I’m Looking For More Personal Wearables - But This Needs To Happen First
Hello, I’m Conor, and I am a data nerd. It doesn’t matter if I’m running, swimming, lifting, or cycling, I love to see where I’m improving – and, more often than not, where I’m losing performance.
This article first appeared in PULSE by Wareable, our weekly subscription based service for wearables insiders. Subscribe free here to get it delivered to your inbox.
Wearables have been a huge resource throughout all this, often acting as the inflection point to go off exploring a way to improve – and I’m still thankful I didn’t have to suffer through the early noughties attempts at tracking even basics like distance.
But after speaking with habits and behavioral change expert Dr Heather McKee for last week’s paid-subscriber edition of PULSE, one point she made stuck with me: the idea that we’re still lacking truly personal wearables.
It’s surprising, in a sense, because I hear from companies almost every week about the idea of creating personal wearables.
But there’s a problem: your wearable experience just looks like mine – even though we’re likely interested in different things, and our bodies/lives are totally different. And sometimes, I don’t think wearables really understand me at all.
So, what comes next?
The imperfect nature of user input

I think Whoop is the best example of a wearable that ‘gets me’ – one that informs behavioral change and aligns with my general goal of improved athletic performance.
Specifically, the platform’s Journal and Insights feature is the big reason for this. In its current form, this relies on a yes/no system to pin down the environmental factors positively or negatively affecting my recovery score.
At least in my experience, this provides great backup for what I’ve likely already suspected. Factors like late workouts, late meals, and a day of high stress will hamper my readiness the following day, while having a consistent wake time and working out early will likely help me to recover better.
But a yes/no input isn’t the most scientific system. For example, taking my creatine monohydrate supplement apparently sees a 6% uptick in my recovery versus not taking it. Yet this is likely skewed by the fact I only skip this when I travel (or have been so busy or stressed that I’ve not managed time to mix a drink).
Not having the stress and disrupted sleep typically associated with traveling is much more likely to be the reason for the ‘positive’ effect it has on my recovery, rather than taking it versus not.
So, as you can see, I’m still doing a lot of hard yards myself to understand which of Whoop’s Insights are and aren’t relevant, but it’s also true that this kind of manual input is one of the most effective implementations we have of understanding our behaviors.
Where AI could fill the gaps

The big sea change here is likely to come from advances in machine learning; AI models that analyze our data and present us with accurate trends without any real intervention.
In our podcast with human performance coach James Hewitt, he outlined how AI could deliver the personalization I’ve been looking for:
“A time is coming when we can look forward to people’s apps looking different to the next person, with screens built on the fly based on what they need to see that day,” James Hewitt told PULSE.
And that also extends to notifications too:
“Notifications also need to be appropriately timed and tailored for the individual. And that can often mean not sending an alert, using adaptable user interfaces,” he continued.
And, again, we are seeing some early signs here. Oura’s Readiness Score summaries take into account mid-afternoon nap or that your resting heart rate is low despite an active day, and platforms like Strava will soon use ‘Athlete Intelligence’ – a sort of new-age Clippy – to pull out interesting insights from your training.
Manual input will always be necessary – we can’t have a sensor for everything, after all – but AI will almost certainly get better at filling the gaps in here, too.
The behaviors we’re already logging, like how much time we spend in the sauna, may also be impacting our best time to exercise or have a direct correlation to our sleep hours. It’s the kind of next-level insight I’d love to see.
Having our wearables wake up to the context of non-tracked behaviors and environmental factors is just one way they can become more personal, too. Something Dr. McKee stressed in our chat is the current lack of diversity in models, with a one-size-fits-all approach often taken by platform builders.
As I said up top, wearables fit me well because I enjoy diving into data.
But plenty of people don’t – my partner, for example, has zero desire to see her heart rate data during workouts. And some, often rightly, don’t understand the relevance of a wearable to their goal.
Yet we’re almost always stuck using the same platforms, which puts a huge amount of the onus on you to pick a wearable that specifically fits your competency level.
And though it’s often overlooked, there’s great value in tailoring data, insights, and prompts to a user – especially with the goal so often to change behaviors.
Teaching, not just tracking

In my experience, coaching-orientated platforms that integrate with wearables are often the most effective – the ones I come back to again and again.
Information gathering is still essential here, but it’s the extra mile in delivery that seems to make the difference.
Instead of just being told your running cadence is low, for example, you’re told that this might be caused by above-average stride length. Instead of being on a strict workout schedule, a lighter session is put forward when you’ve slept poorly.
Since dealing with a running injury, I’ve spent more hours in the pool. And I’ve been using the excellent Form Smart Swim Goggles 2, and its subscription-based coaching recommendations. These are delivered both in real-time and in the app.
It’s been revelatory, and a perfect example of a proactive wearable built to specifically provide feedback on technique cues and your goal.
Why? Because I already know I’m an average swimmer. I want to know why, and how I can improve.
Luckily – and unlike any other wearable – Form’s HeadCoach feature can pin down what part of my technique (peak head roll, if you’re wondering) is the cause of this. It explains to me what it is, why it’s harming my efficiency, and drills to improve it.
And given most people’s goals are likely simple – e.g. getting more sleep or moving more – there’s no reason why wearable makers can’t apply this logic across the board.
Ultimately, we often need to be pushed in the right direction. And that means we need more wearable makers that ask us what we’re looking to get out of their device, and then hold our hand along the way.
That’s the next stage of truly personal wearables – for everyone, not just data nerds like me.