Wearables have enjoyed a meteoric rise in popularity in recent years to the point that one in four of us now wear a smart connected device. Fifteen years ago, it was one in 100 people[1]. This growth in ownership has been driven to an extent by convenience and integration. The ability to see call, text, email, and app notifications, control media, make contactless payments, and receive travel and navigation prompts without removing your phone from your pocket or bag provides the seamless connectivity and enhanced user experience we have all come to expect from our technology in 2025.
Overwhelmingly though, health monitoring and management and fitness and lifestyle enhancement are the leading drivers of wearable tech. The ‘quantified self’ movement—where individuals use data-tracking tools to monitor, analyze, and improve their health, fitness, and productivity—has powered a market that was valued at $84 billion in 2024 and is projected to reach $186 billion by 2030[2].
As wearables have gradually shifted from step counters and fitness trackers to sophisticated health monitors, so we are now seeing the next step in that progression, to devices that can provide clinicians as well as consumers with useful health data. In fact, according to research from analyst GWI, already one in five of us value the ability of wearables to help doctors manage our health[3].
The wealth of data generated by wearables offers immense potential for doctors to make more informed clinical decisions about risk, diagnosis and treatment. Wearables provide continuous real-world monitoring, unlike snapshots taken during occasional clinic visits, and can flag subtle physiological changes before symptoms escalate. They also support remote monitoring and virtual care important for elderly patients, post-surgical monitoring, and chronic disease management.
Despite the obvious potential benefits, the integration of wearable data into clinical practice also presents challenges. Healthcare professionals have expressed concerns about the accuracy and reliability of data from consumer-grade wearables, while there is also apprehension regarding data privacy and the potential for information overload, which could strain healthcare systems.
These issues will take time to iron out, but developers are working on it, and as accuracy, integration, and clinical protocols improve, the use of wearable data in healthcare is set to become mainstream, not marginal.
Today, the technology available to space- and resource-constrained devices means accurate and reliable data is possible from both wrist- and finger-worn wearable devices, including a host of valuable health markers such as the wearer’s V02 max, blood oxygen saturation (Sp02), temperature, heart rate, heart rate variability (HRV), and sleep data.
AI and ML models can filter ‘noisy’ data caused by issues such as sensor drift and skin interference, and recognize patterns—typical resting heart rate and pulse waveform, for example—and then flag anomalies that genuinely matter, and ignore outliers that don’t.
Sensor fusion, meanwhile, enables a device to combine different data streams from multiple sensors, eliminating noise and determining which data points from which sensors correspond to the same health concern, and which do not.
To provide ML and sensor fusion at the edge while simultaneously undertaking a heavy computational workload and supervising reliable and secure wireless connectivity, places significant demands on the wireless SoCs that power today’s advanced health wearables.
And as wearables are designed to be worn comfortably and imperceptibly around the clock, size and weight are also key considerations. That means the SoCs that power them must pack a lot of hardware—an MCU, radio, memory, security features—into a package that in the case of a smart ring might measure no more than 8 by 3 mm. These space constraints also immediately limit the size, weight, and capacity of the battery that can be used in the wearable. As a result, power consumption is always a critical design consideration, and the SoC used needs to be optimized for ultra-low power consumption.
Chipmakers have responded to the strict size constraints of today’s wearables by releasing ever more powerful SoCs in smaller packages. Nordic Semiconductor's nRF54L Series, for example, offers an ultra-compact 2.4 by 2.2 mm WLCSP variant 50 percent smaller than its comparable predecessor, while at the same time doubling the processing power, tripling the processing efficiency, and lowering the power consumption.
Within the series, the nRF54L15 offers the largest memory capacity with 1.5 MB non-volatile memory (NVM) and 256 KB RAM, ideal for demanding, clinical grade wearable applications. In addition to expanded memory, the nRF54L Series integrates a low-power RISC-V coprocessor, supporting advanced application requirements without additional external components, reducing BOM costs, and again enabling compact designs.
And with consumers ever vigilant about protecting their sensitive personal data, the nRF54L Series prioritizes security by design, integrating features such as Arm TrustZone isolation, tamper sensors, and hardened cryptographic accelerators to fulfill essential-to-advanced security requirements.
The next steps towards more widespread clinical adoption lie with regulators as much as developers. Today’s advanced SoCs can undertake the workload, and hundreds if not thousands of devices are already in use, but not enough of them have been approved for clinical use by regulators. Approvals are expensive and time-consuming and the incentives to obtain them are limited compared to marketing devices directly to consumers as ‘well-being tools’.
That said, none of the barriers to clinical adoption are insurmountable with a multi-faceted approach. By improving data accuracy, establishing regulatory frameworks, ensuring data privacy, and ensuring wearables are accessible and user-friendly for patients, wearables can become a valuable tool in personalized medicine and chronic disease management.