Kies de Nederlandse taal
Course module: 202100142
Measuring Human Movement
Course infoSchedule
Course module202100142
Credits (ECTS)6
Course typeCourse
Language of instructionEnglish
Contact persondr. N. Strisciuglio
Externe Docent
K.K. Lemaire
dr. N. Strisciuglio
Contactperson for the course
dr. N. Strisciuglio
Academic year2021
Starting block
RemarksA maximum number of 30 students can participate in the course. Entry will be on a first-come, first-serve basis.
Application procedureYou apply via OSIRIS Student
Registration using OSIRISYes

The purpose of this is course is to familiarize students with data acquisition and data processing methods, such that they can independently conduct a practical experiment and subsequent data analysis to answer a concrete scientific question.

At the end of the course, students will have both theoretical knowledge of, and hands-on laboratory experience with data acquisition systems commonly used in the more technical approach of human movement sciences. Specifically, students will learn to use a force platform, a (marker-based) motion capture device, and to collect Electromyography. In addition, students will be familiarized with signal processing and data preparation methods that are commonly applied to these measurements. 


Data acquisition amounts to transforming a physical signal (e.g. force) into an analog electrical signal (e.g. through deformation of a conductive material), which is then digitally sampled to a computer. Usually, the raw sampled data will need to be digitally processed to be able to answer scientific questions. This course tracks the path of physical signals, from the sensor into the computer, and introduces common data processing techniques. Students will learn the theoretical/conceptual basis of data acquisition and processing methods, and will learn to apply these in hands-on laboratory experiments and corresponding data processing assignments. Measurement systems that are covered include: Force plates (measuring the reaction force from the ground onto a person); marker-based motion capture (tracking body parts through 3D space) and Electromyography (EMG, measuring the electrical signal that accompanies muscle activation). In addition, more advanced measurement techniques will be briefly introduced, such as video-based (marker-less) motion capture and inertial measurement unit-based motion capture. In the last part of the course, students will apply their knowledge to explore a measurement system of their own choice, and answer a simple science question of their interest.

The course will be divided into three parts, each motivated by a simple science question.

  1. Part 1 will deal with the hardware side of measuring physical quantities. We will discuss a.o. sensor properties; signal amplification; calibration; and analog-to-digital conversion, in the context of force plates and motion capture. We answer the question: “do you jump higher with a weight strapped to your waist, or held in your hands?”. A latent goal in this part will be to (re-)familiarize students with basic Newtonian mechanics, as that will be needed to reason about (and compute) jump height.
  2. In part 2 the focus will be on data processing techniques and signal properties, introducing a.o. signal frequency content, (digital) filters, signal-to-noise ratio and (non-)dimensionalization, in the context of EMG signals. We answer the question: “which muscle is activated first during a high jump, the hip or the calf muscle?”.
  3. In part 3 students will apply the knowledge they learned in parts 1 and 2 to answer a simple science question of their own interest. The focus in this mini-project will be on methodological aspects. A latent goal in this part will be to (re-)familiarize students with ethical aspects of performing measurements on human participants, i.e. the role and responsibility of the experimenter and their relation to the participant.

Teaching methods
Lectures, practical labs and programming (homework) assignments.

  • Lectures: Lectures will serve to introduce key concepts/theory and to prepare for practical laboratory assignments. 
  • Practical labs: Hands-on, in-person meetings which form the backbone of the course. Students will work in small groups collecting data on the selected set-ups, tying their conceptual knowledge to concrete examples. Attendance to the labs will be mandatory.
  • Computer labs (home work): Will introduce processing techniques using the data collected in the practical labs. For each part, students will write a short report which describes their answer to the simple science question, which should be supported by relevant data/figures.
  • Mini-project (part 3): Students will work in pairs to address a simple scientific question of their interest. The question should be answerable with a simple experiment, using a measurement technique of the students’ choice. The goal will be to understand the methodology, not to do groundbreaking science. The project will conclude with a short (6 min, including discussion) presentation to your peers.
Lab attendance and homework assignments (pass/fail, 1/10 of grade, necessary condition for completion of the course)
Written exam (6/10 of grade)
Mini project (presentation, 3/10 grade)

Numerus fixus
The number of students that can attend this course will be limited to 30. Entry into the course will be on a first-come, first-serve basis.

Workload & credits
The course load is 6 EC, which equals 168 study hours. These hours could be divided over the course program as follows:
Task Load (hours)
Preparation lectures 12x2=24
Lectures 12x2=24
Preparation lab practicals 2x5=10
Lab practicals 2x5=10
Homework assignments 5x7=35
Mini-project 58
Preparation exam 10
Exam 3
Mini-project presentations 4
Total 168

Lecturer VU
Koen Lemaire 
Participating study
Master Computer Science
Required materials
Recommended materials
Course material
The syllabus will be made available online prior to the start of the course
Instructional modes

Project unsupervised

Presence dutyYes

Project, Exam

Kies de Nederlandse taal