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 analyse 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.

 

The course will be divided into four modules

  1. Introduction: basic operations and file management (importing, loading, saving files)
  2. Data visualization, matrix manipulation
  3. Code optimization: reducing processing time and minimizing changes of errors
  4. Multi-subject dataset management and basic statistics

 

Literature

To be announced. Readings will be provided via the course webpage.

 

Prerequisites

This course is ideal for 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 present a data analysis pipeline generated using Matlab on the last lecture day. The data should preferably be related to the topic of the PhD project, therefore benefiting the student in the standardization of data processing methods. Detailed explanations of the processing steps and the choices for data analysis, based on appropriate references, should be addressed in the presentation.



Organizer: Associate Professor Anderson Oliveira, emailoliveira@mp.aau.dk

Lecturers: Associate Professor Anderson Oliveira, Aalborg University

ECTS: 3.5

Time: 25 March (cancelled), 01, 11, 16, 23 April and 07 and 23 (NB: New date!) May 2019 (25.03, 01.04, 11.4, 16.04, 23.04, 23.05: 12.30 – 16.15; 07.05: 8.15 – 16.15)

Place: Aalborg University, Fredrik Bajers Vej 7E, room E3-209

Zip code: 9220 

City: Aalborg Øst 

Number of seats:

Deadline: 4 March 2019 

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.