MSc graduation project: Machine Learning for Human Motion Recognition


BIASlab logo

BIASlab (Fig.1,, FLUX-7.060) is a subgroup of the Signal Processing Systems (SPS) that aims to develop Intelligent Autonomous Agents (IA). These agents interact with their environment through their sensors and actuators in order to learn purposeful behavior, e.g., to navigate, play soccer or they may learn to decode speech signals under bad acoustic conditions. Our research projects are inspired by the latest insights from machine learning, computational neuroscience and signal processing.

Project Description

Motion model

In this project, you are challenged to design a machine learning agent that learns to recognize specific motions through on-the-spot interaction with a (human) end user. Motion recognition is a broad field with applications such as gesture recognition (e.g., for recognizing sign language or remote device control), activity recognition (e.g., for fall detection) and motion analysis (e.g., for rehabilitation). You are challenged to develop autonomous learning agents that are informed by body-worn motion sensors, e.g., by accelerometers in smart ear buds or wristband devices. In this project, we will primarily focus on one-shot learning of motions: how can we learn specific and complicated motions by an individual user from only a few examples (ideally only one) by that user? This project will get you involved with the latest artificial intelligence methods, since the agent will need to (1) be smart about selecting the most informative motion examples, and (2) learn as much as possible (but not more) from each motion example. These are typical qualities of human learning and this project will also give you an opportunity to learn about how biological brains solve real-time design issues. This project builds upon our previous work on gesture recognition.


Start date: the project is available from September 2017 (or any time thereafter).

Duration: 9 months (fte).

Financial Support

The audio solutions company GN ( may financially support strong candidates (qualifications to be discussed with prof. de Vries) by a GN scholarship.


For more information about this project, please contact Prof. Bert de Vries ( Also, feel free to make an appointment to discuss alternative projects with intelligent autonomous agents that you might be interested in.