1
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Grimmer M, Zhao G. Hip Exoskeleton for Cycling Assistance. Bioengineering (Basel) 2024; 11:683. [PMID: 39061765 PMCID: PMC11273394 DOI: 10.3390/bioengineering11070683] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2024] [Revised: 06/26/2024] [Accepted: 06/28/2024] [Indexed: 07/28/2024] Open
Abstract
Cycling stands as one of the most widely embraced leisure activities and serves purposes such as exercise, rehabilitation, and commuting. This study aimed to assess the feasibility of assisting three unimpaired participants (age: 34.0 ± 7.9 years, height: 1.86 ± 0.02 m, weight: 75.7 ± 12.7 kg) using the GuroX hip exoskeleton, originally designed for walking assistance, during cycling against a resistance of 1 W/kg. The performance evaluation employed a sweep protocol that manipulated the timing of the exoskeleton's peak extension and flexion torque in addition to human-in-the-loop optimization to enhance these timings based on metabolic cost. Our findings indicate that with a peak assistance torque of approximately 10.3 Nm for extension and flexion, the GuroX substantially reduced the net metabolic cost of cycling by 31.4 ± 8.1% and 26.4 ± 14.1% compared to transparent and without exoskeleton conditions, respectively. This demonstrates the significant potential of a hip exoskeleton developed for walking assistance to profoundly benefit cycling. Additionally, customizing the assistance strategy proves beneficial in maximizing assistance. While we attribute the average motor power to be a major contributor to the reduced cycling effort, participant feedback suggests that user comfort and synchronization between the user and exoskeleton may have played integral roles. Further research should validate our initial findings by employing a larger participant pool in real-world conditions. Incorporating a more diverse set of parameters for the human-in-the-loop optimization could enhance individualized assistance strategies.
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Affiliation(s)
- Martin Grimmer
- Institute for Sport Scienceand Department of Electrical Engineering and Information Technology, Technical University of Darmstadt, 64289 Darmstadt, Germany;
| | - Guoping Zhao
- School of Mechanical Engineering, Southeast University, Nanjing 211102, China
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2
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Mosconi D, Moreno Y, Siqueira A. Exploring Human-Exoskeleton Interaction Dynamics: An In-Depth Analysis of Knee Flexion-Extension Performance across Varied Robot Assistance-Resistance Configurations. SENSORS (BASEL, SWITZERLAND) 2024; 24:2645. [PMID: 38676262 PMCID: PMC11053741 DOI: 10.3390/s24082645] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/05/2024] [Revised: 04/10/2024] [Accepted: 04/16/2024] [Indexed: 04/28/2024]
Abstract
Knee rehabilitation therapy after trauma or neuromotor diseases is fundamental to restore the joint functions as best as possible, exoskeleton robots being an important resource in this context, since they optimize therapy by applying tailored forces to assist or resist movements, contributing to improved patient outcomes and treatment efficiency. One of the points that must be taken into account when using robots in rehabilitation is their interaction with the patient, which must be safe for both and guarantee the effectiveness of the treatment. Therefore, the objective of this study was to assess the interaction between humans and an exoskeleton during the execution of knee flexion-extension movements under various configurations of robot assistance and resistance. The evaluation encompassed considerations of myoelectric activity, muscle recruitment, robot torque, and performed movement. To achieve this, an experimental protocol was implemented, involving an individual wearing the exoskeleton and executing knee flexion-extension motions while seated, with the robot configured in five distinct modes: passive (P), assistance on flexion (FA), assistance on extension (EA), assistance on flexion and extension (CA), and resistance on flexion and extension (CR). Results revealed distinctive patterns of movement and muscle recruitment for each mode, highlighting the complex interplay between human and robot; for example, the largest RMS tracking errors were for the EA mode (13.72 degrees) while the smallest for the CR mode (4.47 degrees), a non-obvious result; in addition, myoelectric activity was demonstrated to be greater for the completely assisted mode than without the robot (the maximum activation levels for the vastus medialis and vastus lateralis muscles were more than double those when the user had assistance from the robot). Tracking errors, muscle activations, and torque values varied across modes, emphasizing the need for careful consideration in configuring exoskeleton assistance and resistance to ensure effective and safe rehabilitation. Understanding these human-robot interactions is essential for developing precise rehabilitation programs, optimizing treatment effectiveness, and enhancing patient safety.
