On successful completion of the course, the student should be able to:
understand the basis in the theory of biomedical measurement systems, including sensors, signal conditioning methods, measurement techniques, patient interfacing and instrumentation used in assistive and healthcare technology
understand the basis in the theory of biomechanical measurement systems, including motion, force sensors and visual motion capture system
understand the basis in the theory of machine vision for human behavior analysis, fall and irregularity detection
understand the basis in the machine vision an image processing related to assistive and health technology
demonstrate how signals from biomechanical sensors can be fused for physical activity assessment and feature extraction
demonstrate how wearable sensors and systems can be used in home monitoring, telemedicine and smart home control
write a scientific report
Course contents
This course will provide the students with necessary knowledge about biomedical sensors, biomechanical sensors and measurement methods to design assistive and health technology.
Biomechanical sensors and measurement methods
Biomechanical measurement in diagnostic, rehabilitation and training
Biomedical sensors and measurement methods
Human machine interface and event detection
Signal acquisition processing, fusion and feature extraction methods