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Moeller T, Moehler F, Krell-Roesch J, Dežman M, Marquardt C, Asfour T, Stein T, Woll A. Use of Lower Limb Exoskeletons as an Assessment Tool for Human Motor Performance: A Systematic Review. SENSORS (BASEL, SWITZERLAND) 2023; 23:3032. [PMID: 36991743 PMCID: PMC10057915 DOI: 10.3390/s23063032] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/18/2023] [Revised: 03/06/2023] [Accepted: 03/07/2023] [Indexed: 06/19/2023]
Abstract
Exoskeletons are a promising tool to support individuals with a decreased level of motor performance. Due to their built-in sensors, exoskeletons offer the possibility of continuously recording and assessing user data, for example, related to motor performance. The aim of this article is to provide an overview of studies that rely on using exoskeletons to measure motor performance. Therefore, we conducted a systematic literature review, following the PRISMA Statement guidelines. A total of 49 studies using lower limb exoskeletons for the assessment of human motor performance were included. Of these, 19 studies were validity studies, and six were reliability studies. We found 33 different exoskeletons; seven can be considered stationary, and 26 were mobile exoskeletons. The majority of the studies measured parameters such as range of motion, muscle strength, gait parameters, spasticity, and proprioception. We conclude that exoskeletons can be used to measure a wide range of motor performance parameters through built-in sensors, and seem to be more objective and specific than manual test procedures. However, since these parameters are usually estimated from built-in sensor data, the quality and specificity of an exoskeleton to assess certain motor performance parameters must be examined before an exoskeleton can be used, for example, in a research or clinical setting.
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Affiliation(s)
- Tobias Moeller
- Institute of Sports and Sports Science, Karlsruhe Institute of Technology, 76131 Karlsruhe, Germany
| | - Felix Moehler
- Institute of Sports and Sports Science, Karlsruhe Institute of Technology, 76131 Karlsruhe, Germany
| | - Janina Krell-Roesch
- Institute of Sports and Sports Science, Karlsruhe Institute of Technology, 76131 Karlsruhe, Germany
| | - Miha Dežman
- Institute for Anthropomatics and Robotics, High Performance Humanoid Technologies (H2T), Karlsruhe Institute of Technology, 76131 Karlsruhe, Germany
| | - Charlotte Marquardt
- Institute for Anthropomatics and Robotics, High Performance Humanoid Technologies (H2T), Karlsruhe Institute of Technology, 76131 Karlsruhe, Germany
| | - Tamim Asfour
- Institute for Anthropomatics and Robotics, High Performance Humanoid Technologies (H2T), Karlsruhe Institute of Technology, 76131 Karlsruhe, Germany
| | - Thorsten Stein
- Institute of Sports and Sports Science, Karlsruhe Institute of Technology, 76131 Karlsruhe, Germany
| | - Alexander Woll
- Institute of Sports and Sports Science, Karlsruhe Institute of Technology, 76131 Karlsruhe, Germany
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Maggioni S, Melendez-Calderon A, van Asseldonk E, Klamroth-Marganska V, Lünenburger L, Riener R, van der Kooij H. Robot-aided assessment of lower extremity functions: a review. J Neuroeng Rehabil 2016; 13:72. [PMID: 27485106 PMCID: PMC4969661 DOI: 10.1186/s12984-016-0180-3] [Citation(s) in RCA: 54] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2016] [Accepted: 07/21/2016] [Indexed: 01/01/2023] Open
Abstract
The assessment of sensorimotor functions is extremely important to understand the health status of a patient and its change over time. Assessments are necessary to plan and adjust the therapy in order to maximize the chances of individual recovery. Nowadays, however, assessments are seldom used in clinical practice due to administrative constraints or to inadequate validity, reliability and responsiveness. In clinical trials, more sensitive and reliable measurement scales could unmask changes in physiological variables that would not be visible with existing clinical scores.In the last decades robotic devices have become available for neurorehabilitation training in clinical centers. Besides training, robotic devices can overcome some of the limitations in traditional clinical assessments by providing more objective, sensitive, reliable and time-efficient measurements. However, it is necessary to understand the clinical needs to be able to develop novel robot-aided assessment methods that can be integrated in clinical practice.This paper aims at providing researchers and developers in the field of robotic neurorehabilitation with a comprehensive review of assessment methods for the lower extremities. Among the ICF domains, we included those related to lower extremities sensorimotor functions and walking; for each chapter we present and discuss existing assessments used in routine clinical practice and contrast those to state-of-the-art instrumented and robot-aided technologies. Based on the shortcomings of current assessments, on the identified clinical needs and on the opportunities offered by robotic devices, we propose future directions for research in rehabilitation robotics. The review and recommendations provided in this paper aim to guide the design of the next generation of robot-aided functional assessments, their validation and their translation to clinical practice.
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Affiliation(s)
- Serena Maggioni
- Sensory-Motor Systems (SMS) Lab, Institute of Robotics and Intelligent Systems (IRIS), Department of Health Sciences and Technology (D-HEST), ETH Zürich, Zürich, Switzerland.
- Hocoma AG, Volketswil, Switzerland.