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Affiliation(s)
- Denis Mosconi
- Industry Department, Federal Institute of São Paulo, Catanduva 15808-305, Brazil
- Mechanical Engineering Department, University of São Paulo, São Carlos CEP 13566-590, Brazil; (Y.M.); (A.S.)
| | - Yecid Moreno
- Mechanical Engineering Department, University of São Paulo, São Carlos CEP 13566-590, Brazil; (Y.M.); (A.S.)
| | - Adriano Siqueira
- Mechanical Engineering Department, University of São Paulo, São Carlos CEP 13566-590, Brazil; (Y.M.); (A.S.)
- Center of Engineering Applied to Healthy, São Carlos School of Engineering, University of São Paulo, São Carlos CEP 13566-590, Brazil
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3
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Trivedi U, Joshi AY. Advances in active knee brace technology: A review of gait analysis, actuation, and control applications. Heliyon 2024; 10:e26060. [PMID: 38384524 PMCID: PMC10878936 DOI: 10.1016/j.heliyon.2024.e26060] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Revised: 02/07/2024] [Accepted: 02/07/2024] [Indexed: 02/23/2024] Open
Abstract
This article discusses the significance of knee joint mechanics and the consequences of knee dysfunctions on an individual's quality of life. The utilization of active knee braces, which incorporate concepts of mechatronics systems, is investigated here as a potential treatment option. The complexity of the construction of the knee joint, which has six degrees of motion and is more prone to injury since it bears weight, is emphasized in this article. By wearing braces and using other support devices, one's knee can increase stability and mobility. In addition, the paper discusses various technologies that can be used to measure the knee adduction moment and supply spatial information on gait. Actuators for active knee braces must be compact, lightweight, and capable of producing a significant amount of torque; as a result, electric, hydraulic, and pneumatic actuators are the most common types. Creating control mechanisms, such as position control techniques and force/torque control approaches, is essential to knee exoskeleton research and development. These methods might make knee joint rehabilitation and assistive technology safer and more effective.
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Affiliation(s)
- Udayan Trivedi
- Mechatronics Engineering Department, Parul University, Vadodara, Gujarat, India
| | - Anand Y. Joshi
- Mechatronics Engineering Department, Parul University, Vadodara, Gujarat, India
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4
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Medrano RL, Thomas GC, Keais CG, Rouse EJ, Gregg RD. Real-Time Gait Phase and Task Estimation for Controlling a Powered Ankle Exoskeleton on Extremely Uneven Terrain. IEEE T ROBOT 2023; 39:2170-2182. [PMID: 37304231 PMCID: PMC10249462 DOI: 10.1109/tro.2023.3235584] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2023]
Abstract
Positive biomechanical outcomes have been reported with lower-limb exoskeletons in laboratory settings, but these devices have difficulty delivering appropriate assistance in synchrony with human gait as the task or rate of phase progression change in real-world environments. This paper presents a controller for an ankle exoskeleton that uses a data-driven kinematic model to continuously estimate the phase, phase rate, stride length, and ground incline states during locomotion, which enables the real-time adaptation of torque assistance to match human torques observed in a multi-activity database of 10 able-bodied subjects. We demonstrate in live experiments with a new cohort of 10 able-bodied participants that the controller yields phase estimates comparable to the state of the art, while also estimating task variables with similar accuracy to recent machine learning approaches. The implemented controller successfully adapts its assistance in response to changing phase and task variables, both during controlled treadmill trials (N=10, phase RMSE: 4.8 ± 2.4%) and a real-world stress test with extremely uneven terrain (N=1, phase RMSE: 4.8 ± 2.7%).
