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Graphical user interface of a robotic device for hand sensorimotor assessment after stroke
ETH MIKE is a robotic device for somatosensory, motor and sensorimotor assessment of hand function in stroke patients, developed at Rehabilitation Engineering Laboratory. The aim of the project is to improve the graphical user interface of the robot, so that it can be used regularly and independently by patients and doctors. The software is developed in Unity and the hardware in LabVIEW.
Stroke is one of the leading causes of disability worldwide. Stroke survivors often suffer from impaired motor and/or somatosensory hand functions, affecting their independence and quality of life. The severity of these impairments is typically quantified with clinical assessments, which are subjective and imprecise [1]. We are proposing a robotic solution (ETH MIKE) for rapid and quantitative assessment of hand sensorimotor function. Such technology-driven approach will help to better track patient’s progress during recovery and design patient-specific therapies.
Specifically, ETH MIKE is a robot for the assessment of the metacarpophalangeal (MCP) joint of the index finger. It can assess proprioceptive functions through a gauge position matching task [2]. It can also assess motor and sensorimotor function through tasks such as range of motion and trajectory following. When motor function is assessed, the subject is asked to actively generate movement while his/her finger is placed inside the robot (what allows for a detailed recording of e.g. force produced during motion). In order to ensure smooth transition between different assessments and general entertainment of the participants (currently the tasks are rather boring), we need to improve the graphical user interface.
[1] N. B. Lincoln, J. L. Crow et al., “The unreliability of sensory assessments”, Clinical Rehabilitation, vol. 5, pp. 273–282, 1991.
[2] M. D. Rinderknecht, W. L. Popp et al., “Reliable and Rapid Robotic Assessment of Wrist Proprioception Using a Gauge Position Matching Paradigm”, Frontiers in human neuroscience, vol. 10, p. 316, 2016.
Stroke is one of the leading causes of disability worldwide. Stroke survivors often suffer from impaired motor and/or somatosensory hand functions, affecting their independence and quality of life. The severity of these impairments is typically quantified with clinical assessments, which are subjective and imprecise [1]. We are proposing a robotic solution (ETH MIKE) for rapid and quantitative assessment of hand sensorimotor function. Such technology-driven approach will help to better track patient’s progress during recovery and design patient-specific therapies.
Specifically, ETH MIKE is a robot for the assessment of the metacarpophalangeal (MCP) joint of the index finger. It can assess proprioceptive functions through a gauge position matching task [2]. It can also assess motor and sensorimotor function through tasks such as range of motion and trajectory following. When motor function is assessed, the subject is asked to actively generate movement while his/her finger is placed inside the robot (what allows for a detailed recording of e.g. force produced during motion). In order to ensure smooth transition between different assessments and general entertainment of the participants (currently the tasks are rather boring), we need to improve the graphical user interface.
[1] N. B. Lincoln, J. L. Crow et al., “The unreliability of sensory assessments”, Clinical Rehabilitation, vol. 5, pp. 273–282, 1991. [2] M. D. Rinderknecht, W. L. Popp et al., “Reliable and Rapid Robotic Assessment of Wrist Proprioception Using a Gauge Position Matching Paradigm”, Frontiers in human neuroscience, vol. 10, p. 316, 2016.
The goal is to improve and optimize the graphical user interface (frontend), as well as the backend, to ensure smooth transition between different assessment tasks. Moreover, the visuals and the interactivity of the tasks protocol needs to be improved to ensure entertainment and engagement of the participants.
The goal is to improve and optimize the graphical user interface (frontend), as well as the backend, to ensure smooth transition between different assessment tasks. Moreover, the visuals and the interactivity of the tasks protocol needs to be improved to ensure entertainment and engagement of the participants.
• 10% Literature review on state-of-the-art hand sensorimotor assessments
• 60% Graphical user interface optimisation (Unity & LabVIEW)
• 20% Evaluation of the improved software with physiotherapists
• 10% Report, Presentation
• 10% Literature review on state-of-the-art hand sensorimotor assessments • 60% Graphical user interface optimisation (Unity & LabVIEW) • 20% Evaluation of the improved software with physiotherapists • 10% Report, Presentation
• Background in mechanical engineering/robotics/control systems
• Enthusiasm for clinical applications of robotics
• Experience in Unity (C#) programming
• Experience in National Instruments LabVIEW programming
• Experience in MATLAB programming
• Background in mechanical engineering/robotics/control systems • Enthusiasm for clinical applications of robotics • Experience in Unity (C#) programming • Experience in National Instruments LabVIEW programming • Experience in MATLAB programming
Monika Zbytniewska,
MEng. Imperial College London
Rehabilitation Engineering Laboratory ETH Zurich
monika.zbytniewska@hest.ethz.ch