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Biomimetics
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Bionic Technology – Robotic Exoskeletons and Prostheses
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Bionic Technology – Robotic Exoskeletons and Prostheses

A special issue of Biomimetics (ISSN 2313-7673). This special issue belongs to the section "Locomotion and Bioinspired Robotics".

Deadline for manuscript submissions: closed (30 April 2023) | Viewed by 15215

Special Issue Editor

Prof. Dr. Rafhael Milanezi de Andrade

E-Mail Website
Guest Editor
Department of Mechanical Engineering, Universidade Federal do Espírito Santo, Vitória, ‎‎Brazil‎
Interests: mechanical engineering; biomechanics; motion analysis; bioengineering; biomechatronics; robotic rehabilitation; medical robotics, bionics; design and control of prostheses, orthoses, and exoskeletons; user-robot interaction; soft robot
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Bionic technology has been successfully used to enhance human capabilities and improve the quality of life of disabled people. Recent advances in robotics, mechatronics, data science, soft robotics, neuroscience, photonics, and electronics have paved the way for a new generation of robotic prostheses and exoskeletons. However, the development of wearable robots is highly challenging. These systems should be lightweight and powerful enough to replace or support the limbs and capable of safely interacting with the user physically and cognitively .

For this Special Issue, entitled “Bionic Technology – Robotic Exoskeletons and Prostheses”, we call for contributions from researchers in the field of biomechatronics that cover design and control, exoskeletons, prostheses, physical and cognitive user–robot interaction in wearable robots, and medical robots and bionic devices, among other relevant topics.

Prof. Dr. Rafhael Milanezi de Andrade
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Biomimetics is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2200 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • prosthetics and exoskeletons
  • rehabilitation robotics
  • physical human–robot interaction
  • cognitive human–robot interaction
  • wearable robotics
  • medical robots and systems
  • design and control
  • bioinspired robot learning
  • machine learning for robot control
  • soft robot

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Published Papers (6 papers)