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Affiliation(s)
| | | | - Connor G Keais
- Department of Robotics, University of Michigan, Ann Arbor, MI 48109
| | - Elliott J Rouse
- Department of Mechanical Engineering; Department of Robotics, University of Michigan, Ann Arbor, MI 48109
| | - Robert D Gregg
- Department of Robotics, University of Michigan, Ann Arbor, MI 48109
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5
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de Miguel-Fernández J, Lobo-Prat J, Prinsen E, Font-Llagunes JM, Marchal-Crespo L. Control strategies used in lower limb exoskeletons for gait rehabilitation after brain injury: a systematic review and analysis of clinical effectiveness. J Neuroeng Rehabil 2023; 20:23. [PMID: 36805777 PMCID: PMC9938998 DOI: 10.1186/s12984-023-01144-5] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2021] [Accepted: 01/07/2023] [Indexed: 02/21/2023] Open
Abstract
BACKGROUND In the past decade, there has been substantial progress in the development of robotic controllers that specify how lower-limb exoskeletons should interact with brain-injured patients. However, it is still an open question which exoskeleton control strategies can more effectively stimulate motor function recovery. In this review, we aim to complement previous literature surveys on the topic of exoskeleton control for gait rehabilitation by: (1) providing an updated structured framework of current control strategies, (2) analyzing the methodology of clinical validations used in the robotic interventions, and (3) reporting the potential relation between control strategies and clinical outcomes. METHODS Four databases were searched using database-specific search terms from January 2000 to September 2020. We identified 1648 articles, of which 159 were included and evaluated in full-text. We included studies that clinically evaluated the effectiveness of the exoskeleton on impaired participants, and which clearly explained or referenced the implemented control strategy. RESULTS (1) We found that assistive control (100% of exoskeletons) that followed rule-based algorithms (72%) based on ground reaction force thresholds (63%) in conjunction with trajectory-tracking control (97%) were the most implemented control strategies. Only 14% of the exoskeletons implemented adaptive control strategies. (2) Regarding the clinical validations used in the robotic interventions, we found high variability on the experimental protocols and outcome metrics selected. (3) With high grade of evidence and a moderate number of participants (N = 19), assistive control strategies that implemented a combination of trajectory-tracking and compliant control showed the highest clinical effectiveness for acute stroke. However, they also required the longest training time. With high grade of evidence and low number of participants (N = 8), assistive control strategies that followed a threshold-based algorithm with EMG as gait detection metric and control signal provided the highest improvements with the lowest training intensities for subacute stroke. Finally, with high grade of evidence and a moderate number of participants (N = 19), assistive control strategies that implemented adaptive oscillator algorithms together with trajectory-tracking control resulted in the highest improvements with reduced training intensities for individuals with chronic stroke. CONCLUSIONS Despite the efforts to develop novel and more effective controllers for exoskeleton-based gait neurorehabilitation, the current level of evidence on the effectiveness of the different control strategies on clinical outcomes is still low. There is a clear lack of standardization in the experimental protocols leading to high levels of heterogeneity. Standardized comparisons among control strategies analyzing the relation between control parameters and biomechanical metrics will fill this gap to better guide future technical developments. It is still an open question whether controllers that provide an on-line adaptation of the control parameters based on key biomechanical descriptors associated to the patients' specific pathology outperform current control strategies.
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Affiliation(s)
- Jesús de Miguel-Fernández
- Biomechanical Engineering Lab, Department of Mechanical Engineering and Research Centre for Biomedical Engineering, Universitat Politècnica de Catalunya, Diagonal 647, 08028 Barcelona, Spain
- Institut de Recerca Sant Joan de Déu, Santa Rosa 39-57, 08950 Esplugues de Llobregat, Spain
| | | | - Erik Prinsen
- Roessingh Research and Development, Roessinghsbleekweg 33b, 7522AH Enschede, Netherlands
| | - Josep M. Font-Llagunes
- Biomechanical Engineering Lab, Department of Mechanical Engineering and Research Centre for Biomedical Engineering, Universitat Politècnica de Catalunya, Diagonal 647, 08028 Barcelona, Spain
- Institut de Recerca Sant Joan de Déu, Santa Rosa 39-57, 08950 Esplugues de Llobregat, Spain
| | - Laura Marchal-Crespo
- Cognitive Robotics Department, Delft University of Technology, Mekelweg 2, 2628 Delft, Netherlands
- Motor Learning and Neurorehabilitation Lab, ARTORG Center for Biomedical Engineering Research, University of Bern, Freiburgstrasse 3, 3010 Bern, Switzerland
- Department of Rehabilitation Medicine, Erasmus MC University Medical Center, Doctor Molewaterplein 40, 3015 GD Rotterdam, The Netherlands
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6
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Yu S, Huang TH, Di Lallo A, Zhang S, Wang T, Fu Q, Su H. Bio-inspired design of a self-aligning, lightweight, and highly-compliant cable-driven knee exoskeleton. Front Hum Neurosci 2022; 16:1018160. [PMID: 36419645 PMCID: PMC9677347 DOI: 10.3389/fnhum.2022.1018160] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2022] [Accepted: 10/19/2022] [Indexed: 04/07/2024] Open
Abstract
Powered knee exoskeletons have shown potential for mobility restoration and power augmentation. However, the benefits of exoskeletons are partially offset by some design challenges that still limit their positive effects on people. Among them, joint misalignment is a critical aspect mostly because the human knee joint movement is not a fixed-axis rotation. In addition, remarkable mass and stiffness are also limitations. Aiming to minimize joint misalignment, this paper proposes a bio-inspired knee exoskeleton with a joint design that mimics the human knee joint. Moreover, to accomplish a lightweight and high compliance design, a high stiffness cable-tension amplification mechanism is leveraged. Simulation results indicate our design can reduce 49.3 and 71.9% maximum total misalignment for walking and deep squatting activities, respectively. Experiments indicate that the exoskeleton has high compliance (0.4 and 0.1 Nm backdrive torque under unpowered and zero-torque modes, respectively), high control bandwidth (44 Hz), and high control accuracy (1.1 Nm root mean square tracking error, corresponding to 7.3% of the peak torque). This work demonstrates performance improvement compared with state-of-the-art exoskeletons.
