Connected Devices & AI in Patient Monitoring
During a session at MD&M West 2026 focusing on the shift from reactive to predictive healthcare, MedTech analyst Etienne Nichols at Greenlight Guru emphasized how connected devices and AI‑enabled monitoring are reshaping patient management. His anecdote about his wife’s pacemaker underscored the value of reliable device connectivity and data governance in modern care.
Nichols pointed to emerging AI‑driven tools, such as predictive glucose monitoring, that adapt to patient behavior and improve outcomes. This aligns with broader industry trends in wearable and digital health innovation, as developers leverage sensors and algorithms to move from simple tracking to anticipatory insights.
Last July, the FDA issued a warning letter to WHOOP, alleging that the company’s Blood Pressure Insights feature is a noncompliant and improperly labeled medical device marketed without required FDA clearance or approval. WHOOP countered that the feature belongs in the general wellness category and accused the agency of overreaching.
Earlier versions of the FDA’s guidance on clinical decision support (CDS) software upset many companies in the industry. They argued the FDA was interpreting the law too strictly and saying fewer types of CDS software were exempt from being regulated as medical devices than what Congress truly intended.
Industry groups contended Congress meant to allow more CDS software to avoid heavy medical device regulation, but the FDA took a more cautious approach and limited those exemptions.
The stricter FDA interpretation could officially change. “Two weeks ago, the FDA shared a guidance document about how they will practice enforcement discretion on wellness devices, and that stems from the reaction of how the WHOOP case went,” said Nichols. “Apple’s lobbying too. Long story short, the wellness industry is likely about to see a boom, because the enforcement, the FDA, is rolling back their enforcement discretion. They’re saying, ‘Okay, you are a blood pressure monitor, but you’re just for wellness. Depending on your claims, we will leave you alone.’”
The landscape of data use and privacy is undergoing a magnitude of high-stakes evolution driven by the proliferation of AI adoption. Nichols’ perspective is a timely reminder that success will depend on disciplined execution and that organizations need real-world performance monitoring, stronger data science fluency across teams and clearly defined criteria for AI tools operating in the field.
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Rehana Begg, Editor-in-Chief, Machine Design
