Core Engineering Constraints in Wearable Product Development
Building next-gen wearables is ultimately a game of three unforgiving budgets: energy, time, and trust. This is especially true in wearable firmware development, where power, latency, and update hygiene define real-world success.
1. Power Budget
Embedded systems must efficiently process and transmit complex data in real time while maintaining low power consumption. Real-time machine learning models, crucial for advanced functionalities, must be lightweight to run on low-power devices, often necessitating techniques such as model compression and pruning. The industry’s pursuit of ultra-slim designs introduces high-density battery thermal runaway risks, which can lead to increased design iterations, delayed launch timelines, and higher supply-chain costs.
Overall, short battery life remains a general concern in wearable product development. This makes low-power wearable design and power-budget optimization a first-class requirement for any project.
Bogdan Popescu, Technical Director at rinf.tech within the R&D Embedded Systems division points out that “In wearable devices, it is essential that the operating system is configured to activate only those kernel components that are absolutely necessary, such as memory management, the process scheduler, and the I/O system.” According to Bogdan, “This ensures minimal resource consumption and maximizes battery life, while still allowing applications to run smoothly enough to be usable. For example, if the system consumes too many resources, an ECG monitoring app would only be able to take readings at a very low frequency, resulting in significant inaccuracies. In addition, when reading values from various sensors, there are two possible interface types: SPI and I2C. In some of the projects we developed, tests were conducted using both types, and the accuracy of the readings was found to be identical. Based on this, SPI was selected because it allows the sensor to consume less power than with I2C – an important factor for extending battery life.”
2. Latency
Real-time data collection and analysis are crucial for providing immediate feedback, coaching, education, and remote support. Edge AI reduces dependence on the cloud for the fast path, improving responsiveness and resilience. Advanced connectivity solutions, such as 5G Stand-Alone modules, can support low-latency streaming, but end-to-end results vary by network and deployment.
3. Security Updates and Data Privacy
Wearable devices collect highly sensitive physiological and behavioral data, which raises significant concerns regarding privacy and security. Robust encryption, anonymization, and strict compliance with regulations such as HIPAA in the US and GDPR in the EU are essential.
From day one, treat secure OTA updates for wearables and a maintained SBOM for wearables as non-negotiable parts of the architecture.
4. Development of On-Device Applications for Small Displays
Finally, Andrei Hutuca, R&D Embedded Systems Technical Delivery Manager at rinf.tech, points to another challenge associated with wearables development projects – the development of on-device applications for small displays: “To address the limitations of small display sizes, two categories of applications must be developed for these devices: apps that run directly on the device and apps that run on a smartphone paired with the device. On-device applications must be adapted to the small screen size (approximately 3×3 cm) and the resolution supported by the device to ensure optimal usability. This requires a process of experimentation and adaptation in the way applications are designed for the device.”
According to Andrei, “For smartphone-based applications, the main challenge lies in how the phone connects to the device and how smoothly the app can extract data from it without causing any noticeable interruptions for the user. Another technical difficulty, influenced by connection quality and sensor data accuracy, is the need for apps to include mechanisms that detect and handle situations where received data is erroneous, or to filter out values considered outside the normal range for a specific user. These mechanisms must be personalized for each user and cannot rely on standard thresholds – as every individual is different.“
Why Wearable PoCs and Advancements Stall
Last Mile Engineering
The urgent need for advanced R&D in embedded systems, particularly as devices become more intelligent and interconnected, often encounters critical bottlenecks, such as the ones described earlier. These challenges frequently lead to promising Proof of Concepts (PoCs) stalling before market readiness. This is where a seasoned wearable software development partner can de-risk the handoff to production.
As the wearables market remains massive and is expected to grow steadily through 2027 across segments, only wristbands are projected to slow down in the coming years. Thus, a core tension continues: product leaders want more on-device intelligence but must sustain multi-day battery life. As a result, PoCs or product advancements typically stall at the last-mile engineering step: prototype-to-production wearables that are certifiable, maintainable, and secure.
Bridging this gap involves rigorous testing, adherence to complex regulatory compliance, advanced optimization for power and performance, and seamless integration across diverse hardware and software components. Projects can falter at this juncture due to a lack of specialized expertise in areas such as ultra-low power design, robust security implementation, or navigating the intricate landscape of global certifications. This final, often most challenging phase demands precision and deep technical acumen to mitigate risks, accelerate time-to-market, and ensure the successful productization of complex wearable innovations.
Challenges Leading to PoCs Stalling and Hindering Product Advancement