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Affiliation(s)
- Shuangyue Yu
- Lab of Biomechatronics and Intelligent Robotics, Department of Mechanical and Aerospace Engineering, North Carolina State University, Raleigh, NC, United States
| | - Tzu-Hao Huang
- Lab of Biomechatronics and Intelligent Robotics, Department of Mechanical and Aerospace Engineering, North Carolina State University, Raleigh, NC, United States
| | - Antonio Di Lallo
- Lab of Biomechatronics and Intelligent Robotics, Department of Mechanical and Aerospace Engineering, North Carolina State University, Raleigh, NC, United States
| | - Sainan Zhang
- Lab of Biomechatronics and Intelligent Robotics, Department of Mechanical and Aerospace Engineering, North Carolina State University, Raleigh, NC, United States
- Department of Mechanical Engineering, City College of New York, New York, NY, United States
| | - Tian Wang
- Lab of Biomechatronics and Intelligent Robotics, Department of Mechanical and Aerospace Engineering, North Carolina State University, Raleigh, NC, United States
| | - Qiushi Fu
- Mechanical and Aerospace Engineering, University of Central Florida, Orlando, FL, United States
- NeuroMechanical Systems Laboratory, Biionix (Bionic Materials, Implants & Interfaces) Cluster, University of Central Florida, Orlando, FL, United States
| | - Hao Su
- Lab of Biomechatronics and Intelligent Robotics, Department of Mechanical and Aerospace Engineering, North Carolina State University, Raleigh, NC, United States
- Joint North Carolina State University/The University of North Carolina Department of Biomedical Engineering, NC State University, Raleigh, NC, United States
- Joint North Carolina State University/The University of North Carolina Department of Biomedical Engineering, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
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7
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Zhang T, Ning C, Li Y, Wang M. Design and Validation of a Lightweight Hip Exoskeleton Driven by Series Elastic Actuator With Two-Motor Variable Speed Transmission. IEEE Trans Neural Syst Rehabil Eng 2022; 30:2456-2466. [PMID: 36001514 DOI: 10.1109/tnsre.2022.3201383] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
To overcome the different requirements of torque-velocity characteristics for walking, running, stand-to-sit, sit-to-stand, and climbing stairs, we propose a novel concept for actuator design, namely, a series elastic actuator with two-motor variable speed transmission. The two-motor variable speed transmission can be adjusted in real-time to realize variable torque-velocity characteristics. A novel lightweight wearable hip exoskeleton driven by a series elastic actuator with two-motor variable speed transmission, named SoochowExo, has been developed in this paper for use in the elderly population. The weight of the whole hip exoskeleton is 2.85 kg (excluding batteries), including two actuators and the frame. The proposed hip exoskeleton can match the weight of the state-of-the-art hip exoskeleton while offering suitable torque and velocity for sitting-to-standing, walking, running on level ground, and climbing stairs. The benchtop tests and the preliminary human subject tests further confirm the design.
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8
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Sarkisian SV, Gunnell AJ, Bo Foreman K, Lenzi T. Knee Exoskeleton Reduces Muscle Effort and Improves Balance During Sit-to-Stand Transitions After Stroke: A Case Study. IEEE Int Conf Rehabil Robot 2022; 2022:1-6. [PMID: 36176078 DOI: 10.1109/icorr55369.2022.9896571] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
After a stroke, the weight-bearing asymmetry often forces stroke survivors to compensate with overuse of the unaffected side muscles to stand up. Powered exoskeletons can address this problem by assisting the affected limb during sit-tostand transitions. However, there is currently no experimental evidence demonstrating the efficacy of this intervention with the target population. This study explores controlling a powered knee exoskeleton with EMG signals to assist a stroke patient during sit-to-stand transitions. Our results show decreased peak knee torques by 6.24% and 11.9% on their unaffected and affected sides, respectively, while wearing the exoskeleton. Additionally, the peak value of the EMG signal decreased by 29.3% and 21.9%, and the integrated EMG signal value decreased by 46.7% and 36.1% on their affected vastus medialis and lateralis while wearing the exoskeleton, respectively. Finally, our results indicate improved medial-lateral balance by 61.2%, 81.6%, and 70.0% based on the degree of asymmetry (DOA), the center of pressure (COP), and the center of mass (COM), respectively. These results support the efficacy of using powered exoskeletons for high-torque tasks such as sit-to-stand transitions with stroke survivors.