- Spinal Cord Injury Center, Balgrist University Hospital, University Zürich, Zürich, Switzerland.
| | - Alejandro Melendez-Calderon
- Hocoma AG, Volketswil, Switzerland
- Department of Physical Medicine and Rehabilitation, Northwestern University, Chicago, IL, USA
| | - Edwin van Asseldonk
- Laboratory of Biomechanical Engineering, MIRA Institute for Biomedical Technology and Technical Medicine, University of Twente, Enschede, The Netherlands
| | - Verena Klamroth-Marganska
- Sensory-Motor Systems (SMS) Lab, Institute of Robotics and Intelligent Systems (IRIS), Department of Health Sciences and Technology (D-HEST), ETH Zürich, Zürich, Switzerland
- Spinal Cord Injury Center, Balgrist University Hospital, University Zürich, Zürich, Switzerland
| | | | - Robert Riener
- Sensory-Motor Systems (SMS) Lab, Institute of Robotics and Intelligent Systems (IRIS), Department of Health Sciences and Technology (D-HEST), ETH Zürich, Zürich, Switzerland
- Spinal Cord Injury Center, Balgrist University Hospital, University Zürich, Zürich, Switzerland
| | - Herman van der Kooij
- Laboratory of Biomechanical Engineering, MIRA Institute for Biomedical Technology and Technical Medicine, University of Twente, Enschede, The Netherlands
- Department of Biomechanical Engineering, Delft University of Technology, Delft, The Netherlands
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van Dijk W, van der Kooij H, Koopman B, van Asseldonk EHF, van der Kooij H. Improving the transparency of a rehabilitation robot by exploiting the cyclic behaviour of walking. IEEE Int Conf Rehabil Robot 2014; 2013:6650393. [PMID: 24187212 DOI: 10.1109/icorr.2013.6650393] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
To promote active participation of neurological patients during robotic gait training, controllers, such as "assist as needed" or "cooperative control", are suggested. Apart from providing support, these controllers also require that the robot should be capable of resembling natural, unsupported, walking. This means that they should have a transparent mode, where the interaction forces between the human and the robot are minimal. Traditional feedback-control algorithms do not exploit the cyclic nature of walking to improve the transparency of the robot. The purpose of this study was to improve the transparent mode of robotic devices, by developing two controllers that use the rhythmic behavior of gait. Both controllers use adaptive frequency oscillators and kernel-based non-linear filters. Kernelbased non-linear filters can be used to estimate signals and their time derivatives, as a function of the gait phase. The first controller learns the motor angle, associated with a certain joint angle pattern, and acts as a feed-forward controller to improve the torque tracking (including the zero-torque mode). The second controller learns the state of the mechanical system and compensates for the dynamical effects (e.g. the acceleration of robot masses). Both controllers have been tested separately and in combination on a small subject population. Using the feedforward controller resulted in an improved torque tracking of at least 52 percent at the hip joint, and 61 percent at the knee joint. When both controllers were active simultaneously, the interaction power between the robot and the human leg was reduced by at least 40 percent at the thigh, and 43 percent at the shank. These results indicate that: if a robotic task is cyclic, the torque tracking and transparency can be improved by exploiting the predictions of adaptive frequency oscillator and kernel-based nonlinear filters.
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Wang L, van Asseldonk EHF, van der Kooij H. Model Predictive Control-based gait pattern generation for wearable exoskeletons. IEEE Int Conf Rehabil Robot 2012; 2011:5975442. [PMID: 22275642 DOI: 10.1109/icorr.2011.5975442] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
This paper introduces a new method for controlling wearable exoskeletons that do not need predefined joint trajectories. Instead, it only needs basic gait descriptors such as step length, swing duration, and walking speed. End point Model Predictive Control (MPC) is used to generate the online joint trajectories based on these gait parameters. Real-time ability and control performance of the method during the swing phase of gait cycle is studied in this paper. Experiments are performed by helping a human subject swing his leg with different patterns in the LOPES gait trainer. Results show that the method is able to assist subjects to make steps with different step length and step duration without predefined joint trajectories and is fast enough for real-time implementation. Future study of the method will focus on controlling the exoskeletons in the entire gait cycle.
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Affiliation(s)
- Letian Wang
- Laboratory of Biomechanical Engineering, University of Twente, 7500 EA Enschede, The Netherlands.
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Koopman B, van Asseldonk EHF, van der Kooij H, van Dijk W, Ronsse R. Rendering potential wearable robot designs with the LOPES gait trainer. IEEE Int Conf Rehabil Robot 2012; 2011:5975448. [PMID: 22457902 DOI: 10.1109/icorr.2011.5975448] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
In recent years, wearable robots (WRs) for rehabilitation, personal assistance, or human augmentation are gaining increasing interest. To make these devices more energy efficient, radical changes to the mechanical structure of the device are being considered. However, it remains very difficult to predict how people will respond to, and interact with, WRs that differ in terms of mechanical design. Users may adjust their gait pattern in response to the mechanical restrictions or properties of the device. The goal of this pilot study is to show the feasibility of rendering the mechanical properties of different potential WR designs using the robotic gait training device LOPES. This paper describes a new method that selectively cancels the dynamics of LOPES itself and adds the dynamics of the rendered WR using two parallel inverse models. Adaptive frequency oscillators were used to get estimates of the joint position, velocity, and acceleration. Using the inverse models, different WR designs can be evaluated, eliminating the need to build several prototypes. As a proof of principle, we simulated the effect of a very simple WR that consisted of a mass attached to the ankles. Preliminary results show that we are partially able to cancel the dynamics of LOPES. Additionally, the simulation of the mass showed an increase in muscle activity but not in the same level as during the control, where subjects actually carried the mass. In conclusion, the results in this paper suggest that LOPES can be used to render different WRs. In addition, it is very likely that the results can be further optimized when more effort is put in retrieving proper estimations for the velocity and acceleration, which are required for the inverse models.
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Affiliation(s)
- B Koopman
- Department of Biomechanical Engineering, MIRA, University of Twente, Enschede, The Netherlands.
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