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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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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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David JP, Schick D, Rapp L, Schick J, Glaser M. SensAA-Design and Verification of a Cloud-Based Wearable Biomechanical Data Acquisition System. SENSORS (BASEL, SWITZERLAND) 2024; 24:2405. [PMID: 38676022 PMCID: PMC11053589 DOI: 10.3390/s24082405] [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: 12/30/2023] [Revised: 03/29/2024] [Accepted: 04/04/2024] [Indexed: 04/28/2024]
Abstract
Exoskeletons designed to assist patients with activities of daily living are becoming increasingly popular, but still are subject to research. In order to gather requirements for the design of such systems, long-term gait observation of the patients over the course of multiple days in an environment of daily living are required. In this paper a wearable all-in-one data acquisition system for collecting and storing biomechanical data in everyday life is proposed. The system is designed to be cost efficient and easy to use, using off-the-shelf components and a cloud server system for centralized data storage. The measurement accuracy of the system was verified, by measuring the angle of the human knee joint at walking speeds between 3 and 12 km/h in reference to an optical motion analysis system. The acquired data were uploaded to a cloud database via a smartphone application. Verification results showed that the proposed toolchain works as desired. The system reached an RMSE from 2.9° to 8°, which is below that of most comparable systems. The system provides a powerful, scalable platform for collecting and processing biomechanical data, which can help to automize the generation of an extensive database for human kinematics.
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Affiliation(s)
| | | | | | | | - Markus Glaser
- Zentrum für Zuverlässige Mechatronische Systeme (ZMS), Aalen University, 73430 Aalen, Germany
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Zhang J, Lin J, Peddinti V, Gregg RD. Optimal Energy Shaping Control for a Backdrivable Hip Exoskeleton. PROCEEDINGS OF THE ... AMERICAN CONTROL CONFERENCE. AMERICAN CONTROL CONFERENCE 2023; 2023:2065-2070. [PMID: 37790804 PMCID: PMC10544752 DOI: 10.23919/acc55779.2023.10155839] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/05/2023]
Abstract
Task-dependent controllers widely used in exoskeletons track predefined trajectories, which overly constrain the volitional motion of individuals with remnant voluntary mobility. Energy shaping, on the other hand, provides task-invariant assistance by altering the human body's dynamic characteristics in the closed loop. While human-exoskeleton systems are often modeled using Euler-Lagrange equations, in our previous work we modeled the system as a port-controlled-Hamiltonian system, and a task-invariant controller was designed for a knee-ankle exoskeleton using interconnection-damping assignment passivity-based control. In this paper, we extend this framework to design a controller for a backdrivable hip exoskeleton to assist multiple tasks. A set of basis functions that contains information of kinematics is selected and corresponding coefficients are optimized, which allows the controller to provide torque that fits normative human torque for different activities of daily life. Human-subject experiments with two able-bodied subjects demonstrated the controller's capability to reduce muscle effort across different tasks.
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Affiliation(s)
- Jiefu Zhang
- Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI 48109, USA
| | - Jianping Lin
- Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI 48109, USA
- State Key Laboratory of Mechanical System and Vibration, School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Vamsi Peddinti
- Robotics, University of Michigan, Ann Arbor, MI 48109, USA
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Siviy C, Baker LM, Quinlivan BT, Porciuncula F, Swaminathan K, Awad LN, Walsh CJ. Opportunities and challenges in the development of exoskeletons for locomotor assistance. Nat Biomed Eng 2022; 7:456-472. [PMID: 36550303 DOI: 10.1038/s41551-022-00984-1] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2020] [Accepted: 11/08/2022] [Indexed: 12/24/2022]
Abstract
Exoskeletons can augment the performance of unimpaired users and restore movement in individuals with gait impairments. Knowledge of how users interact with wearable devices and of the physiology of locomotion have informed the design of rigid and soft exoskeletons that can specifically target a single joint or a single activity. In this Review, we highlight the main advances of the past two decades in exoskeleton technology and in the development of lower-extremity exoskeletons for locomotor assistance, discuss research needs for such wearable robots and the clinical requirements for exoskeleton-assisted gait rehabilitation, and outline the main clinical challenges and opportunities for exoskeleton technology.
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Affiliation(s)
- Christopher Siviy
- John A Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA
| | - Lauren M Baker
- John A Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA
| | - Brendan T Quinlivan
- John A Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA
| | - Franchino Porciuncula
- John A Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA.,Department of Physical Therapy, College of Health and Rehabilitation Sciences: Sargent, Boston University, Boston, MA, USA
| | - Krithika Swaminathan
- John A Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA
| | - Louis N Awad
- Department of Physical Therapy, College of Health and Rehabilitation Sciences: Sargent, Boston University, Boston, MA, USA
| | - Conor J Walsh
- John A Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA.
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Yang C, Yu L, Xu L, Yan Z, Hu D, Zhang S, Yang W. Current developments of robotic hip exoskeleton toward sensing, decision, and actuation: A review. WEARABLE TECHNOLOGIES 2022; 3:e15. [PMID: 38486916 PMCID: PMC10936331 DOI: 10.1017/wtc.2022.11] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/06/2022] [Revised: 05/22/2022] [Accepted: 06/09/2022] [Indexed: 03/17/2024]
Abstract
The aging population is now a global challenge, and impaired walking ability is a common feature in the elderly. In addition, some occupations such as military and relief workers require extra physical help to perform tasks efficiently. Robotic hip exoskeletons can support ambulatory functions in the elderly and augment human performance in healthy people during normal walking and loaded walking by providing assistive torque. In this review, the current development of robotic hip exoskeletons is presented. In addition, the framework of actuation joints and the high-level control strategy (including the sensors and data collection, the way to recognize gait phase, the algorithms to generate the assist torque) are described. The exoskeleton prototypes proposed by researchers in recent years are organized to benefit the related fields realizing the limitations of the available robotic hip exoskeletons, therefore, this work tends to be an influential factor with a better understanding of the development and state-of-the-art technology.
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Affiliation(s)
- Canjun Yang
- Ningbo Research Institute, Zhejiang University, Ningbo, China
- School of Mechanical Engineering, Zhejiang University, Hangzhou, China
- School of Mechanical and Energy Engineering, NingboTech University, Ningbo, China
| | - Linfan Yu
- Ningbo Research Institute, Zhejiang University, Ningbo, China
- School of Mechanical Engineering, Zhejiang University, Hangzhou, China
| | - Linghui Xu
- Ningbo Research Institute, Zhejiang University, Ningbo, China
- School of Mechanical Engineering, Zhejiang University, Hangzhou, China
| | - Zehao Yan
- Ningbo Research Institute, Zhejiang University, Ningbo, China
- School of Mechanical Engineering, Zhejiang University, Hangzhou, China
| | - Dongming Hu
- School of Mechanical and Energy Engineering, NingboTech University, Ningbo, China
| | - Sheng Zhang
- Ningbo Research Institute, Zhejiang University, Ningbo, China
- School of Mechanical Engineering, Zhejiang University, Hangzhou, China
| | - Wei Yang
- Ningbo Research Institute, Zhejiang University, Ningbo, China
- School of Mechanical Engineering, Zhejiang University, Hangzhou, China
- School of Mechanical and Energy Engineering, NingboTech University, Ningbo, China
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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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