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9
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Nesler C, Thomas G, Divekar N, Rouse EJ, Gregg RD. Enhancing Voluntary Motion with Modular, Backdrivable, Powered Hip and Knee Orthoses. IEEE Robot Autom Lett 2022; 7:6155-6162. [PMID: 36051565 PMCID: PMC9427014 DOI: 10.1109/lra.2022.3145580] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/05/2023]
Abstract
Mobility disabilities are prominent in society with wide-ranging deficits, motivating modular, partial-assist, lower-limb exoskeletons for this heterogeneous population. This paper introduces the Modular Backdrivable Lower-limb Unloading Exoskeleton (M-BLUE), which implements high torque, low mechanical impedance actuators on commercial orthoses with sheet metal modifications to produce a variety of hip- and/or knee-assisting configurations. Benchtop system identification verifies the desirable backdrive properties of the actuator, and allows for torque prediction within ±0.4 Nm. An able-bodied human subject experiment demonstrates that three unilateral configurations of M-BLUE (hip only, knee only, and hip-knee) with a simple gravity compensation controller can reduce muscle EMG readings in a lifting and lowering task relative to the bare condition. Reductions in mean muscular effort and peak muscle activation were seen across the primary squat musculature (excluding biceps femoris), demonstrating the potential to reduce fatigue leading to poor lifting posture. These promising results motivate applications of M-BLUE to additional populations, and the expansion of M-BLUE to bilateral and ankle configurations.
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Affiliation(s)
- Christopher Nesler
- Department of Electrical Engineering and Computer Science and the Robotics Institute
| | - Gray Thomas
- Department of Electrical Engineering and Computer Science and the Robotics Institute
| | - Nikhil Divekar
- Department of Electrical Engineering and Computer Science and the Robotics Institute
| | - Elliott J Rouse
- Department of Mechanical Engineering and the Robotics Institute, University of Michigan, Ann Arbor, MI 48109
| | - Robert D Gregg
- Department of Electrical Engineering and Computer Science and the Robotics Institute
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10
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Medrano RL, Thomas GC, Rouse EJ, Gregg RD. Analysis of the Bayesian Gait-State Estimation Problem for Lower-Limb Wearable Robot Sensor Configurations. IEEE Robot Autom Lett 2022; 7:7463-7470. [PMID: 35782346 PMCID: PMC9246062 DOI: 10.1109/lra.2022.3183790] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2023]
Abstract
Many exoskeletons today are primarily tested in controlled, steady-state laboratory conditions that are unrealistic representations of their real-world usage in which walking conditions (e.g., speed, slope, and stride length) change constantly. One potential solution is to detect these changing walking conditions online using Bayesian state estimation to deliver assistance that continuously adapts to the wearer's gait. This paper investigates such an approach in silico, aiming to understand 1) which of the various Bayesian filter assumptions best match the problem, and 2) which gait parameters can be feasibly estimated with different combinations of sensors available to different exoskeleton configurations (pelvis, thigh, shank, and/or foot). Our results suggest that the assumptions of the Extended Kalman Filter are well suited to accurately estimate phase, stride frequency, stride length, and ramp inclination with a wide variety of sparse sensor configurations.
