Description
Analysing human movement patterns is highly relevant in several fields related to biomedical engineering, such as sports performance, neurophysiology and behavioural neuroscience. Therefore, the goal of this course is to discuss the most relevant methods to assess and describe human motion: movement kinetics, movement kinematics and surface electromyography. Data acquisition from optical and inertial motion capture systems, ground reaction forces and surface EMG will be explored. The topics covered include:

 -          Relevance of motion analysis in biomedical sciences

-          Extracting relevant features from human kinetics/kinematics – measurement tools and their advantages

-          The relevance of surface electromyography (EMG) to explain human movement in static and dynamic conditions

The course is based on short theoretical lectures, hands-on experiences in laboratory and subsequent data processing. Students will have the opportunity to acquire relevant data and reflect on the advantages and disadvantages of the proposed methods. In addition, students will undergo the processing steps required to properly interpret and present movement analysis data. Trending methods to represent and analyse movement patterns such as statistical parametric mapping (SPM) will be explored using the acquired data. The course has been designed for PhD students considering including movement analysis on their PhD studies, where a range of different methods can be used. Therefore, this course can contribute to defining the best methods to apply on the PhD project.

Literature
Gordon Robertson, Joseph Hamill, Gary Kamen, Graham Caldwell: Research Methods in Biomechanics. Saunders Whittlesey (2004) ISBN-13: 9780736039666.

Further readings will be provided via the course webpage.

Prerequisites
This course is ideal for students with basic knowledge on human biomechanics. Previous experience in MATLAB programming is highly desirable.

Evaluation
Assignment: Students must submit a mini report (max. 4 pages) 2 weeks after the course. This report should be based on data collected during the course – or from a previous/current PhD study – including an introduction, methods, results, and discussion/conclusion. Detailed explanations of the choices for movement analysis methods and data analysis should be included in the report.

Organizer: Associate Professor Anderson Oliveira, e-mail: oliveira@mp.aau.dk

Lecturers: Associate Professor Anderson Oliveira

ECTS: 2.4

NB: New Dates: Time: 27 September, 11, 18, 24 October and 10 November 2022 (12.30-16.15)

Place: Aalborg University - Face to face lectures

Rooms:

27 September: Niels Jernes Vej 12A, Room 6-104

11 October: Niels Jernes Vej 12A, Room 12A/6-104

18 October: Niels Jernes Vej 12A, Room 12A/6-104

24 October: Niels Jernes Vej 12A, Room 12A/5-006

10 November: Niels Jernes Vej 12A, Room 12A/5-006

Number of seats: 30

Deadline: 6 September 2022

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 3.000 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 four 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.