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Digital Health
Monitor. Analyze. Manage.
Technology solutions that enhance patient care and enable better health-related decision-making.
Medical wearables are transforming the way that patients are cared for. But as these devices become smaller, smarter, more interconnected, and more user-friendly, the technology that underpins them needs to be rock-solid. That is where we come in.
We have decades of experience in designing and creating medical wearable sensor systems, miniaturization, wireless connectivity, and ultra-low-power ASIC design. As an ISO13485 certified partner to the medical industry, we are helping to create medical wearables that prevent diseases, monitor at-risk patients, and enhance behavioral changes.
Research and development in Digital Health technologies
The solutions we are creating have the potential to transform how healthcare is administered to stakeholders. Our projects leverage the power of digital technology in healthcare to develop solutions that not only improve patient outcomes but also streamline clinical workflows.
Sensors, wearables, and the Internet of Medical Things (IoMT)
- Design: Creating wearable or system solutions based on CSEM reference designs for monitoring the cardiovascular system (ECG), respiration (impedance and stethoscope), brain (EEG), and muscles (EMG). Our solutions are also being applied to analysis applications for movement and gait, biomarkers, skin/body temperature, and gas analysis to develop medical devices up to Class III.
- Integration and optimization: Simplifying the integration of medical device components including optical/PPG sensors, dry active electrodes, electrochemical and gas sensors as well as ultra-low-power ASIC and sub-threshold CMOS.
Data Science
- Algorithm development and transfer: Creating innovative algorithms for noninvasive measurement of vital signs. We also integrate existing libraries dedicated to the estimation of vital signs including heart rate and its variability (HRV), blood pressure, oxygen saturation, pulmonary artery pressure, and physical activity profiling.
- Diagnostics and detection: Developing AI-based systems for detecting optical cardiac arrhythmia, falls, risk of falls, sleep staging and apnea, and monitoring point-of-care diagnostics.
- Deployment: Designing, implementing, and validating custom models for medical diagnostics and decision support systems implemented, deployed in embedded systems like nRF SoC, STM32, or cloud solutions like AWS, Azure, CSEM proprietary and on-premises software.
Clinical Assessment
- Clinical studies: Working with our network of university hospitals and participating in the design of study protocols in compliance with relevant standards and norms.
- Data collection: Deploying custom-made IoT smart sensor gateways for collecting vital signs from inpatients and outpatients and streaming them in real-time to custom-made databases.
- Privacy: Using machine learning algorithms and distributed AI technologies to ensure data privacy and security of sensitive clinical data.
© CSEM / Antal Thoma
Want to get involved in digital healthcare?
We can help you utilize cutting-edge technology to provide better outcomes for patients. We know the sector, we know the technology, and we know how to take great ideas and turn them into practical and effective medical wearables solutions.
Extensive collaboration with a range of leading Swiss university hospitals has led to the development of medical devices (Aktiia, Inspiring, and others). We would love to collaborate with you too.
Bern Medtech Collaboration Call (BMCC)
To help the Canton of Bern become a leading medtech innovation hub by 2030, Insel Group, the University of Bern, and CSEM collaborate in the frame of joint research and development projects. This initiative is called Bern Medtech Collaboration Call.
Innovative Digital Health solutions: Wearables, sensing, and continuous monitoring
Presenting CSEM’s state-of-the-art continuous monitoring systems designed to provide accurate and reliable data for various health applications.
Digital medical devices
Digital health tech and development
Meet our happy customers
Mattia Bertschi
COO
Aktiia aims at reducing the burden of hypertension with just a sleek bracelet, the fruit of more than 15 years of research and development done at CSEM. Their multidisciplinary team, scientific approach, and passion for innovation have been invaluable throughout the creation of our breakthough solution for cuffless blood pressure monitoring.
Professor Patrick Schoettker
Chief Medical Advisor
CSEM has experience working with the watchmaking industry and is a world-leading expert in oscillator systems. That’s where you go when you’re seeking technologies that break the mold.
George Kouvas
CTO
CSEM’s know-how in the field of medicalgrade wearable devices and experience in sensor technologies have helped us realize the desired capabilities for EPIOS. We are very much looking forward to trialing the system and helping improve quality of life for people living with neuro-disorders.
Marco Pisano
CEO
Lymphatica’s first artificial lymphatic vessel for the treatment of lymphedema is composed of an implanted micropump, controlled externally via a wearable device. Working with CSEM allowed us to develop and produce the first series of wearable controllers to be used in a firstin- man clinical investigation in lymphedema patients.
Cléo Moulin
Clinical Innovation Manager
Thanks to CSEM’s expertise in wearable sensors, signal processing, and medical devices we will accelerate the launch of a disruptive device blending advanced 3D sensor technology with clinically validated algorithms. This will transform the management of patients with severe motor impairments and reduce healthcare costs.
Ilkka Korhonen
CTO
We worked with CSEM to develop a prototype next generation wearable heart rate tracker. Combined, their technical excellence, deep understanding of a companies needs, agile research approach and focus on outcomes was both impressive and unique.
Beat Gersbach
CEO
With the help of CSEM we will open up our aphasia app—which provides training for people who have lost their ability to speak due to stroke—to other languages. We believe there will be semantic differences between languages, and this has to be transferred into machine language models of meaningful content.