Instrument-based measurements of movement problems for detection and prediction the risk of psychiatric disorders

Are you a master's student in Signal & Systems, Clinical Technology, Biomedical Engineering, or a related field?

We are looking for a talented individual to join our team and contribute to our research aimed at identifying potential biomarkers for improving the clinical categorization of psychiatric disorders.

We invite you to join our team and make a significant contribution to an exciting research project within the Erasmus MC (dr. N.H. Grootendorst, psychiatrist).

Motor disorders are commonly observed in psychiatric illnesses but are often overlooked in clinical practice. These disorders are a hallmark feature of severe psychiatric conditions.

Current clinical rating scales, while useful, are limited by their subjective nature. Instrumental, objective measurements of motor disorders have the potential to provide highly accurate and promising movement data, such as actigraphy, instrumental handwriting registration, or video-based observation. These methods offer a finer-grained, more reliable, and sensitive assessment of motor symptoms, which could contribute to a better understanding of phenotypic characteristics and enhance diagnostic support.

Assignment

In this project, you will examine the predictive value of motor disorders for the development of psychiatric illnesses in a high-risk adolescent cohort. This research aims to improve the prognostic precision of existing risk models, presenting new opportunities for early intervention and timely treatment.

Motor measures are assessed at different measurement waves, and their accuracy in predicting the presence or absence of psychiatric disorders will be evaluated. Motor tasks, include tremor assessment, Archimedean spiral drawing using a pressure-sensing stylus, and tapping tests, will be recorded on an electronic tablet. Also actigraphy-data and video-data is available. 

Benefits:

·       Gain hands-on experience in a cutting-edge research project.

·       Large, multi-modal datasets available.

·       Work within a supportive and collaborative research team from department of psychiatry.

·       Gain insight into interdisciplinary research and its real-world applications in healthcare.

Requirements

·       Background in signal processing, machine learning, or clinical technology or related fields

·       Strong communication and collaboration skills

Contact

Last modified: 2025-03-17