Some mornings, Anmol (she/her), a 32-year-old venture capital investor based in Gurgaon, wakes up feeling inexplicably exhausted. She doesn’t want to work out, barely wants to get out of bed, while her Apple Watch tells her that her body is under more stress than usual. A day later, her period arrives, and it all makes sense. “It’s such a womanly experience,” she laughs. “Everybody’s like, Why am I acting up so much? And then one day later you’re like, Oh, of course I was.”
What frustrates her isn’t that the smartwatch detects these physiological shifts, but that it frames them as something gone wrong — elevated stress, poor recovery — rather than recognising the hormonal rhythm behind them. “If I got one notification saying, Take it easy. Your luteal phase is about to start, I’d be like, okay, fine. At least I know,” she says.
Her watch can predict her next period, but it can’t connect that to anything else it measures. “For different phases of your cycle, there are different sleep requirements,” she says. “Does the app really sync that with my cycle? I’m not quite sure.” She imagines a wearable that doesn’t just record her body but helps her live with it — suggesting yoga during the luteal phase, higher intensity around ovulation, treating hormones, sleep and mood as connected rather than separate alerts. “It’s a very one-size-fits-all approach,” she says.
For years, wearable technology has promised to help us understand our bodies through numbers: sleep quality, heart rate variability, stress, recovery, all turned into colourful graphs and daily scores. The premise is seductive: know your numbers, know yourself. But those numbers are only as meaningful as the assumptions behind them. Hidden beneath every readiness score is a simple question: whose body was considered “normal” in the first place?
The Body That Technology Assumed
Like much of modern medicine, wearable technology inherited a default user: a body that has historically been imagined as white, cisgender, male, able-bodied, and relatively young. The baselines and training datasets used to build many devices reflect a limited slice of human experience. Menstrual cycles, pregnancy, menopause, disability, and gender-affirming hormone therapy don’t just add complexity to these systems — they expose the assumptions already built into them.
Few people know their wearable as intimately as Hamsini (she/her). The 34-year-old Mumbai-based finance professional is a long-distance runner who trains 4 to 5 times a week, tracking mileage, training load and heart rate variability (HRV) on her Garmin. Most of the time she trusts it — until her luteal phase, when her HRV drops and resting heart rate rises, well-documented hormonal shifts her Garmin already has the data to recognise. Instead, it warns her she’s under-recovered. “The wearable shouldn’t be gaslighting us into thinking we’re doing something wrong when we’re simply being women,” she says.
For Mumbai-based educator and consultant Zahra Gabuji, who has lived with health anxiety, the problem isn’t inaccurate data so much as what the device does with it. In her first months wearing an ŌURA Ring, small temperature rises during her luteal phase kept triggering alerts for “major signs” of physiological strain. “Having lived with hypochondria, you can imagine the scenarios that play in my head,” she says. Over time, the ring learned her cycle and the warnings stopped — but the experience left her wondering whose bodies these systems are actually built to understand.
Building around women means rethinking everything.
For product teams, these are less user complaints than design problems. “People underestimate the systems thinking that’s required,” says Deekshitha Addanki (she/her), a medextile designer at Murata Business Engineering, whose work focuses on wearable healthcare technologies for early-stage breast cancer screening. Everything from fabric stretch and seam placement to sensor positioning has to work together for the data to be reliable in the first place, and there’s “always one outlier” that questions how far a design can scale. The industry’s default body, she says, still shows up in sizing systems, fit models and clinical validation datasets built around a narrow standard.
Krishna Poddar (she/her), a Product Manager at MAI — an AI-powered wearable designed for women in India — traces the problem further back than the interface. “The harsh reality is that virtually zero mainstream wearables on the market today use a female baseline,” she says. Built for a default male user, natural female physiological shifts get flagged as anomalies; MAI was built instead around hormonal rhythms that shape metabolism, sleep and cognitive energy as fluctuating rather than fixed. Localisation matters too, she notes — most of the underlying medical and algorithmic data comes from Western populations, raising real questions about how well it performs across other ethnicities and lifestyles. Rather than flooding users with raw biometrics, her team built MAI around contextual guidance instead: what to do when something’s out of balance, without manufacturing anxiety.
Divyakshi Kaushik, founder of Anatomech, questions the category’s premise altogether: must a wearable only observe, or can it respond? Most commercial devices measure heart rate, sleep or movement and translate that into a chart. Anatomech’s compression wearables — built for people with lymphedema, varicose veins and chronic circulatory conditions — instead mimic the body’s circulation directly, applying graduated compression to move fluid through the lymphatic and venous systems. “Women are the ones who go through circulatory disruption every month,” she says — menstruation, pregnancy, menopause all change circulation and swelling in ways a static device simply can’t track. “How do we build something that changes with the body instead of expecting the body to fit the product?” For Divyakshi, that’s the real frontier: not more monitoring, but actuation — wearables that actively assist recovery and symptom management rather than just reporting that something’s wrong.
Beyond Women’s Health
The more users I spoke to, the clearer it became that this isn’t simply a story about women. It is about what happens when technology mistakes one kind of body for the default.
For Veer Rathi (he/him), a trans man, wearable tech is another reminder of how few health technologies are built for bodies in transition. Hormone therapy reshapes physiology over months and years, while resting heart rate, recovery, muscle mass, sleep cycles are all affected as well. Yet most consumer wearables continue to interpret these shifts through static baselines, offering little insight into what transition itself might mean for the data they collect.
In that sense, the future of wearables may have less to do with collecting more data than with asking better questions. Can a device distinguish between illness and hormonal change? Between overtraining and recovery? Between chronic pain and an inaccessible environment? Between a body that is failing and one that is simply changing?
Perhaps the most radical shift underway isn’t that technology is finally beginning to take women’s bodies seriously. It’s that designers are slowly abandoning the idea that there has ever been a single “normal” body to design around.
The next generation of wearables will almost certainly become smaller, smarter and more predictive. But their real test will be something far less technical: whether they can stop asking bodies to conform to technology, and instead build technology that learns to conform to bodies.
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