The Equestrian's Guide to Wearables, From Someone Who Actually Rides

Sweat patches, WHOOP bands, Oura Rings, and performance vests are showing up on elite World Cup athletes, and the teams deploying them have a specific goal: catch fatigue before it becomes a problem, personalize recovery, and find every possible edge. England's team has been tracking jet lag through heart rate variability. Brazil's squad wore sweat patches to dial in hydration in real time. You may even have one for your last ride, counting strides and turns and transitions.

This is elite sports science running on the same consumer devices sitting in your Amazon cart or already on your wrist at the barn. The question I get asked constantly at shows: should I be wearing one of these, and can I trust what it tells me? The honest answer is yes and no, and the details matter considerably depending on what you are using it for.

Every wrist or ring wearable uses a technology called photoplethysmography, or PPG. A light shines into your skin, a sensor reads how much bounces back, and from that pattern the device estimates your heart rate. This turns out to be one of the more reliable things these devices do. A Stanford study found six out of seven popular trackers measured heart rate within 5 percent accuracy during exercise. For most purposes, that is genuinely useful data.

Sleep tracking, resting heart rate trends, heart rate variability, and skin temperature are also solid territory for most devices, particularly Oura and Apple Watch. For anyone managing perimenopause, these are the metrics that matter most and the ones worth paying attention to.

Oura's dataset, pulled from over 850,000 women, shows perimenopausal women lose an average of two hours of sleep per week. Skin temperature often shifts before a hot flash even registers consciously. A 20 to 30 percent drop in HRV has been linked to the mood disruption and anxiety many women report during this transition. Oura has leaned into this with a dedicated Menopause Insights feature and a symptom scoring tool, and it is currently the most purpose-built device for women navigating this life stage.

Most wearable content is written for runners and gym athletes. Riding is a different sport entirely, and some equestrian specific apps are looking to close that gap. Think about what that means for a rider in her mid-forties who is waking up at 3am before a show, performing below where she knows she should be, and attributing it to nerves or stress. Her ring might be telling a different story. That story has a name and a treatment.

Equilab is the most equestrian-specific option on the market and worth mentioning here because it does something no general fitness tracker does: it tracks your horse. Using the sensors in your phone or a paired Apple Watch, Equilab analyzes gaits, speed, distance, turns, and time in each gait. It can tell you how long your horse spent in trot versus canter, track trends in your training over time, and even flag gait irregularities that might warrant a closer look. For Premium subscribers, it integrates with a Polar heart rate monitor for rider-specific data and includes a Safety Tracking feature that alerts your contacts if you stop moving unexpectedly. For anyone riding alone on trails or in remote areas, that last feature alone is worth the subscription.

Equilab also pairs with Apple Watch directly. The free version lets you use your watch as a remote control for your phone while riding, viewing your time, speed, distance, and gaits on your wrist without digging your phone out of your pocket. Premium subscribers can track standalone rides from the watch without the phone present at all.

That said, Equilab is fundamentally a horse performance tool. It tells you about your horse's movement and your training patterns. It does not give you the kind of physiological data about your own body that a dedicated health wearable provides.

Apple Watch does have a built-in Equestrian Sports workout mode, which you can find by scrolling down in the Workout app and tapping Add Workout. Selecting it activates continuous heart rate monitoring and GPS tracking for the duration of your ride and logs the session toward your activity rings. Here is the honest limitation: the watch cannot distinguish between your movement and your horse's movement in the way Equilab can. The step count it generates during an equestrian workout is notoriously unreliable because the horse's footfalls register through your wrist. Heart rate data during the ride is the genuinely useful output. The calorie estimate and step count should be treated with skepticism.

For riders who want the clearest picture of what their own body is doing during a ride, the most practical setup is Equilab running on your phone to track the horse and a chest strap like the Polar H10 feeding your heart rate data to either Equilab or Apple Health simultaneously. That combination gives you accurate rider heart rate alongside horse performance data, which is something no single device does well on its own.