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Research

21 pages, 15681 KiB  
Article
Tracking Control for a Lower Extremity Exoskeleton Based on Adaptive Dynamic Programing
by Qiying Su, Zhongcai Pei and Zhiyong Tang
Biomimetics 2023, 8(4), 353; https://doi.org/10.3390/biomimetics8040353 - 9 Aug 2023
Cited by 1 | Viewed by 1397
Abstract
The utilization of lower extremity exoskeletons has witnessed a growing presence across diverse domains such as the military, medical treatment, and rehabilitation. This paper introduces a novel design of a lower extremity exoskeleton specifically tailored for individuals engaged in heavy object carrying tasks. [...] Read more.
The utilization of lower extremity exoskeletons has witnessed a growing presence across diverse domains such as the military, medical treatment, and rehabilitation. This paper introduces a novel design of a lower extremity exoskeleton specifically tailored for individuals engaged in heavy object carrying tasks. The exoskeleton incorporates an impressive 12 degrees of freedom (DOF), with four of them being effectively controlled through hydraulic cylinders. To achieve optimal control of this intricate lower extremity exoskeleton system, the authors propose an adaptive dynamic programming (ADP) algorithm. Several crucial components are established to implement this control scheme. These include the formulation of the state equation for the lower extremity exoskeleton system, which is well-suited for the ADP algorithm. Additionally, a corresponding performance index function based on the tracking error is devised, along with the game algebraic Riccati equation. By employing the value iteration ADP scheme, the lower extremity exoskeleton demonstrates highly effective tracking control. This research not only highlights the potential of the proposed control approach but also showcases its ability to enhance the overall performance and functionality of lower extremity exoskeletons, particularly in scenarios involving heavy object carrying. Overall, this study contributes to the advancement of lower extremity exoskeleton technology and offers valuable insights into the application of ADP algorithms for achieving precise and efficient control in demanding tasks. Full article
(This article belongs to the Special Issue Bionic Technology – Robotic Exoskeletons and Prostheses)
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14 pages, 4920 KiB  
Article
Biomimetic Design of a Tendon-Driven Myoelectric Soft Hand Exoskeleton for Upper-Limb Rehabilitation
by Rodrigo C. Silva, Bruno. G. Lourenço, Pedro H. F. Ulhoa, Eduardo A. F. Dias, Fransergio L. da Cunha, Cristiane P. Tonetto, Luis G. Villani, Claysson B. S. Vimieiro, Guilherme A. Lepski, Marina Monjardim and Rafhael M. Andrade
Biomimetics 2023, 8(3), 317; https://doi.org/10.3390/biomimetics8030317 - 19 Jul 2023
Cited by 6 | Viewed by 3051
Abstract
Degenerative diseases and injuries that compromise hand movement reduce individual autonomy and tend to cause financial and psychological problems to their family nucleus. To mitigate these limitations, over the past decade, hand exoskeletons have been designed to rehabilitate or enhance impaired hand movements. [...] Read more.
Degenerative diseases and injuries that compromise hand movement reduce individual autonomy and tend to cause financial and psychological problems to their family nucleus. To mitigate these limitations, over the past decade, hand exoskeletons have been designed to rehabilitate or enhance impaired hand movements. Although promising, these devices still have limitations, such as weight and cost. Moreover, the movements performed are not kinematically compatible with the joints, thereby reducing the achievements of the rehabilitation process. This article presents the biomimetic design of a soft hand exoskeleton actuated using artificial tendons designed to achieve low weight, volume, and cost, and to improve kinematic compatibility with the joints, comfort, and the sensitivity of the hand by allowing direct contact between the hand palm and objects. We employed two twisted string actuators and Bowden cables to move the artificial tendons and perform the grasping and opening of the hand. With this configuration, the heavy part of the system was reallocated to a test bench, allowing for a lightweight set of just 232 g attached to the arm. The system was triggered by the myoelectric signals of the biceps captured from the user’s skin to encourage the active participation of the user in the process. The device was evaluated by five healthy subjects who were asked to simulate a paralyzed hand, and manipulate different types of objects and perform grip strength. The results showed that the system was able to identify the intention of movement of the user with an accuracy of 90%, and the orthosis was able to enhance the ability of handling objects with gripping force up to 1.86 kgf. Full article
(This article belongs to the Special Issue Bionic Technology – Robotic Exoskeletons and Prostheses)
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17 pages, 833 KiB  
Article
Predicting Wrist Joint Angles from the Kinematics of the Arm: Application to the Control of Upper Limb Prostheses
by Antonio Pérez-González, Victor Roda-Casanova and Javier Sabater-Gazulla
Biomimetics 2023, 8(2), 219; https://doi.org/10.3390/biomimetics8020219 - 24 May 2023
Viewed by 1935
Abstract
Automation of wrist rotations in upper limb prostheses allows simplification of the human–machine interface, reducing the user’s mental load and avoiding compensatory movements. This study explored the possibility of predicting wrist rotations in pick-and-place tasks based on kinematic information from the other arm [...] Read more.
Automation of wrist rotations in upper limb prostheses allows simplification of the human–machine interface, reducing the user’s mental load and avoiding compensatory movements. This study explored the possibility of predicting wrist rotations in pick-and-place tasks based on kinematic information from the other arm joints. To do this, the position and orientation of the hand, forearm, arm, and back were recorded from five subjects during transport of a cylindrical and a spherical object between four different locations on a vertical shelf. The rotation angles in the arm joints were obtained from the records and used to train feed-forward neural networks (FFNNs) and time-delay neural networks (TDNNs) in order to predict wrist rotations (flexion/extension, abduction/adduction, and pronation/supination) based on the angles at the elbow and shoulder. Correlation coefficients between actual and predicted angles of 0.88 for the FFNN and 0.94 for the TDNN were obtained. These correlations improved when object information was added to the network or when it was trained separately for each object (0.94 for the FFNN, 0.96 for the TDNN). Similarly, it improved when the network was trained specifically for each subject. These results suggest that it would be feasible to reduce compensatory movements in prosthetic hands for specific tasks by using motorized wrists and automating their rotation based on kinematic information obtained with sensors appropriately positioned in the prosthesis and the subject’s body. Full article
(This article belongs to the Special Issue Bionic Technology – Robotic Exoskeletons and Prostheses)
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10 pages, 1569 KiB  
Article
