The course covers the fundamental types of sensors, the physical concepts underlying various sensing systems, data handling, the practical applications of measurement, as well as discussions of constraints and error sources.
After taking this course, the student will have familiarity:
the measurements units
different type of sensors (i.e., inertial, physiological, environmental, smart sensors, and biosensors)
different type of sensing methods (i.e., HW based, or radio signals-based)
errors, noise, accuracy and resolution in measurement process
basic overview of biomedical systems
the physical principles utilized in the different kinds of sensors
calibration of sensors and instruments
basic concepts of signal processing
sensors communication technologies (e.g., serial, Bluetooth, WiFi, Zigbee, etc)
timeseries analysis, and timeseries forecasting
introduction to the use of data/signals/timeseries in machine learning
sensors based application scenarios (e.g., Human Activity Recognition based on inertial sensors, flow measurements, blood pressure, measurements of the respiratory systems or hear rate).
As part of the laboratory activity, the students will program and use an Arduino in order to perform practical measurements.
Required prerequisite knowledge
ELE100 Electrical Engineering 1, ELE130 Applied Mathematics and Physics in Programming of Robots
There must be an early dialogue between the course coordinator, the student representative and the students. The purpose is feedback from the students for changes and adjustments in the course for the current semester.In addition, a digital course evaluation must be carried out at least every three years. Its purpose is to gather the students experiences with the course.