Calorie burn is where all of these devices consistently fail. A 2020 meta-analysis in the International Journal of Exercise Science found consumer trackers overestimate or underestimate calorie burn by 20 to 40 percent on average, and during strength and resistance work that error can exceed 50 percent. The device does not actually measure calories. It measures heart rate and movement, then runs those numbers through an algorithm that assumes a predictable relationship between the two. Two women of the same age, weight, and height riding side by side can burn meaningfully different amounts of energy, and the tracker has no way to account for that.

For patients in The Easy Keeper program on GLP-1 therapy, I want this point to land clearly: do not make eating decisions based on the calorie number on your wrist. It is a rough estimate dressed in a very precise costume. Resting heart rate trends, sleep quality data, and activity patterns are far more trustworthy.

Many people assume smaller wrists produce worse readings, and wrist circumference does appear as a variable in some studies. A comprehensive guidelines paper published in npj Digital Medicine found higher device error rates in men than in women, not the reverse. Skin tone at the sensor site matters more consistently than sex does, since melanin absorbs the green light these sensors use. Tattoos over the sensor site cause similar interference. If either of those applies to you, look for a brand that has published accuracy data across diverse skin tones rather than assuming the flagship model performs equally well for everyone.

Which tracker or app is the best for you? It depends on what you want to track.

• For perimenopause and menopause tracking, the Oura Ring is the strongest option available right now. The dedicated temperature and symptom tracking is purpose-built for this transition, and the sleep architecture data is the best in its class.

• For overall heart rate accuracy across a range of activities, Apple Watch leads independent meta-analyses, coming in above 86 percent accuracy for heart rate measurement.

• For step counting during ground-based activities, Garmin holds the edge.

• For equestrian-specific ride tracking and horse performance data, Equilab is the clear choice. The free version is a solid starting point. Premium is worth it if safety tracking or advanced gait data matters to you.

• For anyone doing structured training who wants accurate heart rate data during effort, pair any wrist device with a Bluetooth chest strap like the Polar H10. A wrist device runs a 15 to 25 percent error rate during high-intensity work. A chest strap brings that under 3 percent and is the single most cost-effective accuracy upgrade available.

None of these devices replace a conversation with your physician about your labs, your hormones, or your weight management. Think of them as a rough compass rather than a map. If your ring shows HRV trending down for two weeks or your sleep is quietly falling apart, that data is worth bringing to your next visit. It is a starting point for a clinical conversation, not a diagnosis.

Riders are already good at reading signals in their horses. You notice a subtle head bob before it becomes three legged lameness. You catch a feed pan that isn't cleaned up before a full blown colic. A wearable that helps you start reading your own recovery, sleep, stress load, and hormonal patterns with the same attention is not a bad investment.

The number on your wrist is only as useful as the conversation you have about it.

Find me at www.presencemd.net.

TL:DR on the Study

The basics: Stanford researchers tested seven popular wrist-worn fitness trackers to evaluate how accurately they measure heart rate and calorie burn compared to medical-grade equipment, published in the Journal of Personalized Medicine.

Who was in the study: Sixty volunteers, 31 women and 29 men, across varying ages, body sizes, skin tones, and fitness levels.

What they did: Participants wore up to four trackers simultaneously while sitting, walking, running on a treadmill, and pedaling a stationary bike. Researchers measured actual heart rate via ECG and actual energy expenditure via indirect calorimetry for comparison.

The results: Six of seven devices measured heart rate within 5 percent accuracy. None of the seven measured calorie burn reliably.

Why it matters: Heart rate data from a wearable is generally trustworthy enough to guide training and track trends over time. The calorie number is not. Adjusting what you eat based on what your tracker says you burned means making decisions from a figure that may be off by 20 to 50 percent.

The catch: This study used 2017 data and none of the exact devices tested remain on the market. The underlying PPG technology and its core limitations have not changed fundamentally, though individual device accuracy has improved, particularly for heart rate. Calorie estimation remains the weakest output across the entire category regardless of brand or year.

How it works (probably): Heart rate monitoring requires detecting a repeating pulse pattern in reflected light, which is a relatively clean signal to isolate. Calorie burn requires estimating total metabolic cost from that heart rate data combined with age, weight, and sex, and that calculation varies significantly between individuals based on fitness level, muscle mass, and metabolic efficiency. None of those variables are visible to the sensor.