Lecture

Biomedical Microsystems: Fundamentals and Applications

Graph Chat

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.

In course

EE-519: Bioelectronics and biomedical microelectronics

The course covers the fundaments of bioelectronics and integrated microelectronics for biomedical and implantable systems. Issues and trade-offs at the circuit and systems levels of invasive microelectronic systems as well as their eluding designs, methods ...

Description

This lecture covers the organization of the course, including class lectures, exercises, student seminars, and course evaluation. It delves into the grading policy, course topics such as bioelectricity, electrodes, signal processing, and implantable systems. The course goals encompass fundamental expertise, microelectronic-related expertise, technology-related expertise, and soft skills. It also discusses the material sources, additional information sources, and references related to implantable biomedical microsystems. Furthermore, it explores the use of CMOS ICs in biomedical instrumentation, societal shifts in biomedical engineering, common medical measurands, and the usage of biomedical systems. The lecture concludes with neural engineering definitions, bioimplantable microsystems, and specific examples like pacemakers.

Instructor

Alexandre Schmid

Alexandre Schmid received the M.Sc. degree in microengineering and the Ph.D. degree in electrical engineering from the Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland, in 1994 and 2000, respectively. Since 1994, he has been with the EPFL, working with the Integrated Systems Laboratory as a Research and Teaching Assistant, and with the Electronics Laboratories as a Postdoctoral Fellow. In 2002, he was a Senior Research Associate with the Microelectronic Systems Laboratory, where he has been conducting research in the fields of bioelectronic interfaces and implantable biomedical electronics, nonconventional signal processing and neuromorphic hardware, and reliability of nanoelectronic devices, and also teaches with the Microengineering and Electrical Engineering Departments of EPFL. Since 2011, he is a Maître d'Enseignement et de Recherche (MER) Faculty Member with EPFL. He is a coauthor of two books, Reliability of Nanoscale Circuits and Systems, Methodologies and Circuit Architectures, Springer, 2011, and Wireless Cortical Implantable Systems, Springer, 2013, and a coeditor of one book, as well as over 100 articles published in journals and conferences. Dr. Schmid has served as the General Chair of the Fourth International Conference on Nano-Networks in 2009 and has been serving as an Associate Editor of the Institute of Electrical, Information, and Communication Engineers Electronics Express since 2009.

Official source

Related concepts (32)

Digital signal processing

Digital signal processing (DSP) is the use of digital processing, such as by computers or more specialized digital signal processors, to perform a wide variety of signal processing operations. The digital signals processed in this manner are a sequence of numbers that represent samples of a continuous variable in a domain such as time, space, or frequency. In digital electronics, a digital signal is represented as a pulse train, which is typically generated by the switching of a transistor.

Medical device

A medical device is any device intended to be used for medical purposes. Significant potential for hazards are inherent when using a device for medical purposes and thus medical devices must be proved safe and effective with reasonable assurance before regulating governments allow marketing of the device in their country. As a general rule, as the associated risk of the device increases the amount of testing required to establish safety and efficacy also increases.

Analog signal processing

Analog signal processing is a type of signal processing conducted on continuous analog signals by some analog means (as opposed to the discrete digital signal processing where the signal processing is carried out by a digital process). "Analog" indicates something that is mathematically represented as a set of continuous values. This differs from "digital" which uses a series of discrete quantities to represent signal. Analog values are typically represented as a voltage, electric current, or electric charge around components in the electronic devices.

Filter (signal processing)

In signal processing, a filter is a device or process that removes some unwanted components or features from a signal. Filtering is a class of signal processing, the defining feature of filters being the complete or partial suppression of some aspect of the signal. Most often, this means removing some frequencies or frequency bands. However, filters do not exclusively act in the frequency domain; especially in the field of many other targets for filtering exist.

Digital signal processor

A digital signal processor (DSP) is a specialized microprocessor chip, with its architecture optimized for the operational needs of digital signal processing. DSPs are fabricated on MOS integrated circuit chips. They are widely used in audio signal processing, telecommunications, , radar, sonar and speech recognition systems, and in common consumer electronic devices such as mobile phones, disk drives and high-definition television (HDTV) products. The goal of a DSP is usually to measure, filter or compress continuous real-world analog signals.

Related lectures (64)

Bioelectronics and Biomedical Microsystems

Covers bioelectricity, electrodes, microelectronics, signal processing, and implantable systems.

Neural Signals and Signal Processing

Explores nuclear magnetic resonance, MRI principles, pulse sequences, image reconstruction, safety considerations, and volume normalization in brain imaging.

Neural Signals and Signal Processing

Explores neural signals, EMG control, muscle synergies, and HD-EMG for prosthetic devices.

Neural Signals and Signal Processing

Covers neural signals, brain enthusiasm, neuroimaging, and statistical analysis in neuroimaging studies.

Optimization of Neuroprosthetic Systems

Explores the optimization of neuroprosthetic systems, including sensory feedback restoration and neural stimulation strategies.

Related concepts (32)

Digital signal processing

Medical device

Analog signal processing

Filter (signal processing)

Digital signal processor