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Opinion

Emotions are data: The missing layer in femtech’s measurement era

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By Zahra Bhatti, founder and CEO, Véa

We are living through a measurement boom.

Wrist-worn wearables ship in the hundreds of millions IDC forecast worldwide shipments at 537.9 million units in 2024, with 136.5 million units shipped in Q2 2025 alone.

We can track steps, sleep stages, heart rate, HRV, temperature, glucose variability and recovery scores.

We have never had more physiological insight into the human body.

So why are women still burning out? Still overwhelmed? Still carrying invisible cognitive load that never appears on a single dashboard?

If the data revolution in health tech was supposed to empower women, why do so many feel more monitored than supported?

A number on your wrist can tell you what happened in your body. It rarely tells you why it happened, what it meant or what you need next.

That missing layer is emotional data. And femtech is uniquely positioned to build it.

We Built Dashboards. We Didn’t Build Interpretation.

Picture this.

It’s 6:47am. You’ve been up since 4 with a teething toddler, made packed lunches on autopilot, managed a meltdown at the school gates and arrived at your desk already running on fumes.

Your watch buzzes. Sleep score: 38. Stress: High. Recovery: Poor. Thanks. You already knew.

This is the problem no one in health tech wants to name.

Wearables are extraordinary at capturing signals but measurement without meaning stops at awareness.

Your HRV dips and a notification pings. It cannot tell you whether that dip came from the argument you didn’t finish with your partner, the guilt of missing bedtime again, the weight of being the only one who remembers the GP appointment or the hormonal crash of your luteal phase hitting while all of it lands at once.

The sensor caught the signal but it missed the entire story.

The evidence backs up what women already feel in their bones.

While activity trackers can increase step counts, a Lancet Digital Health umbrella review found their effect on broader psychological wellbeing is limited.

A 2024 systematic review went further, calling the evidence for wearables improving mental health “extremely limited”.

The sensors work but the interpretation doesn’t. That gap between data and meaning is exactly where women fall through.

Women’s Mental Health Is Not a Niche Concern. It Is a Systems Failure.

Consider the architecture of burden women navigate daily.

Depression is approximately 1.5 times more common among women than men, according to the World Health Organization.

The gender gap emerges at puberty and persists through the lifespan, driven by biological, psychological and social factors that compound over decades.

In the UK, 26.2 per cent of women reported high anxiety in the most recent ONS quarterly data, compared with 18.8 per cent of men – a gap that has remained statistically significant for over a decade.

But here is the question nobody in wellness tech seems to be asking: where does all that invisible labour live in the data?

Globally, women perform 2.5 times more unpaid care and domestic work than men.

That is time, emotional bandwidth and cognitive effort that never surfaces in economic metrics or health dashboards.

Forty-five percent of working-age women are outside the labour force because of unpaid care responsibilities, compared with just 5 per cent of men.

For those who do stay at work, the toll compounds: CIPD research found that 67 per cent of women aged 40–60 experiencing menopause symptoms report a mostly negative impact at work, with 79 per cent feeling less able to concentrate and one in six considering leaving their role entirely.

These are not isolated statistics.

They describe accumulated cognitive and emotional load across a lifetime a compounding interest of stress that no single intervention can repay.

Yet most wellness technologies still focus on optimisation metrics such as: output, recovery, movement and productivity.

Women do not simply need better tracking. They need systems that reduce the burden of self-interpretation.

When did we decide that measuring a woman’s body was more important than understanding what she’s carrying inside it?

Emotions Are Not Soft Signals. They Are Early Data.

Emotions are routinely dismissed as subjective, anecdotal and too messy to measure.

But from a systems perspective, they are high-frequency signals about safety versus threat, capacity versus overload, connection versus isolation and alignment versus self-betrayal.

They are early-warning indicators arriving long before burnout becomes clinical, long before sleep deteriorates especially long before productivity drops.

Physiology lags behind the emotional moment.

Your heart rate spikes after the confrontation. Your sleep fragments after a week of over-functioning. Your inflammation markers will never capture the micro-stresses that accumulated all day. Emotions do.

They are the body’s first responders faster than cortisol, more specific than HRV, more honest than any self-reported wellness score.

When emotional data is captured consistently, patterns emerge that no wearable can detect alone: anxiety clustering after specific meetings, energy dipping during certain cycle phases, irritability rising after relational overextension, creative clarity following solitude or movement.

This is not mood tracking for novelty. This becomes behavioural pattern recognition – the diagnostic layer women have been missing and needing.

