DC3: A EMI Risk management of Assistive Health Technology

Project: A EMI Risk management of Assistive Health Technology (WP1)

Host institution: KU Leuven (Belgium)

Supervisor: Dr D. Vanoost (KU Leuven, Belgium)

Co-supervisor(s): Assoc Prof. M. Kok (TUD), Dr. M. F. Russold(OBHP)

Objectives:

Create and deploy continuous monitoring systems for electromagnetic disturbances in assistive devices during operation, with the ability to detect and respond to unexpected high disturbances to ensure safety and reliability

Expected Results:

Innovative and cost-effective EMI sensors capable of continuous monitoring to ensure environmental disturbances remain within the specified limits for the assistive device. Documentation and validation of the AI’s ability to detect potential EMI failures in real-time.

Planned secondment(s):

  1. TUD (3 months, M17-M19): Deep Learning Techniques for Compressive Sensing-Based Reconstruction of EMD with M. Kok (KPI: joint conference paper)
  2. OBHP (3 months, M33-M35): Implementing on an edge device sensor the fusion technique for EMI detection in power prosthesis, with M. F. Russold (KPI: joint journal paper)

Enrolment in Doctoral degree: Doctoral School of KU Leuven (Belgium)

Required profile: Electrical Engineering

Desirable skills/interests: Electromagnetic Compatibility – Electromagnetism – Sensors – Measurement Techniques

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