993.

Toader, C., Eva, L., Tataru, C.I., Covache-Busuioc, R.A., Bratu, B.G., Dumitrascu, D.I., Costin, H.P., Glavan, L.A. and Ciurea, A.V., (2023). Frontiers of Cranial Base Surgery: Integrating Technique, Technology, and Teamwork for the Future of Neurosurgery. Brain Sciences, 13(10), p.1495.

Prasad, M., Ghosh, M., Patki, H.S., Kumar, S., Brar, B., Sindhu, N., Goel, P., Kaushik, S., Mohan, H., Syed, S. and Kumar, R., (2021). Imaging Techniques in Veterinary Disease Diagnosis. In Advances in Animal Disease Diagnosis (pp. 103-145). CRC Press.

Awwad, S., Henein, C., Ibeanu, N., Khaw, P.T. and Brocchini, S., (2020). Preclinical challenges for developing long-acting intravitreal medicines. European Journal of Pharmaceutics and Biopharmaceutics, 153, pp.130-149.

Hall, C., Randle, H., Pearson, G., Preshaw, L. and Waran, N., (2018). Assessing equine emotional state. Applied animal behaviour science, 205, pp.183-193.

Dwyer, A.E. and de Linde Henriksen, M., (2022). Equine ocular examination and treatment techniques. Equine Ophthalmology, pp.1-89.

VERMA, V., KRISHNAN, V. and VERMA, C., (2021). Telemedicine in India–an investment of technology for a digitized healthcare industry: a systematic review. Romanian Journal of Information Technology & Automatic Control/RevistaRomână de InformaticășiAutomatică, 31(4).

Bhattad, P.B. and Jain, V., (2020). Artificial intelligence in modern medicine–the evolving necessity of the present and its role in transforming the future of medical care. Cureus, 12(5).

Gris, V.N., Broche Jr, N., Kaneko, A., Okamoto, M., Suzuki, J., Mills, D.S. and Miyabe-Nishiwaki, T., (2022). Investigating subtle changes in facial expression to assess acute pain in Japanese macaques. Scientific Reports, 12(1), p.19675.

Pessanha, F., Salah, A.A., van Loon, T. and Veltkamp, R., (2022). Facial image-based automatic assessment of equine pain. IEEE Transactions on Affective Computing.

Kil, N., Ertelt, K. and Auer, U., (2020). Development and validation of an automated video tracking model for stabled horses. Animals, 10(12), p.2258.

Mota-Rojas, D., Marcet-Rius, M., Ogi, A., Hernández-Ávalos, I., Mariti, C., Martínez-Burnes, J., Mora-Medina, P., Casas, A., Domínguez, A., Reyes, B. and Gazzano, A., (2021). Current advances in the assessment of dog's emotions, facial expressions, and their use for clinical recognition of pain. Animals, 11(11), p.3334.

Kelemen, Z., Grimm, H., Long, M., Auer, U. and Jenner, F., (2021). Recumbency as an Equine Welfare Indicator in Geriatric Horses and Horses with Chronic Orthopaedic Disease. Animals, 11(11), p.3189.

Džermeikaitė, K., Bačėninaitė, D. and Antanaitis, R., (2023). Innovations in Cattle Farming: Application of Innovative Technologies and Sensors in the Diagnosis of Diseases. Animals, 13(5), p.780.

Mota-Rojas, D., Wang, D., Titto, C.G., Gómez-Prado, J., Carvajal-de la Fuente, V., Ghezzi, M., Boscato-Funes, L., Barrios-García, H., Torres-Bernal, F., Casas-Alvarado, A. and Martínez-Burnes, J., (2021). Pathophysiology of fever and application of infrared thermography (IRT) in the detection of sick domestic animals: Recent advances. Animals, 11(8), p.2316.

May, A., Gesell‐May, S., Müller, T. and Ertel, W., (2022). Artificial intelligence is a tool to aid in the differentiation of equine ophthalmic diseases with an emphasis on equine uveitis. Equine Veterinary Journal, 54(5), pp.847-855.

Evangelista, M.C., Watanabe, R., Leung, V.S., Monteiro, B.P., O’Toole, E., Pang, D.S. and Steagall, P.V., (2019). Facial expressions of pain in cats: the development and validation of a Feline Grimace Scale. Scientific reports, 9(1), p.19128.

Egan, S., Brama, P.A., Goulding, C., McKeown, D., Kearney, C.M. and McGrath, D., (2021). The feasibility of equine field-based postural sway analysis using a single inertial sensor. Sensors, 21(4), p.1286.

How to Cite
Surendra Yadav, Prerna Mahajan, Ravindra Kumar Pandey. (2024). Analyzing Pain in Equine with Eye Syndrome: Advancements in Recognition and Assessment Systems. Revista Electronica De Veterinaria, 25(1), 15-23. Retrieved from