CSEM

"We can change it later” deserves a closer look before a medical-device function goes into silicon. A sensing interface may be well understood. A classification algorithm may still evolve as the team collects more representative physiological data. I’d be cautious about treating both as equally ready for fixed hardware. The architecture needs to deliver useful efficiency today while leaving room for foreseeable changes and the verification work those changes may require. I explore that balance in this article on connected medical devices: https://lnkd.in/d_bpJgmJ #CustomASIC #MedicalDevice #EmbeddedAI #UltraLowPower #AI CSEM Bahaa R. Stephane Emery Paulo Augusto D. Dragan Manic Gabriel K. Nadim Maamari Pascal Nussbaum Josef Hayoz Mathieu Lemay Jens Krauss

𝗔 𝗽𝗮𝘁𝗶𝗲𝗻𝘁 𝘄𝗶𝗹𝗹 𝗲𝘃𝗲𝗻𝘁𝘂𝗮𝗹𝗹𝘆 𝗹𝗲𝗮𝘃𝗲 𝘁𝗵𝗲𝗶𝗿 𝗽𝗵𝗼𝗻𝗲 𝗶𝗻 𝗮𝗻𝗼𝘁𝗵𝗲𝗿 𝗿𝗼𝗼𝗺. 𝗧𝗵𝗲 𝗺𝗲𝗱𝗶𝗰𝗮𝗹 𝘄𝗲𝗮𝗿𝗮𝗯𝗹𝗲 𝗻𝗲𝗲𝗱𝘀 𝗮 𝗽𝗹𝗮𝗻 𝗳𝗼𝗿 𝘁𝗵𝗮𝘁. Can it continue monitoring? Which measurements will it retain? When the connection returns, can the system reconstruct the sequence without losing the original timestamps? These are ordinary situations with consequences for how the care team interprets the data. I explore them in this article, including why reliable remote monitoring depends on what happens during a disconnection: https://lnkd.in/e35hqSxV #RemotePatientMonitoring #MedicalWearables #ConnectedHealth #DigitalHealth #Medtech Fabian Braun Christopher M. Mathieu Lemay Damien Ferrario Gürkan YILMAZ João Jorge Adriano Giovannini Jens Krauss Martin Proença Alia Lemkaddem

𝐖𝐡𝐞𝐧 𝐚 𝐩𝐚𝐭𝐢𝐞𝐧𝐭’𝐬 𝐦𝐞𝐚𝐬𝐮𝐫𝐞𝐦𝐞𝐧𝐭𝐬 𝐝𝐢𝐬𝐚𝐩𝐩𝐞𝐚𝐫 𝐟𝐫𝐨𝐦 𝐚 𝐫𝐞𝐦𝐨𝐭𝐞-𝐦𝐨𝐧𝐢𝐭𝐨𝐫𝐢𝐧𝐠 𝐝𝐚𝐬𝐡𝐛𝐨𝐚𝐫𝐝, 𝐬𝐨𝐦𝐞𝐨𝐧𝐞 𝐡𝐚𝐬 𝐭𝐨 𝐰𝐨𝐫𝐤 𝐨𝐮𝐭 𝐰𝐡𝐲. Was the wearable removed? Did the sensor lose contact? Is the phone out of range? On screen, those situations can look similar. For the care team, they call for different responses. I think medical devices should help explain these gaps. Otherwise, healthcare professionals inherit technical uncertainty alongside the patient data. In this article, I explore what that means for the architecture behind remote care: https://lnkd.in/e35hqSxV Zohaib Gulzar Jens Krauss Mathieu Lemay Damien Ferrario Adriano Giovannini Gürkan YILMAZ Christopher M. Fabian Braun Alia Lemkaddem Martin Proença Oskar T. James Rosenthal João Jorge #medtech #medicalasics #wearables #digitalhealth #medicaldevices

In a medical wearable, the AI model only gets the signal the device manages to capture. A PPG measurement affected by motion or an ECG signal compromised by poor contact gives the algorithm a harder starting point. That’s why we pay as much attention to acquisition as to inference. Sensor interfaces, noise performance, and filtering choices influence what information remains available for analysis. In this article, I explore the engineering decisions that come before AI and why they matter for intelligent medical devices. Read the Article Below #MedicalDevices #WearableTechnology #EdgeAI #ASIC #MedTech https://lnkd.in/eVnfrHTu

Not every dangerous driver state looks like drowsiness. 👀 A driver may appear tired when the real issue is a hidden medical event. DriverCheck, a technology developed by CSEM uses contactless, privacy-first AI to detect subtle warning signs. Watch the video: https://lnkd.in/eRK82_aA #DriverMonitoring #RoadSafety #EdgeAI

🏭 The AI race is not about models. It is about production. 🤖 Last week at the World Economic Forum in Davos, one message kept coming up: the next AI winners will not be the ones closest to the cutting edge. They will be the ones who can industrialize AI. ⚙️ In the AI game, Europe is entering Phase 2: scaling AI in the real world, building on the strengths we are known for: manufacturing, system integration, quality, and reliability. 🔋🤝 In this short clip, CSEM’s Tonio Buonassisi and Vincent R. share why connecting AI and industry creates a new flywheel for Europe, and how we are making it concrete at CSEM, from automation to our Battery Innovation Hub. No matter where you are on your AI + automation adoption journey (lab to pilot, or pilot to production), let's talk!🚀 💬 Question for you: what is the biggest barrier you see today between AI pilots and full scale industrial deployment? #ArtificialIntelligence #IndustrialAI #AIinIndustry #Industry40 #DeepTech