When we first started working on “A Systematic Review of Emerging Trends of IoT in Healthcare and IoMT Frameworks”, our motivation was not just academic curiosity. It came from a much more grounded question: why do so many promising healthcare technologies never reach real patients in a meaningful way?

As students and early-stage researchers working at the intersection of information technology and healthcare, we repeatedly encountered impressive prototypes smart wearables, remote monitoring systems, AI-driven diagnostics that looked promising on paper but struggled in real-world adoption. This gap between what is possible and what is practical became the starting point of our research.

Why IoT and Healthcare?

Healthcare systems worldwide are under increasing pressure from rising chronic illnesses to shortages of medical professionals and limited accessibility in remote regions. The Internet of Things (IoT), and more specifically the Internet of Medical Things (IoMT), has often been proposed as a solution: connected sensors, smart devices, real-time data collection, and automation to support clinicians and patients alike.

However, as we explored existing literature, we noticed fragmentation. Research was advancing rapidly, but often in silos focused either on devices, data analytics, security, or applications without a holistic understanding of how these components interact within real healthcare ecosystems.

This realization led us to undertake a systematic review spanning research from 2011 to 2024, following PRISMA guidelines, to synthesize trends, identify gaps, and understand where IoMT truly stands today.

What We Found: Progress, but Also Gaps

One of the most striking findings of our review was that nearly 80% of existing IoMT research remains theoretical or conceptual, with very limited clinical validation or large-scale deployment. While innovation is thriving, practical translation lags behind.

We identified three persistent barriers across studies:

• Security and privacy concerns, especially due to sensitive medical data and heterogeneous devices
• Interoperability issues, where devices from different vendors fail to communicate seamlessly
• High implementation costs, making solutions inaccessible in low-resource settings

At the same time, we observed encouraging trends particularly the growing integration of AI and machine learning, the rise of wearable health devices, and increasing interest in remote monitoring and home-based rehabilitation.

These insights shaped not only our conclusions as researchers, but also our thinking as technologists and innovators.

When Research Meets Reality

Parallel to this research, we were working on a startup-oriented project that focused on technology-assisted rehabilitation and writing assistance, especially in neuro-muscular recovery contexts. This practical exposure changed how we read academic papers.

For example, while reviewing IoT-based rehabilitation systems, we noticed that many solutions lacked real-time personalized feedback, relied heavily on constant internet connectivity, or were too expensive to scale. Similarly, AI-based healthcare tools often suffered from limited datasets and poor adaptability to individual users.

These weren’t just theoretical limitations we encountered them firsthand while attempting to design systems that could work reliably outside controlled environments.

Our research paper, therefore, became a reflection exercise: a way to critically evaluate what exists, understand why adoption is slow, and identify what future systems must prioritize if they are to move from labs to lives.

Research as a Foundation for Innovation

This paper does not propose a single new device or framework. Instead, it provides a structured understanding of the IoMT landscape, highlighting where innovation is needed most standardized architectures, ethical data governance, affordability, and user-centric design.

For us, this systematic review became the conceptual backbone of our startup vision. It reinforced the importance of building healthcare technology that is:

• modular and interoperable
• secure by design, not as an afterthought
• accessible to patients beyond urban or high-income settings
• supportive of clinicians rather than burdensome

In many ways, the research validated what we were intuitively learning through development and experimentation.

Lessons as Early-Career Researchers

Writing this review as students and early-career researchers taught us that impactful research does not exist in isolation. Literature reviews are often seen as purely academic exercises, but in our case, they became a bridge between research, product thinking, and social responsibility.

It also highlighted the importance of interdisciplinary collaboration healthcare innovation cannot succeed without contributions from technologists, clinicians, policymakers, and ethicists working together.

Looking Ahead

IoMT is no longer a futuristic concept it is already shaping modern healthcare. Yet, as our review suggests, we are only at the surface of what is possible. Much like an iceberg, visible innovations represent only a small portion of the potential beneath.

Our hope is that this work encourages researchers and innovators to focus not just on what can be built, but on what can be adopted, trusted, and sustained. For us, this paper marks both a milestone in our academic journey and a foundation for future real-world solutions.