Digital Health

Photoplethysmography and optical sensing

Building on long-standing expertise in photoplethysmography (PPG), CSEM develops high-performance optical sensing solutions. By leveraging optical PPG data, CSEM’s advanced vital signs algorithms extract a wide range of physiological parameters, including blood pressure, cardiac arrhythmia detection, oxygen saturation (SpO2), sleep metrics, heart rate, heart rate variability, breathing rate, and stress levels. 

In addition, CSEM leads pioneering research in remote PPG, speckle photoplethysmography, and laser Doppler flowmetry, advancing the frontiers of non-invasive cardiovascular and perfusion monitoring.

Biopotential and bioimpedance monitoring

CSEM develops advanced biopotential and bioimpedance monitoring technologies for Digital Health and medical applications. Our expertise covers a wide range of sensing modalities—including ECG, EEG, EMG, EoG, EHG, fECG, ECGi, as well as electrical impedance tomography (EIT), thoracic impedance monitoring, impedance cardiography, and impedance plethysmography.

CSEM’s expertise encompasses both traditional biopotential and bioimpedance systems, as well as innovative solutions based on its patented cooperative sensor (CS) technology. Leveraging ultra-low power, custom ASICs, this scalable CS-platform enables high-quality signal acquisition via up to 250 active dry or gel electrodes connected through a single unshielded cable of maximum 2 wires—ideal for multi-channel monitoring and imaging wearables in clinical environments, Digital Health, and research.

Current R&D activities address pregnancy monitoring and non-invasive assessment of pulmonary artery pressure (PAP) based on a combination of EIT and ECG. They also explore multifrequency EIT for continuous, non-invasive monitoring of blood glucose or other analytes.
  

Emerging sensing technologies

CSEM is actively exploring emerging sensing technologies to drive tomorrow's wearable vital signs monitoring solutions. These R&D activities include compact ultrasound sensors combined with tailored reconstruction and processing algorithms, digital stethoscopes with enhanced sensing and interpretation capabilities, as well as innovative skin and core body temperature sensing approaches.

Gait and motion analysis

CSEM develops technologies and algorithms for analyzing and tracking motion across multiple body locations, including the wrist, foot, thorax, and head. Our algorithm portfolio covers activity classification, gait analysis, fall detection, workout profiling, sleep monitoring, and motion and gesture recognition.

Our step detector has been independently verified as best-in-class for accuracy. All solutions are designed for real-time operation with minimal power and memory requirements, making them ideal for embedded Digital Health and fitness applications. 
   

Data Science and AI in healthcare

CSEM offers a clinically validated portfolio of vital signs algorithms, many of which are medical-grade and available for licensing. Beyond ready-to-use solutions, we develop custom vital signs algorithms by combining classic signal processing with machine learning (ML) and artificial intelligence (AI) to meet specific application needs in healthcare—for both on-edge devices and cloud-based environments. 
   

Gen AI and LLMs in Digital Health

We also explore the integration of generative AI and large language models (LLMs) into Digital Health ecosystems. We develop agentic frameworks that combine classical databases with retrieval-augmented generation (RAG) techniques to provide timely, context-aware information to clinicians and patients. These approaches aim to enhance clinical decision support, streamline workflows, and personalize patient engagement through intelligent, adaptive interfaces. 
   

Internet of Medical Things and Custom Mobile Apps

Our evolving expertise in advanced sensing technologies for wearable vital signs monitoring is complemented by a robust, evolving Internet of Medical Things (IoMT) framework and custom mobile applications, enabling secure, real-time remote patient monitoring across clinical and home environments. 

• Licensing of Digital Health sensing and algorithm IP: We give you access to our portfolios of sensing technologies and vital signs algorithms for medical devices and wearables.
• ISO 13485/IEC 62304-compliant co-development and medical system engineering: CSEM offers end-to-end support for medical device and system development under its ISO 13485-certified quality management system and IEC 62304-compliant processes for medical software. We integrate hardware, firmware, and algorithms with rigorous risk management and regulatory alignment.
• PPG services: CSEM offers expert support in photoplethysmography (PPG), from concept to implementation. Our PPG services include sensor architecture design, optical path optimization, signal conditioning, and algorithm integration—tailored to your application needs.
• Custom algorithms development: We support you in developing your vital signs algorithms, be it by using classical signal processing, with machine learning (ML) and artificial intelligence (AI) —for both on-edge devices and cloud-based environments.

• Clinical research trial support: With decades of experience in clinical research and validation studies—particularly with vital sign monitoring devices that generate large volumes of continuous data—CSEM offers comprehensive end-to-end support for your clinical trials. Our expertise covers every stage, from study design to data acquisition, analysis, and interpretation, ensuring reliable outcomes. To support your studies, we provide access to our proven wearable demonstrator platforms and our secure IoMT platform (see below).
• Loan of wearable demonstrator platforms: CSEM offers a portfolio of wearable demonstrator platforms that showcase our advanced sensing and algorithmic capabilities across a wide range of applications—from cardiac and respiratory monitoring to maternal and fetal health. The platforms enable evaluation, integration, and clinical research.
• Secure IoMT platform: Our secure internet of medical things (IoMT) platform, built on a robust cloud infrastructure and advanced digital stack, delivers seamless data management, real-time monitoring, and full compliance with data privacy and regulatory standards—providing a trusted backbone for connected healthcare solutions. This platform enables secure remote monitoring and efficient data handling and can, for example, be deployed in clinical studies, as successfully demonstrated in the Swiss Fever Project.