Changes in Distance between a Wearable Robotic Exoskeleton User and Four-Wheeled Walker during Gait in Level and Slope Conditions: Implications for Fall Prevention Systems
by Koki Tan, Soichiro Koyama, Hiroaki Sakurai, Yoshikiyo Kanada and Shigeo Tanabe
Biomimetics 2023, 8(2), 213; https://doi.org/10.3390/biomimetics8020213 - 23 May 2023
Viewed by 1652
Abstract
When walking with wearable robotic exoskeletons (WRE) in people with spinal cord injury, the distance between the user and the walker is one of the most important perspectives for ensuring safety. The purpose of this study was to clarify the distance between WRE [...] Read more.
When walking with wearable robotic exoskeletons (WRE) in people with spinal cord injury, the distance between the user and the walker is one of the most important perspectives for ensuring safety. The purpose of this study was to clarify the distance between WRE users and four-wheeled walkers (4WW) while walking on level and sloping surfaces. To eliminate the effects of variation in neurological conditions, 12 healthy subjects participated. All participants ambulated using the WRE and the 4WW on level and sloping surfaces. The outcomes were the mean distances between the WRE users and the 4WWs in the level and slope conditions. To examine the influence of uphill and downhill slopes on distance, comparisons were conducted between the uphill or downhill conditions and the respective transitional periods. In the uphill condition, the mean distances were significantly greater than that in the level condition. Conversely, the mean distance moving downhill was significantly shorter than that in the level condition. Changes in the distance between the WRE user and the 4WW might increase the risk of falling forward on an uphill slope and backward on a downhill slope. This study’s results will assist in developing a new feedback system to prevent falls. Full article
(This article belongs to the Special Issue Bionic Technology – Robotic Exoskeletons and Prostheses)
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17 pages, 12267 KiB  
Article
Object Grasp Control of a 3D Robot Arm by Combining EOG Gaze Estimation and Camera-Based Object Recognition
by Muhammad Syaiful Amri bin Suhaimi, Kojiro Matsushita, Takahide Kitamura, Pringgo Widyo Laksono and Minoru Sasaki
Biomimetics 2023, 8(2), 208; https://doi.org/10.3390/biomimetics8020208 - 18 May 2023
Cited by 2 | Viewed by 2593
Abstract
The purpose of this paper is to quickly and stably achieve grasping objects with a 3D robot arm controlled by electrooculography (EOG) signals. A EOG signal is a biological signal generated when the eyeballs move, leading to gaze estimation. In conventional research, gaze [...] Read more.
The purpose of this paper is to quickly and stably achieve grasping objects with a 3D robot arm controlled by electrooculography (EOG) signals. A EOG signal is a biological signal generated when the eyeballs move, leading to gaze estimation. In conventional research, gaze estimation has been used to control a 3D robot arm for welfare purposes. However, it is known that the EOG signal loses some of the eye movement information when it travels through the skin, resulting in errors in EOG gaze estimation. Thus, EOG gaze estimation is difficult to point out the object accurately, and the object may not be appropriately grasped. Therefore, developing a methodology to compensate, for the lost information and increase spatial accuracy is important. This paper aims to realize highly accurate object grasping with a robot arm by combining EMG gaze estimation and the object recognition of camera image processing. The system consists of a robot arm, top and side cameras, a display showing the camera images, and an EOG measurement analyzer. The user manipulates the robot arm through the camera images, which can be switched, and the EOG gaze estimation can specify the object. In the beginning, the user gazes at the screen’s center position and then moves their eyes to gaze at the object to be grasped. After that, the proposed system recognizes the object in the camera image via image processing and grasps it using the object centroid. The object selection is based on the object centroid closest to the estimated gaze position within a certain distance (threshold), thus enabling highly accurate object grasping. The observed size of the object on the screen can differ depending on the camera installation and the screen display state. Therefore, it is crucial to set the distance threshold from the object centroid for object selection. The first experiment is conducted to clarify the distance error of the EOG gaze estimation in the proposed system configuration. As a result, it is confirmed that the range of the distance error is 1.8–3.0 cm. The second experiment is conducted to evaluate the performance of the object grasping by setting two thresholds from the first experimental results: the medium distance error value of 2 cm and the maximum distance error value of 3 cm. As a result, it is found that the grasping speed of the 3 cm threshold is 27% faster than that of the 2 cm threshold due to more stable object selection. Full article
(This article belongs to the Special Issue Bionic Technology – Robotic Exoskeletons and Prostheses)
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17 pages, 6454 KiB  
Article
Design and Optimization of Lower Limb Rehabilitation Exoskeleton with a Multiaxial Knee Joint
by Jiandong Jiang, Peisong Chen, Jiyu Peng, Xin Qiao, Fengle Zhu and Jiang Zhong
Biomimetics 2023, 8(2), 156; https://doi.org/10.3390/biomimetics8020156 - 14 Apr 2023
Cited by 11 | Viewed by 3844
Abstract
To facilitate rehabilitation training for patients, we proposed the implementation of an anthropomorphic exoskeleton structure that incorporates a variable instantaneous center of rotation (ICR). This design considers the variability in knee ICR among individuals, resulting from the irregular form of the human knee [...] Read more.
To facilitate rehabilitation training for patients, we proposed the implementation of an anthropomorphic exoskeleton structure that incorporates a variable instantaneous center of rotation (ICR). This design considers the variability in knee ICR among individuals, resulting from the irregular form of the human knee joint, and leverages a double-degrees-of-freedom (2DOF) five-bar mechanism to adapt to these differences. The walking gait of the human lower limb and the corresponding knee ICR were measured and calculated using an optical 3D motion capture system. The optimal dimension parameters of the five-bar mechanism were then obtained through the optimization of human movement position inputs and rod length constraints to minimize the error in knee ICR, gait angle, and ankle trajectory between the human and the exoskeleton. Finally, we established an exoskeleton prototype to conduct relevant experimental tests. The experiment results showed that the average errors of knee ICR trajectory, hip angle, knee angle, and ankle trajectory were 5.52 × 10−4 m, 0.010 rad, 0.014 rad, and 1.57 × 10−3 m, respectively. The experimental results demonstrated that the exoskeleton’s movement trajectory was close to the human’s, reducing the human–mechanism interaction force and improving patient comfort during rehabilitation training. Full article
(This article belongs to the Special Issue Bionic Technology – Robotic Exoskeletons and Prostheses)
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