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Biomimetics
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Biologically Inspired Assistive and Rehabilitation Robotics
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Biologically Inspired Assistive and Rehabilitation Robotics

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

Deadline for manuscript submissions: closed (31 December 2023) | Viewed by 14136

Special Issue Editor

Dr. Giuk Lee

E-Mail Website
Guest Editor
Department of Mechanical Engineering, Chung-Ang University, Seoul, Republic of Korea
Interests: wearable robotics; assistive technology; bio-mechatronics; human–robot interaction
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Wearable robots are robotic systems that can augment, support, and restore various physical abilities of the wearer. Different types of wearable robots have been proposed. Specifically, given their primary purpose of assisting people's physical abilities, wearable robots are often developed by imitating the principles of the human musculoskeletal system.

This Special Issue aims to introduce and share the latest research in the field of biologically inspired wearable robots. In particular, this Issue introduces various types of wearable robots that utilize biomimetics in multiple aspects, such as robot design, control algorithms, sensors, and recognition. This Issue also covers the utilization and evaluation of biologically inspired wearable robots.

Potential topics include, but are not limited to: assistive and rehabilitation robotics; biomechanical and physiological evaluation; biologically inspired design and control; biologically inspired sensing and recognition.

Dr. Giuk Lee
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

  • biologically inspired
  • biomimetic
  • wearable robot
  • assistive and rehabilitation robot
  • design and control
  • sensing and recognition

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Published Papers (5 papers)