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Affiliation(s)
- Roberto Leo Medrano
- Department of Mechanical Engineering and the Robotics Institute, University of Michigan, Ann Arbor, MI 48109 USA
| | - Gray Cortright Thomas
- Department of Electrical Engineering and Computer Science and the Robotics Institute, University of Michigan, Ann Arbor, MI 48109 USA
| | - Elliott J. Rouse
- Department of Mechanical Engineering and the Robotics Institute, University of Michigan, Ann Arbor, MI 48109 USA
| | - Robert D. Gregg
- Department of Electrical Engineering and Computer Science and the Robotics Institute, University of Michigan, Ann Arbor, MI 48109 USA
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11
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Ingraham KA, Remy CD, Rouse EJ. The role of user preference in the customized control of robotic exoskeletons. Sci Robot 2022; 7:eabj3487. [PMID: 35353602 DOI: 10.1126/scirobotics.abj3487] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/02/2022]
Abstract
User preference is a promising objective for the control of robotic exoskeletons because it may capture the multifactorial nature of exoskeleton use. However, to use it, we must first understand its characteristics in the context of exoskeleton control. Here, we systematically measured the control preferences of individuals wearing bilateral ankle exoskeletons during walking. We investigated users' repeatability identifying their preferences and how preference changes with walking speed, device exposure, and between individuals with different technical backgrounds. Twelve naive and 12 knowledgeable nondisabled participants identified their preferred assistance in repeated trials by simultaneously self-tuning the magnitude and timing of peak torque. They were blinded to the control parameters and relied solely on their perception of the assistance to guide their tuning. We found that participants' preferences ranged from 7.9 to 19.4 newton-meters and 54.1 to 59.2 percent of the gait cycle. Across trials, participants repeatably identified their preferences with a mean standard deviation of 1.7 newton-meters and 1.5 percent of the gait cycle. Within a trial, participants converged on their preference in 105 seconds. As the experiment progressed, naive users preferred higher torque magnitude. At faster walking speeds, these individuals were more precise at identifying the magnitude of their preferred assistance. Knowledgeable users preferred higher torque than naive users. These results highlight that although preference is a dynamic quantity, individuals can reliably identify their preferences. This work motivates strategies for the control of lower limb exoskeletons in which individuals customize assistance according to their unique preferences and provides meaningful insight into how users interact with exoskeletons.
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Affiliation(s)
- K A Ingraham
- Department of Mechanical Engineering, University of Michigan, Ann Arbor, MI, USA.,Robotics Institute, University of Michigan, Ann Arbor, MI, USA
| | - C D Remy
- Institute for Nonlinear Mechanics, University of Stuttgart, Stuttgart, Germany
| | - E J Rouse
- Department of Mechanical Engineering, University of Michigan, Ann Arbor, MI, USA.,Robotics Institute, University of Michigan, Ann Arbor, MI, USA
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12
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Medrano RL, Thomas GC, Rouse EJ. Can humans perceive the metabolic benefit provided by augmentative exoskeletons? J Neuroeng Rehabil 2022; 19:26. [PMID: 35219335 PMCID: PMC8881941 DOI: 10.1186/s12984-022-01002-w] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2021] [Accepted: 02/15/2022] [Indexed: 11/30/2022] Open
Abstract
BACKGROUND The purpose of augmentative exoskeletons is to help people exceed the limitations of their human bodies, but this cannot be realized unless people choose to use these exciting technologies. Although human walking efficiency has been highly optimized over generations, exoskeletons have been able to consistently improve this efficiency by 10-15%. However, despite these measurable improvements, exoskeletons today remain confined to the laboratory. To achieve widespread adoption, exoskeletons must not only exceed the efficiency of human walking, but also provide a perceivable benefit to their wearers. METHODS In this study, we quantify the perceptual threshold of the metabolic efficiency benefit provided during exoskeleton-assisted locomotion. Ten participants wore bilateral ankle exoskeletons during continuous walking. The assistance provided by the exoskeletons was varied in 2 min intervals while participants provided feedback on their metabolic rate. These data were aggregated and used to estimate the perceptual threshold. RESULTS Participants were able to detect a change in their metabolic rate of 22.7% (SD: 17.0%) with 75% accuracy. This indicates that in the short term and on average, wearers cannot yet reliably perceive the metabolic benefits of today's augmentative exoskeletons. CONCLUSIONS If wearers cannot perceive the benefits provided by these technologies, it will negatively affect their impact, including long-term adoption and product viability. Future exoskeleton researchers and designers can use these methods and results to inform the development of exoskeletons that reach their potential.