From Self-Optimisation to Self-Understanding

We have built extraordinary tools to measure the female body.

We have not yet built infrastructure to interpret the emotional load women carry daily, the invisible labour, the relational tension, the hormonal transitions and most importantly the resulting cognitive overload.

These forces rarely appear in a recovery score rather they show up unmistakably in emotional patterns.

Imagine: a wearable detects sustained stress variability. An emotional check-in identifies relational strain. Context shows deadline pressure and reduced recovery. The system responds not with another metric, but with a small, realistic intervention that fits your life.

From dashboard to preventative mental health infrastructure. THIS is the golden opportunity femtech has to lead.

When emotions are treated as structured, longitudinal data rather than vague self-expression, they become a preventative signal.

They reveal when capacity is shrinking, when boundaries are leaking, when resilience is building. They show what no heart rate monitor ever could: the moment a woman stops prioritising herself, and the pattern that follows.

This shift is already beginning.

Platforms like Véa are building emotional operating systems that treat emotions as legitimate health data translating micro-check-ins and pattern recognition into contextual insight, reducing the invisible labour of self-analysis rather than adding to it.

Not more optimisation. Not more self-surveillance. Structured self-understanding that actually lightens the load.

In a world saturated with metrics, the competitive advantage is no longer more data. It is better meaning.

Emotions remain the most underutilised dataset in women’s health. Femtech has the infrastructure, the audience and the moment to build the missing layer.

The question is whether it will.

News

We built Ema like a nurse: Here’s why that matters

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By Claire Pettengill, science intern and Jade Anstine, clinical AI intern, Ema EQ

Every year, Gallup asks Americans which professions they trust most. Every year, nurses win. Not doctors. Not scientists. Nurses. And if you spend any time thinking about why, the answer is not hard to find.

Medicine runs on the nurse noticing first. In other words, the diagnosis follows the nurse sounding the alarm. They ask questions that feel human, not procedural. They explain what is happening in language you can understand.

And, critically, they know when something is beyond their scope and get you to the right person without making you feel like a burden for needing more.

That is the model we built Ema on.

When we set out to build an AI companion for women’s health, we could have just built something that answers questions efficiently. Pattern matching. Fast retrieval. Clinically accurate outputs.

Those things matter, and Ema does all of them. But accuracy alone does not build trust, and trust is the entire game in healthcare.

A woman asking about her postpartum recovery, her fertility, or her breastfeeding supply is not looking for a search engine. She is looking for someone who will take her seriously.

Women’s concerns don’t just need to be ‘validated’; they also need to be believed. Dismiss a woman’s pain as anxiety once, and you’ve taught her to doubt her own body.

The nursing model of care is built on exactly that premise. It is care that is shaped by her story. It asks about context and symptoms.

It treats the person as a whole, and it recognises that the right answer is sometimes a referral, not a response.

We trained Ema to escalate. That may sound like a small thing, but in AI, it is a deliberate design choice.

Most AI systems are optimised to answer and maintain engagement. Ema is optimised to help, and sometimes helping means saying “you need to speak to a clinician” and making that path easy.

This matters especially in women’s health, where the clinical trust gap is well-documented.

In a 2022 nationally representative survey of over 5,000 women, nearly 1 in 3 reported that their doctor had dismissed their concerns, and 15 per cent said a provider simply didn’t believe them.

Women are more likely to have their symptoms dismissed, their concerns minimised, and their pain undertreated. Among women under 35, nearly half reported at least one of these experiences.

They have had to learn how to advocate within systems designed for efficiency, built on men’s health.

With Ema, every conversation is an opportunity to make a woman feel heard, informed, and directed to the right level of care, neither over-triaged nor undertreated.

The goal is not to replace clinicians. It is to create a trustworthy first point of support that listens carefully, explains clearly, recognises limits, and helps women move toward appropriate care.

The nurses who top those Gallup rankings every year earn that trust through consistency. They show up, listen, follow through, and know their limits.

Ema is simply that trust, built into technology. That is the standard we hold Ema to: a trustworthy presence that knows when to answer and when to hand off.

Medicine spent a long time teaching women not to expect to be believed. Ema is built by the people who never stopped listening.

Bios

Claire Pettengill is a psychiatric nurse and DNP-PMHNP candidate at Columbia University School of Nursing, specialising in women’s mental health across the lifespan and algorithmic justice – ensuring the AI tools shaping women’s care are built to actually listen. She joined Ema EQ as a science intern focusing on clinical safety standards for evaluating AI in women’s health.