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Research

15 pages, 2641 KiB  
Article
Design and Evaluation of a Bilateral Semi-Rigid Exoskeleton to Assist Hip Motion
by Arash Mohammadzadeh Gonabadi, Prokopios Antonellis, Alex C. Dzewaltowski, Sara A. Myers, Iraklis I. Pipinos and Philippe Malcolm
Biomimetics 2024, 9(4), 211; https://doi.org/10.3390/biomimetics9040211 - 30 Mar 2024
Cited by 4 | Viewed by 2888
Abstract
This study focused on designing and evaluating a bilateral semi-rigid hip exoskeleton. The exoskeleton assisted the hip joint, capitalizing on its proximity to the body’s center of mass. Unlike its rigid counterparts, the semi-rigid design permitted greater freedom of movement. A temporal force-tracking [...] Read more.
This study focused on designing and evaluating a bilateral semi-rigid hip exoskeleton. The exoskeleton assisted the hip joint, capitalizing on its proximity to the body’s center of mass. Unlike its rigid counterparts, the semi-rigid design permitted greater freedom of movement. A temporal force-tracking controller allowed us to prescribe torque profiles during walking. We ensured high accuracy by tuning control parameters and series elasticity. The evaluation involved experiments with ten participants across ten force profile conditions with different end-timings and peak magnitudes. Our findings revealed a trend of greater reductions in metabolic cost with assistance provided at later timings in stride and at greater magnitudes. Compared to walking with the exoskeleton powered off, the largest reduction in metabolic cost was 9.1%. This was achieved when providing assistance using an end-timing at 44.6% of the stride cycle and a peak magnitude of 0.11 Nm kg−1. None of the tested conditions reduced the metabolic cost compared to walking without the exoskeleton, highlighting the necessity for further enhancements, such as a lighter and more form-fitting design. The optimal end-timing aligns with findings from other soft hip exosuit devices, indicating a comparable interaction with this prototype to that observed in entirely soft exosuit prototypes. Full article
(This article belongs to the Special Issue Biologically Inspired Assistive and Rehabilitation Robotics)
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22 pages, 8888 KiB  
Article
Biohybrid Robotic Hand to Investigate Tactile Encoding and Sensorimotor Integration
by Craig Ades, Moaed A. Abd, Douglas T. Hutchinson, Emmanuelle Tognoli, E Du, Jianning Wei and Erik D. Engeberg
Biomimetics 2024, 9(2), 78; https://doi.org/10.3390/biomimetics9020078 - 27 Jan 2024
Cited by 2 | Viewed by 3106
Abstract
For people who have experienced a spinal cord injury or an amputation, the recovery of sensation and motor control could be incomplete despite noteworthy advances with invasive neural interfaces. Our objective is to explore the feasibility of a novel biohybrid robotic hand model [...] Read more.
For people who have experienced a spinal cord injury or an amputation, the recovery of sensation and motor control could be incomplete despite noteworthy advances with invasive neural interfaces. Our objective is to explore the feasibility of a novel biohybrid robotic hand model to investigate aspects of tactile sensation and sensorimotor integration with a pre-clinical research platform. Our new biohybrid model couples an artificial hand with biological neural networks (BNN) cultured in a multichannel microelectrode array (MEA). We decoded neural activity to control a finger of the artificial hand that was outfitted with a tactile sensor. The fingertip sensations were encoded into rapidly adapting (RA) or slowly adapting (SA) mechanoreceptor firing patterns that were used to electrically stimulate the BNN. We classified the coherence between afferent and efferent electrodes in the MEA with a convolutional neural network (CNN) using a transfer learning approach. The BNN exhibited the capacity for functional specialization with the RA and SA patterns, represented by significantly different robotic behavior of the biohybrid hand with respect to the tactile encoding method. Furthermore, the CNN was able to distinguish between RA and SA encoding methods with 97.84% ± 0.65% accuracy when the BNN was provided tactile feedback, averaged across three days in vitro (DIV). This novel biohybrid research platform demonstrates that BNNs are sensitive to tactile encoding methods and can integrate robotic tactile sensations with the motor control of an artificial hand. This opens the possibility of using biohybrid research platforms in the future to study aspects of neural interfaces with minimal human risk. Full article
(This article belongs to the Special Issue Biologically Inspired Assistive and Rehabilitation Robotics)
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17 pages, 19208 KiB  
Article
Design, Characterization, and Preliminary Assessment of a Two-Degree-of-Freedom Powered Ankle–Foot Prosthesis
by Tsung-Han Hsieh, Hyungeun Song, Tony Shu, Junqing Qiao, Seong Ho Yeon, Matthew Carney, Luke Mooney, Jean-François Duval and Hugh Herr
Biomimetics 2024, 9(2), 76; https://doi.org/10.3390/biomimetics9020076 - 26 Jan 2024
Cited by 3 | Viewed by 2346
Abstract
Powered ankle prostheses have been proven to improve the walking economy of people with transtibial amputation. All commercial powered ankle prostheses that are currently available can only perform one-degree-of-freedom motion in a limited range. However, studies have shown that the frontal plane motion [...] Read more.
