Health Monitoring with Edge AI: Insights from Ambiq's Carlos Morales

In the urgent field of digital health, the combination of artificial intelligence and ultra-low-power computing is transforming possibilities for personal wellness and medical monitoring. In a recent Wevolver webinar, Carlos Morales, Vice President of AI at Ambiq, engaged in a presentation with Samir Jaber on how the company's technology is paving the way for a new generation of intelligent, energy-efficient health monitoring devices that operate at the edge.

Why Health Monitoring Needs Edge AI

The growing demand for continuous health tracking—spanning heart rate, sleep quality, respiratory function, and beyond—requires devices that are always on, always aware, yet discreet and energy-efficient. Traditional cloud-based processing can’t meet the latency, privacy, or power constraints of wearables or other on-body sensors. That’s where Ambiq comes in.

Carlos Morales explained how Ambiq’s ultra-low-power solutions are enabling real-time, on-device AI for wearable health monitors that can run sophisticated algorithms while consuming minuscule amounts of energy. This technology makes it possible to track vital biometrics without frequent recharging, a crucial advantage for devices like fitness trackers, medical patches, and smartwatches.

Always-On Intelligence for Personalized Health

One of the key insights from Morales was that Ambiq’s platform supports “always-on” capabilities—devices that continuously monitor signals such as heart rate variability or blood oxygen levels and flag anomalies without relying on cloud connectivity. This opens up possibilities for early warning systems, personalized fitness tracking, and even remote patient care.

He emphasized that “health monitoring is one of the clearest use cases for edge AI,” citing how Ambiq’s solutions allow developers to run complex machine learning models directly on-device. Whether it’s detecting abnormal breathing patterns or monitoring cardiovascular strain, these models can now run efficiently on wearable hardware that lasts days—or even weeks—on a single charge.

Use Cases: From Fitness to Clinical-Grade Monitoring

Throughout the webinar, Morales highlighted several real-world applications made possible with Ambiq's technology:

• Fitness wearables that can adapt workouts based on real-time physiological data.
  
  
• Sleep trackers that use AI to analyze sleep stages and recommend behavioral changes.
  
  
• Medical devices that monitor ECG or blood pressure trends and alert users or healthcare professionals about irregularities.
  
  

In one notable case, Ambiq-enabled wearables were used to monitor post-operative patients remotely, enabling hospitals to discharge patients earlier while still maintaining visibility over recovery—reducing costs and improving patient satisfaction.

Energy Efficiency as a Health Imperative

Energy efficiency isn’t just a nice-to-have in health devices—it’s a core requirement. Morales pointed out that minimizing energy consumption extends battery life and reduces device size, which enhances user comfort and long-term adoption. Ambiq’s SPOT® platform (Subthreshold Power Optimized Technology) lies at the heart of this value, allowing for ultra-efficient AI inference at the edge.

This enables not just better battery life, but also devices that can be thinner, lighter, and more discreet—all essential for wearable health monitors and implantable tech.

Closing Thoughts

Carlos Morales closed the session with a call to action for engineers and developers to consider how they can leverage edge AI for the next wave of health innovations. He encouraged the audience to think not just about what AI can do, but how and where it operates—and to prioritize power efficiency and user comfort alongside performance.

With edge AI platforms like Ambiq’s, the future of health monitoring is not just smarter—it’s more accessible, reliable, and personal. Watch the full webinar above. 

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