How Sanya Sharma is reinventing equine welfare

What started with a rider’s instinct to understand her horse better has evolved into an attempt to solve one of equine care’s biggest challenges: identifying health problems before they become visible.

Equestrian Sanya Sharma, a grade 12 student, is combining her experience in the saddle with her research into horse behaviour to develop EquiSense AI, a wearable device that uses physiological, behavioural and environmental data to detect signs of stress and potential health issues.

Sanya speaks about the technology, her motivation behind it and her ambition to make horse health monitoring more accessible to stable owners.

Excerpts:

What exactly does EquiSense AI do?

EquiSense combines heart rate and HRV sensors, an IMU for motion tracking, temperature sensors, EDA/GSR sensors for stress response, and environmental monitoring into a single wearable band.

The machine learning models are trained on this data to classify a horse’s state including calm, stressed, possible pain, colic risk, lameness risk or heat stress and flag concerning patterns through real-time alerts. Explainable AI is also built in, so a vet or trainer can see why the system raised a flag, rather than simply being told that it did.

How has your own experience with horses shaped EquiSense AI?

I wanted to look beyond winning medals and focus on improving the well-being of horses by developing an innovative wearable device. This is an area where I felt there was a need for something new, and it has been inspiring to see how passion, empathy and innovation can come together to make a meaningful impact on equine care.

Alongside my competitive career, I have researched horse behaviour psychology, with my work published in IJFMR in 2025, focusing on how horses communicate stress non-verbally and how the rider-horse bond shapes emotional regulation. That dual fluency as an elite athlete and behavioural researcher is the foundation EquiSense is built on.

Why is it so difficult to identify health problems in horses early?

Horses are prey animals and they hide weakness. Showing pain or fatigue makes them a target but it is also exactly what makes equine care so difficult. Colic, one of the most common and dangerous conditions in horses, contributes to roughly 150 horse deaths a day in the United States alone. Often, by the time visible symptoms such as pawing or repeated lying down appear, the window for early intervention has already narrowed.

What are some of the challenges involved in developing the device?

It is a notable technical undertaking for a student athlete, but I see engineering as inseparable from behavioural science. Sensor placement, for instance, isn't just an electronics question. It requires understanding equine anatomy and movement patterns, as well as where a horse will tolerate a band without the device itself becoming a stressor.

How are you planning to test the device?

I plan to pilot EquiSense with 10 to 12 horses at the stable where I train, over an 8 to 12-week period. The aim is to collect more than 500 hours of physiological and behavioural data across rest, exercise and stress states. The bar I have set for myself is quite exacting for a high school project: 80% or higher accuracy in detecting stress or pain, fewer than 10% false positives, and validation against actual veterinary behavioural assessments.

The real prize would be one or two documented cases where the system flags a problem four to eight hours before visible symptoms appear, confirmed by a vet, with a documented intervention outcome.

What makes the paid order significant?

Western products in this category are priced at around Rs 27,000 and generally measure heart rate and little beyond it. My EquiSense AI prototype, built with an ESP32, an ECG sensor, a temperature sensor and an IMU, costs approximately Rs 8,000. That makes it one of the more affordable solutions of its kind while capturing a much broader range of data.

As a 'Make in India' effort, it is also among the first indigenous attempts at a comprehensive horse health monitoring product, in a category that riders and stables here have long had to source from abroad.

How do you describe the field your work sits in?

I don't position myself purely as an engineer. I describe my interest as sitting at the intersection of comparative psychology, psychophysiology and applied animal welfare science.

I use the language of stress markers and behavioural observation as much as I use code. It is an unusual combination for a competitive athlete, but for anyone who has watched a horse go quite right before something goes wrong, it makes a great deal of sense.

I am trying my best to address the larger issues related to horse well-being, and I will continue to work on it while riding to make this product economically viable for stable owners.