Welcome to MATLAB FOR NON-ENGINEERS: BASIC DATA PROCESSING AND OPTIMIZATION
Description:
Research on biomedical engineering topics usually require the acquisition of biological signals or additional instrumentation that provides continuous time series. For non-engineers, processing those types of data can be time consuming and inaccurate if proper processing methods are not used. Therefore, the goal of this course is to present basic processing tools to analyze biological and non-biological signals. The course is based on Matlab, one of the most powerful software packages for data recording and analysis in Engineering. The course presents a dynamic format, in which students will have practical experiences regarding the use of Matlab during the lectures. This format will offer the unique possibility to learn how to perform basic and complex operations with the assistant of the lecturer while generating the data analyses scripts. The course has been designed for PhD students without previous experience on programming on Matlab, such as Physiotherapists, Medical Doctors, Pharmacists, Psychologists, Sports Science professionals. However, this course could also suit students with Matlab skills looking for new ways to analyze their current datasets.
The course will be divided in four modules
- Introduction: basic operations and file management (importing, loading, saving files)
- Data visualization, matrix manipulation
- Code optimization: reducing processing time and minimizing changes of errors
- Multi-subject dataset management and basic statistics
Literature
To be announced. Readings will be provided via the course webpage.
Prerequisites
This course is ideal at students early or midway in their PhD. You should be at least 3 months into your project development. Ideally, students should use their own target data to develop scripts for analysis.
Evaluation
Assignment: Students must submit a mini report (5 pages) 2 weeks after the course including a sample script used for data analysis and a summary of the results extracted from the dataset. Detailed explanations of the processing steps and the choices for data analysis, based on appropriate references, should be included in the report.
Organizer: Associate Professor Anderson Oliveira, e-mail: oliveira@mp.aau.dk
Lecturers: Associate Professor Anderson Oliveira
ECTS: 3
Time: 5 April (8.15-12.00), 13 April (12.30-16.15), 26 April (8.15-12.00), 7 May (8.15-12.00), 24 May 2018 (8.15-16.00)
Place: Aalborg University, Fredrik Bajers Vej 7E, room E3-109
City: Aalborg
Number of seats:
Deadline: 15 March 2018
Important information concerning PhD courses We have over some time experienced problems with no-show for both project and general courses. It has now reached a point where we are forced to take action. Therefore, the Doctoral School has decided to introduce a no-show fee of DKK 5,000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before start of the course. Registered illness is of course an acceptable reason for not showing up on those days. Furthermore, all courses open for registration approximately three months before start. This can hopefully also provide new students a chance to register for courses during the year. We look forward to your registrations.
- Teacher: Anderson de Souza Castelo Oliveira