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• AI Algorithm in Medical Robotics

  Politecnico Di Milano (POLIMI)

  Providing expertise in the field of medical robotics (medical imaging for surgical planning, virtual reality, extended reality) to be eventually tailored to specific projects: 1) Definition of applications objectives 2) Data collection, data curation and bias evaluation 3) Preprocessing and optimization of feature extractions 4) Selection of suitable machine learning models, model training and testing 5) External validation 6) Interpretations of models (XAI algorithm applications and development) Keywords: AI, algorithm development, AI testing and validation, Medical Imaging for Surgical Planning, Virtual Reality, Extended Reality

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• Biomedical Data acquistion- Autonomic nervous system

  Univerzita Komenskeho V Bratislave (UK BA)

  The laboratory performs research and scientific activities in the research of autonomic nervous system regulation. It uses Finometer (FMS) and Nexfin (Edwards Lifesciences) devices, which are used for non-invasive beat-to-beat blood pressure monitoring using volume-clamp method, and MedGem (Microlife) for determination of basal metabolism. It uses ECG Cardiofax 9620M (Nihon Cohden) for monitoring the electrical activity of the heart, RespiTrace (NIMS) for non-invasive respiratory monitoring by impedance method using chest and abdominal belts, CardioScreen 2000 (Medis) for non-invasive monitoring of various parameters associated with pumping function of the heart (systolic volume, systolic time intervals, etc.). It uses VaSera VS-1500N (Fukuda Denshi) characterization of arterial stiffness, EndoPAT 2000 (Itamar Medical) - characterization of endothelial dysfunction, InBody J10 (Biospace) - analysis of body composition, ECG (BTL; Pola V8) - non-invasive continuous bio signals monitoring, Finometer (Finapres medical systems), blood pressure, Flex Comp Infinity, Thought Technology for measuring the electrodermal activity, respiration, peripheral temperature, Neuroptics PLR200, pupilometry, Eyetracking (Pupil Labs) for eye movements, InBody 120 - body composition analysis.

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• BioSignal Suite: Design and Validation of Biomedical Signal Processing Pipelines

  Karolinska Institutet (KI)

  ## Overview This service supports the development and validation of biomedical signal processing pipelines for healthcare applications. SMAILE at Karolinska Institutet provides guidance for processing a range of biosignals, including ECG, EEG, EMG, respiration, accelerometers, gyroscope, and electrical bioimpedance. The focus is on signal filtering, feature extraction, event detection, and pipeline validation, aligned with clinical research standards. ### We provide expertise in: • Biomedical signal filtering and preprocessing • Feature extraction and clinical event annotation • Signal Analysis and Modeling • Quality assurance and reproducibility ### How can the service help you? Many early-stage companies and research projects lack robust, validated signal pipelines. This service enables reproducible analysis, clinical readiness, and regulatory alignment for biosignal-driven products and studies. ### How will the service be delivered? Can be delivered virtually or in conjunction with lab access. Clients share sample datasets, objectives, and processing goals. Duration: 2–6 weeks based on complexity. ## Additional Information ### Provider Description SMAILE provides advanced support in biomedical signal analytics, with experience in wearable health monitoring, digital phenotyping, and clinical-grade biosignal systems. ### Technical Description Pipelines are constructed and validated using Python (SciPy, MNE, NeuroKit), MATLAB, or other signal tools. ### Service Customization Clients may request focused support for real-time processing, offline batch analysis, or integration with AI modules. Output formats, sampling rates, and noise tolerance are adjustable.

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• Brain Digital Twins for clinical and pharmacological applications

  Universita Degli Studi Di Pavia (UNIPV)

  This service offers the construction and simulation of brain digital twins for neurological and neuropharmacological applications. The simulations are typically applicable to single subject data for developing personalized medicine and pharma. Method description: Raw structural and functional data is preprocessed and analyzed to create brain connectivity data. The computational framework is tuned against experimental data to simulate brain dynamics and optimize physiological parameters, e.g., excitatory and inhibitory activity. In order to obtain personalized digital brain twin single-subject data must be used. Method reference: Local method respecting General Data Protection Regulation (GDPR)

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• Clinical Feasibility Assessment & Real-World Validation

  Fraunhofer Gesellschaft Zur Forderung Der Angewandten Forschung Ev (Fraunhofer)

  **Who Can Benefit:** - Clinical Researchers and Investigators: For gaining insights into the feasibility of proposed studies and enhancing study designs with practical clinical input. - Healthcare Institutions: To expand research capabilities by connecting with technical and clinical experts and facilities. - Research and Development Teams: For testing new technologies or methodologies in applicable clinical contexts, ensuring innovative solutions are viable and effective. **Key Features:** - Technical Feasibility Assessment: Organizes and conducts comprehensive technical feasibility studies to evaluate the practicality and potential of clinical research projects. - Connection to Clinical Personnel: Facilitates collaboration between researchers and clinical experts at University Clinic Erlangen, ensuring access to expertise and resources necessary for study success. - Access to Real-Life and Laboratory Test Environments: Provides opportunities to conduct studies within associated clinics, leveraging previous experience in cardiology, neurology, and biomechanics to ensure practical and applicable results. **Possible Applications:** - Project Feasibility Evaluation: Assists in determining the feasibility of clinical research projects, helping to identify potential challenges and solutions early in the development phase. - Research Collaboration: Enhances research outcomes through the integration of clinical expertise and real-world testing environments, ensuring studies are rooted in clinical reality. **Who We Are:** The **Fraunhofer Insitute for Integrated Circuits (Fraunhofer IIS)** has established the **"Center for Sensor Technology and Digital Medicine" (CEMDIS)** in cooperation with the Universitätsklinikum Erlangen and the Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) to enhance modern healthcare through **innovative sensor technology** and **digital solutions**. This center focuses on integrating **innovative medical technologies** such as **wearables** and **robotic systems** to support **medical diagnostics**, **patient monitoring** and **evaluating patient-specific therapies** by providing digital health solutions für real-life healthcare. Located at the Universitätsklinikum Erlangen, it offers unique infrastructures for the **development**, **integration**, and **validation** of novel health technologies, providing companies opportunities for **technological advancements**. For more information, visit the [Fraunhofer IIS website](https://www.iis.fraunhofer.de/de/ff/sse/health/zentrum-sensorik-medizin.html).

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• Clinical Research Services - Technical support (AI)

  HUMANI SC - Hospital network (HUMANI)

  Technical feasibility study for the implementation of medical devices in acute care areas, such as operating theatres, intensive care units, etc. Support for interfacing sensors and medical devices to a data warehouse. Carry out maintenance and monitoring activities to ensure the connectivity of the device to be tested with the infrastructure and the transmission of data. Support in implementing the solution. Daily technical support for care unit beta-testers. Technical evaluation report on the solution (functionality, ergonomics, durability, etc).

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