Jade Anstine is a senior nursing student at Gustavus Adolphus College looking to bridge the gap between frontline medicine and digital health innovation. He joined Ema EQ as a Clinical AI Intern to assess the Ema AI model across different clinical populations, specifically pediatrics and LGBTQ+.

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Opinion

The technology exists: Why are women still waiting?

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By Jane Lewis, chief operating officer, chief financial officer and women’s health lead, ABHI

For years, the conversation around women’s health has rightly focused on recognition.

Recognition that women wait longer for diagnosis. Recognition that symptoms are too often dismissed or normalised. Recognition that healthcare systems have historically been designed around male biology, leaving gaps in research, evidence and care.

That recognition matters. But awareness alone will not improve outcomes.

The challenge facing women’s health today is no longer simply identifying the problem. It is acting on the solutions already available.

At ABHI’s Women’s Health Summit earlier this year, leaders from across healthcare, government, academia and industry came together to discuss the future of women’s health.

One message emerged repeatedly throughout the day: we do not have an innovation problem.

Across medical devices, diagnostics, digital health and genomics, there are already technologies capable of transforming outcomes for women.

From self-sampling approaches for cervical screening and non-invasive diagnostics to AI-enabled tools and advanced imaging, innovation is happening. The question is whether healthcare systems can adopt it quickly enough.

Too often, promising technologies become trapped in pilot programmes, fragmented procurement processes or lengthy implementation pathways. Evidence generation, commissioning and adoption are frequently treated as separate challenges rather than part of a single journey.

The consequence is that innovations capable of improving quality of life and reducing pressure on health services take years to reach the women who could benefit from them.

This matters because women’s health extends far beyond reproductive health.

Historically, many discussions have centred on fertility, pregnancy and gynaecological conditions. These remain critically important, but they represent only part of the picture.

Women experience cardiovascular disease differently to men. They are disproportionately affected by autoimmune conditions. They face distinct health challenges throughout their lives, from adolescence to healthy ageing.

                            Jane Lewis

Yet healthcare systems often continue to approach these issues in isolation.

A woman does not experience her health in separate compartments. Pregnancy, cardiovascular risk, menopause, mental health and musculoskeletal conditions are interconnected.

Healthcare systems need to reflect that reality through more integrated, life-course approaches to care.

There has never been a better opportunity to do so.

Across the NHS, the shift towards prevention, community-based care and digital transformation aligns closely with the needs of women’s health.

Women’s Health Hubs are already demonstrating the benefits of bringing services together around the needs of women rather than organisational boundaries. Digital technologies are helping to identify risk earlier and support more personalised care.

Innovation can help deliver all three of the NHS’s major transformation ambitions: moving from treatment to prevention, from hospital to community, and from analogue to digital care.

But innovation alone is not enough.

Closing the women’s health gap also requires us to address longstanding gaps in research and evidence.

Women remain underrepresented in many areas of clinical research, and sex-disaggregated analysis is not always applied consistently. The result is that clinical pathways and treatment decisions are often based on evidence that does not fully reflect female physiology.

Better data, stronger research participation and greater focus on female-specific and female-predominant conditions will be essential.

There is also a compelling economic case for action.

Women’s health is often framed as an equality issue, and equality remains central. But poor health affects workforce participation, productivity and economic growth.

Improving outcomes for women benefits not only patients, but employers, healthcare systems and wider society.

Yet despite this, women’s health innovation continues to attract only a fraction of the investment directed towards other areas of healthcare.

That is beginning to change.

Across the UK and internationally, momentum is building. Governments, investors, researchers and innovators increasingly recognise that women’s health is both a societal necessity and an economic opportunity.

The conversation has moved on significantly in recent years. Topics that were once overlooked are now firmly on the policy agenda.

The next challenge is ensuring that awareness translates into action.

The technologies exist. The evidence is growing. The policy direction is increasingly clear.

ABHI is increasingly taking this agenda beyond national boundaries. Through our engagement with international industry associations, policymakers and healthcare leaders, we are working to ensure that women’s health is recognised as both a health and economic priority.

We are helping to shape discussions on innovation, regulation, investment and adoption, while sharing lessons from the UK with partners around the world.

Whether addressing the gender health gap, improving access to diagnostics or accelerating the uptake of new technologies, international collaboration will be essential.

The challenge now is not recognising the need for change, but delivering it.

Women have waited long enough for acknowledgement of the problem. They should not have to wait any longer for the benefits of the solutions that already exist.