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Affiliation(s)
- Roberto Leo Medrano
- Department of Mechanical Engineering, University of Michigan, Ann Arbor, 48109 USA
- Robotics Institute, University of Michigan, 48109 Ann Arbor, USA
| | - Gray Cortright Thomas
- Department of Mechanical Engineering, University of Michigan, Ann Arbor, 48109 USA
- Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, 48109 USA
- Robotics Institute, University of Michigan, 48109 Ann Arbor, USA
| | - Elliott J. Rouse
- Department of Mechanical Engineering, University of Michigan, Ann Arbor, 48109 USA
- Robotics Institute, University of Michigan, 48109 Ann Arbor, USA
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13
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LIN JIANPING, DIVEKAR NIKHILV, THOMAS GRAYC, GREGG ROBERTD. Optimally Biomimetic Passivity-Based Control of a Lower-Limb Exoskeleton Over the Primary Activities of Daily Life. IEEE OPEN JOURNAL OF CONTROL SYSTEMS 2022; 1:15-28. [PMID: 35673605 PMCID: PMC9170045] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
Abstract
Task-specific, trajectory-based control methods commonly used in exoskeletons may be appropriate for individuals with paraplegia, but they overly constrain the volitional motion of individuals with remnant voluntary ability (representing a far larger population). Human-exoskeleton systems can be represented in the form of the Euler-Lagrange equations or, equivalently, the port-controlled Hamiltonian equations to design control laws that provide task-invariant assistance across a continuum of activities/environments by altering energetic properties of the human body. We previously introduced a port-controlled Hamiltonian framework that parameterizes the control law through basis functions related to gravitational and gyroscopic terms, which are optimized to fit normalized able-bodied joint torques across multiple walking gaits on different ground inclines. However, this approach did not have the flexibility to reproduce joint torques for a broader set of activities, including stair climbing and stand-to-sit, due to strict assumptions related to input-output passivity, which ensures the human remains in control of energy growth in the closed-loop dynamics. To provide biomimetic assistance across all primary activities of daily life, this paper generalizes this energy shaping framework by incorporating vertical ground reaction forces and global planar orientation into the basis set, while preserving passivity between the human joint torques and human joint velocities. We present an experimental implementation on a powered knee-ankle exoskeleton used by three able-bodied human subjects during walking on various inclines, ramp ascent/descent, and stand-to-sit, demonstrating the versatility of this control approach and its effect on muscular effort.
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Affiliation(s)
- JIANPING LIN
- Robotics Institute, University of Michigan, Ann Arbor, MI 48109 USA
| | | | - GRAY C. THOMAS
- Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI 48109 USA
| | - ROBERT D. GREGG
- Robotics Institute, University of Michigan, Ann Arbor, MI 48109 USA,Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI 48109 USA
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14
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Huang TH, Zhang S, Yu S, MacLean MK, Zhu J, Di Lallo A, Jiao C, Bulea TC, Zheng M, Su H. Modeling and Stiffness-Based Continuous Torque Control of Lightweight Quasi-Direct-Drive Knee Exoskeletons for Versatile Walking Assistance. IEEE T ROBOT 2022; 38:1442-1459. [DOI: 10.1109/tro.2022.3170287] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Affiliation(s)
- Tzu-Hao Huang
- Laboratory of Biomechatronics and Intelligent Robotics, Department of Mechanical and Aerospace Engineering, North Carolina State University, Raleigh, NC 27695 USA
| | - Sainan Zhang
- Laboratory of Biomechatronics and Intelligent Robotics, Department of Mechanical and Aerospace Engineering, North Carolina State University, Raleigh, NC 27695 USA
| | - Shuangyue Yu
- Laboratory of Biomechatronics and Intelligent Robotics, Department of Mechanical and Aerospace Engineering, North Carolina State University, Raleigh, NC 27695 USA
| | - Mhairi K. MacLean
- Laboratory of Biomechatronics and Intelligent Robotics 57522, Enschede The Netherlands, and also with the Department of Mechanical Engineering, University of Twente 57522, Enschede The Netherlands
| | - Junxi Zhu
- Laboratory of Biomechatronics and Intelligent Robotics, Department of Mechanical and Aerospace Engineering, North Carolina State University, Raleigh, NC 27695 USA
| | - Antonio Di Lallo
- Laboratory of Biomechatronics and Intelligent Robotics, Department of Mechanical and Aerospace Engineering, North Carolina State University, Raleigh, NC 27695 USA
| | - Chunhai Jiao
- Laboratory of Biomechatronics and Intelligent Robotics, Department of Mechanical and Aerospace Engineering, North Carolina State University, Raleigh, NC 27695 USA
| | - Thomas C. Bulea
- Functional and Applied Biomechanics Section, Rehabilitation Medicine Department, Clinical Center, National Institutes of Health, Bethesda, MD 20892 USA
