DC13: In-Game Assessment for Patient-adaptive Intelligent Rehabilitation Robotics

Project: In-Game Assessment for Patient-adaptive Intelligent Rehabilitation Robotics (WP4)

Host institution: TYRO (Austria)

Supervisor: I. Jakob

Co-supervisor(s): T. Seel (LUH – Germany), A. Turolla (Univ. of Bologna – Italy)

Objectives:

Improve independence of robot-assisted therapy for unsupervised home settings.

Expected Results:

Integrate data fusion and learning algorithms for adaptive real-time human-machine interaction, tailored to individual patient conditions and goals. Implement sensor-based in-game assessments to identify patient-specific performance parameters for informed progression of difficulty levels..

Planned secondment(s):

  1. LUH (3 months, M13-M15): development of data fusion and learning algorithm with T. Seel (KPI: joint conference paper)
  2. University of Bologna (3 months, M33-M35): Evaluation of clinical system requirements, with A. Turolla (KPI: joint journal paper)

Enrolment in Doctoral degree: Doctoral School of Leibniz University Hannover (Germany)

Required profile: Master’s degree in field Biomedical Engineering or Robotics or Computer Science or Neuroscience.

Desirable skills/interests: data fusion and learning algorithms – therapeutic/medical therapy – virtual reality (VR) – mechatronic systems, especially robotics and sensor technology.

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