In the Vibrating Socks project we will develop a patient-centered, clinically and scientifically evaluated prototype of a small device worn around the ankle that contains a sensor and a vibration actuator that will analyse gait patterns retrieved from the sensor data using machine learning algorithms and provides a vibrotactile cue when gait disturbances or a freezing episode is detected. In addition, an app is being developed that connects to the device and stores and summarizes relevant data in an easy-to-understand format for people with Parkinson’s disease and health providers.

Gait impairments and freezing of gait are one of the most disabling symptoms in patients with Parkinson’s disease and may be provoked by turning, passing through narrow passages, but also by emotional distress, cognitive dual tasks, and experiencing time pressure. By increasing our understanding of these impairments we will develop and optimize the prototype such that each individual patient can benefit the most from it in improving gait and preventing freezing and falls.

We look for a dedicated researcher with a passion for studying human cognition and motor control by analysing physiological and behavioural signals recorded from smart sensors worn by Parkinson patients, and a keen interest in the development of smart tools to aid these patients in daily living situations. One of the objectives of the project is to determine which cueing strategies have the best effect in preventing or overcoming freezing gait impairments and freezing under specific environmental conditions and/or increased mental load or dual tasking.

• You are an enthusiastic researcher and highly motivated.
• You have a MSc degree in Biomedical Engineering, Technical Medicine, Electrical Engineering, Applied Physics, Biomedical Sciences or a related topic, with excellent experimental and theoretical skills including programming skills for the development of signal analysis algorithms and handling large data sets.
• You have a creative mindset and excellent analytical and communication skills.
• You have good team spirit and like to work in an interdisciplinary environment.
• You are fluent in English.

• As a PhD student at the UT, you will be appointed on a fulltime position for four years, with a qualifier in the first year, within a very stimulating scientific environment. You will also work part-time in the Neurophysiology lab at the Radboud University in Nijmegen.
• Salary and conditions are in accordance with the collective labor agreement for Dutch universities (CAO- NU).
• You will receive a salary ranging from €2.325,- gross per month at the start to €2.972,- in the fourth year.
• A minimum of 232 leave hours in case of full-time employment based on a formal workweek of 38 hours. A full-time employment in practice means 40 hours a week, therefore resulting in 96 extra leave hours on an annual basis.
• Excellent benefits including a holiday allowance of 8% of the gross annual salary, a year-end bonus of 8.3% and a solid pension scheme.
• A training program in which you and your supervisors will make up a plan for additional suitable education and supervision.
• We encourage a high degree of responsibility and independence, while collaborating with colleagues and researchers from various disciplines, and partners from industry.

The group Biomedical Signals & Systems aims to enable improved diagnosis and treatment of patients with motor, sensory and cardiopulmonary dysfunction in clinical and home/self-care setting. Our research is embedded in the multidisciplinary research institute Technical Medicine (TechMed) Centre.

The team working on Central Motor Control, led by Ciska Heida and Richard van Wezel, combines computational modelling and experimental research to study the neuronal mechanisms of movement disorders and to develop new and optimize existing therapeutic neuromodulation strategies such as deep brain stimulation and cueing. You will be co-supervised by Marleen Tjepkema-de Boer of the Clinical Neurophysiology group and the Hospital MST. The project is part of a larger collaborative project between University of Münster, Hospital MST (Enschede), Radboud UMC, Radboud University, companies and patient organizations.