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Interaction control strategies on hand assessment robot for stroke patients
ETH MIKE is a robotic device for somatosensory, motor and sensorimotor assessment of hand function in stroke patients, developed at RELab. The aim of the project is to improve and characterize transparency of the robot. Multiple control strategies will be tested and assessed to design an optimum human-robot interaction control.
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 validity of such assessment (comparison to the clinical standards), we need a transparent environment, so that it is easy to move inside the robot (as in the air).
[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 validity of such assessment (comparison to the clinical standards), we need a transparent environment, so that it is easy to move inside the robot (as in the air).
[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 implement and evaluate multiple interaction control strategies (i.e. feedforward, force feedback) and appropriately characterize their performance (i.e. transparency planes). The project is inspired by the work of Metzger et. al. 2015 [3].
[3] J-C. Metzger, O. Lambercy et al., “Performance Comparison of Interaction Control Strategies on a Hand Rehabilitation Robot”, IEEE International Conference on Rehabilitation Robotics, vol. 2015-September, pp. 846–851, 2015.
The goal is to implement and evaluate multiple interaction control strategies (i.e. feedforward, force feedback) and appropriately characterize their performance (i.e. transparency planes). The project is inspired by the work of Metzger et. al. 2015 [3].
[3] J-C. Metzger, O. Lambercy et al., “Performance Comparison of Interaction Control Strategies on a Hand Rehabilitation Robot”, IEEE International Conference on Rehabilitation Robotics, vol. 2015-September, pp. 846–851, 2015.
• 20% Literature review on state-of-the-art hand sensorimotor assessments as well as existing interaction control strategies
• 30% Implementation of different interaction controllers in LabVIEW
(i.e. feedforward, force feedback)
• 30% Characterization of the controllers (i.e. transparency planes)
• 20% Report, Presentation – with the aim to publish on a scientific conference
• 20% Literature review on state-of-the-art hand sensorimotor assessments as well as existing interaction control strategies
• 30% Implementation of different interaction controllers in LabVIEW (i.e. feedforward, force feedback)
• 30% Characterization of the controllers (i.e. transparency planes)
• 20% Report, Presentation – with the aim to publish on a scientific conference
• Background in mechanical engineering/robotics/control systems
• Enthusiasm for clinical applications of robotics
• 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 National Instruments LabVIEW programming
• Experience in MATLAB programming
Monika Zbytniewska, MEng. Imperial College London
Rehabilitation Engineering Laboratory ETH Zurich
monika.zbytniewska@hest.ethz.ch