| | - Minghui Zheng
- Department of Mechanical and Aerospace Engineering, University at Buffalo, Buffalo, NY 14260 USA
| | - Hao Su
- Laboratory of Biomechatronics and Intelligent Robotics, Department of Mechanical and Aerospace Engineering, North Carolina State University, Raleigh, NC 27695 USA
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15
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Babič J, Laffranchi M, Tessari F, Verstraten T, Novak D, Šarabon N, Ugurlu B, Peternel L, Torricelli D, Veneman JF. Challenges and solutions for application and wider adoption of wearable robots. WEARABLE TECHNOLOGIES 2021; 2:e14. [PMID: 38486636 PMCID: PMC10936284 DOI: 10.1017/wtc.2021.13] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/02/2021] [Revised: 08/25/2021] [Accepted: 09/18/2021] [Indexed: 03/17/2024]
Abstract
The science and technology of wearable robots are steadily advancing, and the use of such robots in our everyday life appears to be within reach. Nevertheless, widespread adoption of wearable robots should not be taken for granted, especially since many recent attempts to bring them to real-life applications resulted in mixed outcomes. The aim of this article is to address the current challenges that are limiting the application and wider adoption of wearable robots that are typically worn over the human body. We categorized the challenges into mechanical layout, actuation, sensing, body interface, control, human-robot interfacing and coadaptation, and benchmarking. For each category, we discuss specific challenges and the rationale for why solving them is important, followed by an overview of relevant recent works. We conclude with an opinion that summarizes possible solutions that could contribute to the wider adoption of wearable robots.
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Affiliation(s)
- Jan Babič
- Laboratory for Neuromechanics and Biorobotics, Department of Automation, Biocybernetics and Robotics, Jožef Stefan Institute, Ljubljana, Slovenia
| | - Matteo Laffranchi
- Rehab Technologies Lab, Istituto Italiano di Tecnologia, Genoa, Italy
| | - Federico Tessari
- Rehab Technologies Lab, Istituto Italiano di Tecnologia, Genoa, Italy
| | - Tom Verstraten
- Robotics & Multibody Mechanics Research Group, Vrije Universiteit Brussel and Flanders Make, Brussels, Belgium
| | - Domen Novak
- University of Wyoming, Laramie, Wyoming, USA
| | - Nejc Šarabon
- Faculty of Health Sciences, University of Primorska, Izola, Slovenia
| | - Barkan Ugurlu
- Biomechatronics Laboratory, Faculty of Engineering, Ozyegin University, Istanbul, Turkey
| | - Luka Peternel
- Delft Haptics Lab, Department of Cognitive Robotics, Delft University of Technology, Delft, The Netherlands
| | - Diego Torricelli
- Cajal Institute, Spanish National Research Council, Madrid, Spain
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16
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Wang S, Zhang B, Yu Z, Yan Y. Differential Soft Sensor-Based Measurement of Interactive Force and Assistive Torque for a Robotic Hip Exoskeleton. SENSORS (BASEL, SWITZERLAND) 2021; 21:6545. [PMID: 34640867 PMCID: PMC8512818 DOI: 10.3390/s21196545] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/06/2021] [Revised: 09/24/2021] [Accepted: 09/25/2021] [Indexed: 11/24/2022]
Abstract
With the emerging of wearable robots, the safety and effectiveness of human-robot physical interaction have attracted extensive attention. Recent studies suggest that online measurement of the interaction force between the robot and the human body is essential to the aspects above in wearable exoskeletons. However, a large proportion of existing wearable exoskeletons monitor and sense the delivered force and torque through an indirect-measure method, in which the torque is estimated by the motor current. Direct force/torque measuring through low-cost and compact wearable sensors remains an open problem. This paper presents a compact soft sensor system for wearable gait assistance exoskeletons. The contact force is converted into a voltage signal by measuring the air pressure within a soft pneumatic chamber. The developed soft force sensor system was implemented on a robotic hip exoskeleton, and the real-time interaction force between the human thigh and the exoskeleton was measured through two differential soft chambers. The delivered torque of the hip exoskeleton was calculated based on a characterization model. Experimental results suggested that the sensor system achieved direct force measurement with an error of 10.3 ± 6.58%, and torque monitoring for a hip exoskeleton which provided an understanding for the importance of direct force/torque measurement for assistive performance. Compared with traditional rigid force sensors, the proposed system has several merits, as it is compact, low-cost, and has good adaptability to the human body due to the soft structure.
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Affiliation(s)
- Sun’an Wang
- School of Mechanical Engineering, Xi’an Jiaotong University, No. 28, Xianning West Road, Xi’an 710049, China; (B.Z.); (Z.Y.); (Y.Y.)
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