ABHI is the UK’s leading industry association for HealthTech. Its members, ranging from multinationals to small and medium-sized enterprises (SMEs), develop and supply technologies spanning everything from syringes and wound dressings to surgical robots, diagnostics, and digitally enabled healthcare solutions. ABHI’s 400 member companies represent approximately 80% of the UK HealthTech sector by value.

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Opinion

Women’s Health has waited long enough for innovation

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By Dr Fran Conti-Ramsden, clinician at Guy’s and St Thomas’ NHS Foundation Trust, academic at King’s College London, and chief medical officer of MEGI Health.

A woman gives birth. A few days later she goes home, often with a bag of medication for her blood pressure, and then, very often, very little structured follow-up for her heart (cardiovascular) health.

In my clinical work, and through our collaboration with Action on Pre-eclampsia, I see and hear about this postnatal cliff edge again and again, and it still shocks me.

We invest a lot of medical care and attention whilst a woman or birthing individual is pregnant, then, at the very moment emerging evidence suggests we have a window of opportunity to modify long-term health, the support falls away.

That cliff edge is a symptom of a deeper issue: we have come to treat “women’s health” as a synonym for reproductive health. Pregnancy, periods and fertility, important as they are, have crowded out everything else.

Yet the conditions that do most to shorten and limit women’s lives are not reproductive at all.

Cardiovascular disease is the leading cause of death in women worldwide, and it is still too readily thought of as a man’s problem.

Heart disease in women is more likely to be missed and under-treated, in part because for decades women were under-represented in the research that built our knowledge.

Pregnancy makes this vivid.

Conditions such as pre-eclampsia are not only risks to be managed for nine months; they are early warnings about a woman’s future, markers that she is more likely to develop heart disease and high blood pressure in the years to come.

We have the knowledge to act on that. What we mostly do instead is discharge her and look away.

This is exactly the kind of problem better tools should help us solve: spotting risk earlier, supporting women and their clinicians through the vulnerable postnatal window, and providing continuity where the system currently provides a drop due to lack of capacity.

Artificial intelligence and digital health have real potential here; in risk prediction, in monitoring blood pressure at home, and in helping stretched clinicians know who needs attention and when.

And yet this is not where most of the energy is going.

It is far easier to build, fund and scale an app that tracks a cycle than a tool that changes the trajectory of a woman’s heart.

So, innovation clusters at the lighter, lower-risk end of innovation, while the conditions that actually kill and disable women, and moments like the postnatal cliff, stay under-served.

Closing the women’s health gap could add at least a trillion dollars to the global economy each year, the World Economic Forum estimates, but the bigger prize is women living longer, healthier lives.

None of this means technology is a cure in itself. It is a tool, and a tool built carelessly can do harm.

Because women have been under-represented in medical data, systems trained on that data can quietly carry the same blind spots forward, deepening inequalities rather than closing them.

Responsible innovation, with clinical-grade evidence, privacy and equity designed in from the start, and tools built around real clinical pathways rather than bolted on afterwards, is not a brake on progress.

It is the only version of progress worth having.

I am optimistic, because a serious community is forming around exactly these questions and the appetite to get it right is real.

It is why, at MEGI, we are bringing clinicians, researchers, founders, regulators and investors together for our AI × Women’s Health summit on 25 June.

If we keep our focus on the conditions that matter most to women’s lives, and build the tools to meet them responsibly, the postnatal cliff edge could become something else entirely: the moment the system finally catches her and delivers preventative healthcare.

AI × Women’s Health: Innovation, Challenges and Opportunities summit is taking place on Thursday 25 June 2026 at the London Institute for Healthcare Engineering. The event is free and is fully booked and operating a waiting list. Join the waiting list here.

About Dr Fran Conti-Ramsden

Dr Fran Conti-Ramsden is a UK Obstetrics and Gynaecology registrar and Chadburn Clinical Lecturer at KCL passionate about transforming women’s health through technology and innovation.

Combining NHS clinical experience with an MRC-funded PhD, recent NHS Clinical AI fellowship and commercial role as Chief Medical Officer at Megi health, she works at the intersection of clinical medicine, data science, technology and AI.

Her current programme of research focuses on the intersection of healthcare and technology; leveraging advances such as smartphone based vital signs capture and large language models to drive forward scalable innovation in maternal cardiovascular care.

She has published over 20 peer-reviewed manuscripts (See gScholar, h-index 12), including award-winning work recognized by Hypertension Journal.

She was awarded an AI visionary award in 2025 by Health Innovation KSS was the recipient of the 2024 International Society for the Study of Hypertension in Pregnancy Zuspan prize.

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