Powered ankle prostheses have been proven to improve the walking economy of people with transtibial amputation. All commercial powered ankle prostheses that are currently available can only perform one-degree-of-freedom motion in a limited range. However, studies have shown that the frontal plane motion during ambulation is associated with balancing. In addition, as more advanced neural interfaces have become available for people with amputation, it is possible to fully recover ankle function by combining neural signals and a robotic ankle. Accordingly, there is a need for a powered ankle prosthesis that can have active control on not only plantarflexion and dorsiflexion but also eversion and inversion. We designed, built, and evaluated a two-degree-of-freedom (2-DoF) powered ankle–foot prosthesis that is untethered and can support level-ground walking. Benchtop tests were conducted to characterize the dynamics of the system. Walking trials were performed with a 77 kg subject that has unilateral transtibial amputation to evaluate system performance under realistic conditions. Benchtop tests demonstrated a step response rise time of less than 50 milliseconds for a torque of 40 N·m on each actuator. The closed-loop torque bandwidth of the actuator is 9.74 Hz. Walking trials demonstrated torque tracking errors (root mean square) of less than 7 N·m. These results suggested that the device can perform adequate torque control and support level-ground walking. This prosthesis can serve as a platform for studying biomechanics related to balance and has the possibility of further recovering the biological function of the ankle–subtalar–foot complex beyond the existing powered ankles. Full article
(This article belongs to the Special Issue Biologically Inspired Assistive and Rehabilitation Robotics)
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18 pages, 1968 KiB  
Article
Transhumeral Arm Reaching Motion Prediction through Deep Reinforcement Learning-Based Synthetic Motion Cloning
by Muhammad Hannan Ahmed, Kyo Kutsuzawa and Mitsuhiro Hayashibe
Biomimetics 2023, 8(4), 367; https://doi.org/10.3390/biomimetics8040367 - 15 Aug 2023
Cited by 5 | Viewed by 2340
Abstract
The lack of intuitive controllability remains a primary challenge in enabling transhumeral amputees to control a prosthesis for arm reaching with residual limb kinematics. Recent advancements in prosthetic arm control have focused on leveraging the predictive capabilities of artificial neural networks (ANNs) to [...] Read more.
The lack of intuitive controllability remains a primary challenge in enabling transhumeral amputees to control a prosthesis for arm reaching with residual limb kinematics. Recent advancements in prosthetic arm control have focused on leveraging the predictive capabilities of artificial neural networks (ANNs) to automate elbow joint motion and wrist pronation–supination during target reaching tasks. However, large quantities of human motion data collected from different subjects for various activities of daily living (ADL) tasks are required to train these ANNs. For example, the reaching motion can be altered when the height of the desk is changed; however, it is cumbersome to conduct human experiments for all conditions. This paper proposes a framework for cloning motion datasets using deep reinforcement learning (DRL) to cater to training data requirements. DRL algorithms have been demonstrated to create human-like synergistic motion in humanoid agents to handle redundancy and optimize movements. In our study, we collected real motion data from six individuals performing multi-directional arm reaching tasks in the horizontal plane. We generated synthetic motion data that mimicked similar arm reaching tasks by utilizing a physics simulation and DRL-based arm manipulation. We then trained a CNN-LSTM network with different configurations of training motion data, including DRL, real, and hybrid datasets, to test the efficacy of the cloned motion data. The results of our evaluation showcase the effectiveness of the cloned motion data in training the ANN to predict natural elbow motion accurately across multiple subjects. Furthermore, motion data augmentation through combining real and cloned motion datasets has demonstrated the enhanced robustness of the ANN by supplementing and diversifying the limited training data. These findings have significant implications for creating synthetic dataset resources for various arm movements and fostering strategies for automatized prosthetic elbow motion. Full article
(This article belongs to the Special Issue Biologically Inspired Assistive and Rehabilitation Robotics)
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14 pages, 1938 KiB  
Article
The Effects of a Custom−Designed High−Collar Shoe on Muscular Activity, Dynamic Stability, and Leg Stiffness: A Biomimetic Approach Study
by Alireza Nasirzadeh, Jaeha Yang, Seungtae Yang, Juseok Yun, Young Yoon Bae, Juyeon Park, Jooeun Ahn and Giuk Lee
Biomimetics 2023, 8(3), 274; https://doi.org/10.3390/biomimetics8030274 - 27 Jun 2023
Cited by 1 | Viewed by 2498
Abstract
High-collar shoes are a biomimetic approach to preventing lateral ankle injuries during high-demand activities; however, the influence of collar stiffness (CS) on parameters related to lateral ankle sprain prevention during running remains unclear. In this study, we investigated the effects of a custom-designed [...] Read more.
High-collar shoes are a biomimetic approach to preventing lateral ankle injuries during high-demand activities; however, the influence of collar stiffness (CS) on parameters related to lateral ankle sprain prevention during running remains unclear. In this study, we investigated the effects of a custom-designed shoe CS on muscular activity, dynamic stability, and leg stiffness (Kleg) during running using a biomimetic design approach inspired by the mechanisms of ankle sprain prevention. Sixteen healthy male participants ran on a treadmill while wearing a custom-designed high-collar shoe with low, medium, and high CS conditions, measured using circumferential ankle pressure (CAP). Lower extremity kinematics and electromyography (EMG) data were recorded simultaneously. One-way repeated-measures ANOVA was conducted to compare the CS conditions. Results indicate that high and medium CS conditions significantly reduce sagittal and frontal ankle ranges of motion (ROMs) compared to the low CS condition, providing improved stability and support against lateral ankle sprain; moreover, there was a trend towards higher dynamic stability and Kleg with increasing CS. Our study highlights the importance of considering the CAP in regulating high-collar stiffness properties and how higher CS may provide better support for the ankle during running. Nevertheless, additional research is necessary to validate the efficacy of the current design in preventing ankle sprains during high-demand activities. Full article
(This article belongs to the Special Issue Biologically Inspired Assistive and Rehabilitation Robotics)
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