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(New course) ECE1390 Integrated Circuits for Sensors and Biomedical Devices (Fall 2022)

We are living in a transformative era where novel sensors and biomedical devices are revolutionizing our lives from every perspective: emerging implantable medical devices can now treat and regulate diseases that cannot be cured by medications; intelligent sensors are being integrated into modern vehicles to enable autonomous driving and improve our safety. It is estimated that over one trillion sensors are being used today around the world, connecting us through a massive internet of things (IoT). Integrated circuits (ICs) play an essential role in interfacing with these devices to realize their functionalities and fulfill their potential.

This course will introduce the design methodology for key IC blocks for sensors and biomedical devices. We will discuss topics including energy-efficient subthreshold circuits model and design, low-noise instrumentational circuits, dynamic noise and offset cancellation techniques, low-power data converters, low-power machine learning and system integration. We will cover IC design examples, such as biopotential amplifiers, CMOS image sensors, brain-machine interfaces (BMIs), photodetectors and LiDAR interface, DNA and protein detectors, MEMS sensor and actuator interfaces.


(New course) ECE441 Interfacing and Modulating the Nervous System (Fall 2023)

This course will introduce undergraduate engineering students to the fundamental principles of neuromodulation and its clinical implementation. The lectures have been structured to provide students with a basic understanding of the technological as well as the therapeutic aspect of neuromodulation and includes key aspects of neurotechnology including ‘introduction to electrical-neural interfaces’, ‘fundementals of signal processing’ and ‘instrumentation for neuromodulation devices’. The lab component will include hands-on measurement of body surface potentials as well as observational visits to pre-clinical labs that use neuromodulation in the treatment of neurological disorders. The course also includes guest lectures by subject-matter experts in the field.

Upon completing this course, students will be able to:

  • Use signal processing techniques to model and analyze human nervous system, neural circuits and oscillation
  • Use control theories to develop algorithms for modulating nervous systems
  • Use instrumentation to acquire neural signals and perform electrical neural stimulation
  • Understand the requirements and applications of electronics in neuromodulation devices
  • Gain practical, hands-on knowledge with acquiring neural signals and using software to analyze and stimulate neural behaviors
  • Learn about the recent advancements and state-of-the-art research trends in this area

  • ECE331 Analog Electronics (Fall 2021)

    This course covers transistor amplifiers including differential and multistage amplifiers, integrated circuit biasing techniques, output stage design and IC amplifier building blocks. Frequency response of amplifiers at low, medium and high frequencies. Feedback amplifier analysis. Stability and compensation techniques for amplifiers using negative feedback.

    Upon completing this course, students will be able to:

  • Identify key analog blocks, including differential and multistage amplifiers, biasing circuits, current mirrors, and output stage
  • Derive the transfer functions and port impedance of analog circuit blocks
  • Analyze the frequency responses of amplifiers at low, medium and high frequencies
  • Analyze different types of feedback circuits
  • Analyze the frequency responses and stability of analog circuit blocks
  • Optimize circuit parameters to achieve the desired operational condition and performance
  • Use engineering tools to evaluate circuit function and performance

  • ECE110 Electrical Fundamentals (Winter 2022)

    An overview of the physics of electricity and magnetism: Coulomb’s law, Gauss’ law, Ampere’s law, Faraday’s law, Lenz’s law, and Ohm’s law. Physics of capacitors, resistors, and inductors. An introduction to circuit analysis: resistive circuits, nodal and mesh analysis, linearity and superposition, Thévenin’s and Norton’s theorems, maximum power transfer, first-order RC and RL transient response, and sinusoidal steady-state analysis.

    In this course, students will:

  • Learn the laws govern the behaviors of electric charges, and interactions between charges. Understand the concepts of electric fields, electric potentials, and electric potential energies.
  • Learn about electrical energy storing elements, such as capacitors, and then use them in various electrical circuits.
  • Learn about magnetism, magnetic forces on moving electric charges and on current carrying wires. Learn about the concept of magnetic fields, magnetic energy, and magnetic energy storing devices such as inductors. Understand how inductors behave in electrical circuits.
  • Learn about basic circuit elements such as power supply, resistor, capacitor and inductor. Learn how to analyze resistive circuits under DC excitation. Learn about various circuit analysis techniques: Kirchhoff’s law, current/voltage division rules, nodal/mesh analysis, and superposition principles.
  • Learn the roles of a capacitor and an inductor in RC and RL transient circuits respectively, and the step-by-step technique in analyzing first-order transient circuits.
  • Learn about the concepts of phasors and impedances and use them to analyze sinusoidal steady-state (AC) circuits.
  • Learn about Thevenin’s and Norton’s theorems and their significance in circuit analysis. Apply Thevenin/Norton theorems and maximum power transfer theorem to resistive networks (DC) and sinusoidal steady-state (AC) circuits.



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