Objectives
After completing the course, the student will have the necessary skills to analyse data recorded by a typical wearable device such as a smart watch or an electrocardiogram patch. The student will learn about the specific properties of biosignals and understand what kind of methods typically work in real-life scenarios. Students will learn how to pre-process biosignals, how to detect peaks for heart and heart rate variability estimation, how to estimate the quality of biosignals and how to detect rhythm disorder. In addition, the students will learn about outlier detection and how to improve detection performance through post processing. At the end of the course, you will be able to analyse biosignal data and build working algorithms for basic, yet important, analysis tasks.
After completing the course, the student will have the necessary skills to analyse data recorded by a typical wearable device such as a smart watch or an electrocardiogram patch. The student will learn about the specific properties of biosignals and understand what kind of methods typically work in real-life scenarios. Students will learn how to pre-process biosignals, how to detect peaks for heart and heart rate variability estimation, how to estimate the quality of biosignals and how to detect rhythm disorder. In addition, the students will learn about outlier detection and how to improve detection performance through post processing. At the end of the course, you will be able to analyse biosignal data and build working algorithms for basic, yet important, analysis tasks.
- Opettaja
Matti Kaisti