Welcome, MedTech Professionals.

W46 Edition of The MedTech AI Monitor

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Hey there,

Thanks for tuning into this week's update, where I try to cut through all the hype and write about valuable and real-world uses of Artificial Intelligence.

If you want to chat about using or governing AI in your organization, put some time on my calendar: https://calendly.com/greg-avip/25min​

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Let's start with a quick story about rollerblading.

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tl;dr

-Rollerblading is metal

-AI wearables market > $130B by 2029

-How do wearables actually use AI? Insanely fast image processing.

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For the past 10ish years, I've bladed in the NorthShore Inline Marathon. The route follows Lake Superior, and it is a ton of fun. Think a running marathon, but 100x better because you don't have to... run.

The race starting out great- watching the sun rise over the massive lake. But 1 mile from the finish line, a guy fell down. By the time I got close, there was a group alternating chest compressions. When the ambulance arrived, we all were told to head to the finish line.

I found out he didn't make it. Cardiac arrest. He was 37.

It was a pretty somber event end. Later that same day I happen to stumble upon a LinkedIn video of an AI-enabled device, a wearable ultrasound system. Real-time heart and muscle function alerts. For hospital and at-home (or on the go) use.

This is where I see the amazing use of AI/ML. Not just "ChatGPT: write this email to my boss", but something really important, devices that can save lives. I think 20 years from now, health diagnostic wearables will be as common as iPhones.

If you have any interest in trying something new- check out the NorthShore Marathon. You don't have to be in great shape to compete (and there's a 1/2 marathon option).

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Hyper growth of AI-enabled wearables

The global wearable AI market size was valued at USD 62.7 billion in 2024 and is estimated to reach USD 138.5 billion by 2029. (M&M)​

There are a handful of companies making ultrasound wearables, the clip I saw was from a startup called Sonologi out of Palo Alto.

If you are an athlete, coaches and medical staff can assess real-time cardiovascular health (like arrhythmias), muscle strain, and fatigue levels.

“Imagine a future where real-time, continuous imaging is as ubiquitous as EKG or oxygen monitoring—inside and outside the hospital.”

How does it actually use AI? This device only uses Predictive Machine Learning (ML) for two functions:

1. Compensating on-the-fly movement to maintain image stability
2. Recording, monitoring, and alerting potential health issues over time

GenerativeAI: (think ChatGPT)

PredictiveML: (think forecasting models)

Predictive ML focuses on analyzing existing data to forecast outcomes or extract insights. Generative AI creates new data.

Future devices could apply generative AI models to enhance/reconstruct low-quality ultrasound images, filling in missing details or improving resolution.

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In the weeds

If you're interested in the science behind this type of AI-enabled wearable, check out this paper.​

1. Traditional non-invasive imaging methods are limited by bulkiness, and only capture surface signals.
2. Innovations in device design and materials improve skin-device coupling, allowing for multi-view left ventricular imaging during motion.
3. By applying a deep learning neural network to extract key information (for example, the left ventricular volume in apical four-chamber view) from the continuous stream of images, you can dramatically reduce variability.
4. This model generates waveforms for key cardiac metrics, including stroke volume, cardiac output, and ejection fraction.
5. The technology enables accurate, dynamic cardiac monitoring while biking, running, sleeping, etc.