Biomedical Engineering Applications of Quantum Sensors

This Applied and Technical (Level 3) course, developed by Quantum Vista, explores the cutting-edge intersection of advanced quantum sensing technologies and the diverse challenges within biomedical engineering. Students will investigate how the unprecedented sensitivity and novel capabilities of quantum sensors are paving the way for revolutionary advancements in medical diagnostics, non-invasive patient monitoring (such as brain activity), and molecular-level imaging. The course emphasizes a cross-disciplinary approach, linking fundamental quantum principles to physiological understanding and clinical needs.

This course is designed for advanced undergraduate or graduate students specializing in Biomedical Engineering, Medical Physics, Biophysics, or related engineering and applied science fields who have a keen interest in leveraging quantum technologies for healthcare solutions.

Successful completion of Level 2 and foundational Level 3 courses (specifically "Quantum Mechanics for Applied Sciences," "Quantum Sensing Fundamentals," and "Quantum Devices and Technologies in Sensing") or equivalent demonstrated knowledge is strongly recommended. Students should possess:

• A solid understanding of quantum sensing principles and various device modalities.
• Familiarity with basic concepts in human physiology and common medical imaging/diagnostic challenges.
• An aptitude for interdisciplinary thinking.

• Advanced Magnetoencephalography (MEG) & Magnetocardiography (MCG): In-depth look at Optically Pumped Magnetometers (OPMs) and SQUIDs for non-invasive mapping of brain and heart activity, including challenges in signal processing and source localization.
• Nanoscale Quantum Biosensing: Utilizing NV centers in diamond, quantum dots, or other quantum probes for high-sensitivity detection of single molecules, proteins, or cellular processes relevant to early disease diagnostics and drug discovery.
• Quantum-Enhanced Magnetic Resonance Imaging (MRI): Exploring concepts like hyperpolarization techniques enhanced by quantum effects and the potential for low-field MRI using highly sensitive quantum magnetometers.
• Case Studies in Medical Diagnostics: Analysis of specific diagnostic challenges (e.g., early cancer detection, neurodegenerative disease monitoring) and how quantum sensors could provide novel solutions.
• Molecular Imaging with Quantum Probes: Concepts for using quantum effects to improve resolution, sensitivity, or functional information in molecular imaging techniques.
• Challenges in Clinical Translation: Discussion of the practical hurdles in bringing quantum sensor technology from the lab to clinical use, including device robustness, cost, regulatory aspects, and integration with existing medical workflows.
• Ethical Considerations: Brief overview of ethical implications related to advanced biomedical sensing and data.

Upon successful completion of this course, students are expected to be able to:

• Critically analyze the application of specific quantum sensor types to various biomedical problems.
• Evaluate the advantages, limitations, and potential impact of quantum sensing technologies in healthcare compared to conventional methods.
• Understand the key design considerations and operational principles for quantum sensors in biologically relevant environments.
• Identify and discuss the challenges associated with the clinical translation and broader adoption of quantum biomedical devices.
• Propose conceptual quantum sensing solutions for specific unmet needs in medicine or biomedical research.
• Communicate effectively at the interface of quantum physics, engineering, and biomedical science.

This Quantum Vista course will rely heavily on the study of current research literature, review articles focusing on quantum applications in biomedicine, and detailed case studies of emerging technologies. Learning will be driven by critical analysis of published data, conceptual design exercises, and presentations. Access to scientific databases and journals will be essential. Depending on module specifics, some illustrative simulations of sensor-analyte interactions or signal processing might be introduced using standard scientific computing environments.