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Actuators
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Intelligent Systems, Robots and Devices for Healthcare and Rehabilitation
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Intelligent Systems, Robots and Devices for Healthcare and Rehabilitation

A special issue of Actuators (ISSN 2076-0825). This special issue belongs to the section "Actuators for Medical Instruments".

Deadline for manuscript submissions: 30 June 2025 | Viewed by 7684

Special Issue Editors

Dr. Duk Shin

E-Mail Website
Guest Editor
Department of Mechatronics, Tokyo Polytechnic University, Atsugi 243-0297, Japan
Interests: BMI/BCI; rehabilitation robot
Dr. JaeHyo Kim

E-Mail Website
Guest Editor
Department of Mechanical and Control Engineering, Handong Global University, Pohang 37554, Republic of Korea
Interests: neuro robotics; rehabilitation robot; human motor control
Dr. Abdelkader Nasreddine Belkacem

E-Mail Website
Guest Editor
Department of Computer and Network Engineering, United Arab Emirates University, Abu Dhabi, United Arab Emirates
Interests: brain computer interface; human-robot interaction; applied AI

Special Issue Information

Dear Colleagues,

Over time, the motor skills of older adults and people with neuromuscular disorders gradually decline, affecting both movement speed and accuracy. Intelligent healthcare and biomedical systems have had a major impact on this field over the past decade and are expected to revolutionize rehabilitation and the treatment of movement disorders caused by aging, stroke, and neuromuscular diseases. How to assess and support motor improvement in this field is crucial.

This requires more quantitative methods based on the collection and processing of biological signals as well as control actuators to assist and resist for rehabilitation and healthcare systems.

Relevant are advances in neural signal acquisition, machine learning processes of neural signals, and computer as well as robotic technologies for assisting humans. These areas have the potential to support rehabilitation and healthcare strategies by providing standards for biomedical engineering.

We invite researchers to submit original research papers and review articles that address novel methods for rehabilitation that promote advances to help patients and older adults with motor impairments, including brain–machine interfaces, prosthetics, rehabilitation robots, and control actuators. These new methods promote the advancement of intelligent healthcare and biomedical systems.

Potential topics include, but are not limited to, the following:

  • Actuator control methods for interactions between human and devices.
  • Novel rehabilitation/healthcare systems.
  • Assistive technologies for patients with motor control impairments.
  • Personalized rehabilitation interfaces for adapted physical activity.
  • New techniques using deep learning and machine learning.
  • Internet of Medical Things (IoMT).
  • Biomimetic robots and home support robots.

Dr. Duk Shin
Dr. JaeHyo Kim
Dr. Abdelkader Nasreddine Belkacem
Guest Editors

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. Actuators 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 2400 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

  • intelligent healthcare and biomedical systems
  • rehabilitation
  • actuator control
  • biomimetic robots

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (6 papers)

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Research

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17 pages, 3174 KiB  
Article
Real-Time Motor Control Using a Raspberry Pi, ROS, and CANopen over EtherCAT, with Application to a Semi-Active Prosthetic Ankle
by Kieran M. Nichols, Rebecca A. Roembke and Peter G. Adamczyk
Actuators 2025, 14(2), 84; https://doi.org/10.3390/act14020084 - 10 Feb 2025
Viewed by 1094
Abstract
This paper focused on the implementation method and results of modifying a Raspberry Pi 4 for real-time control of brushless direct-current motors, with application in a semi-active two-axis ankle prosthesis. CANopen over EtherCAT was implemented directly on the Raspberry Pi to synchronize real-time [...] Read more.
This paper focused on the implementation method and results of modifying a Raspberry Pi 4 for real-time control of brushless direct-current motors, with application in a semi-active two-axis ankle prosthesis. CANopen over EtherCAT was implemented directly on the Raspberry Pi to synchronize real-time communication between it and the motor controllers. Kinematic algorithms for setting ankle angles of zero to ten degrees in any combination of sagittal and frontal angles were implemented. To achieve reliable motor communication, where the motors continuously move, the distributed clock synchronization of Linux and Motor driver systems needs to have a finely tuned Proportional-Integral compensation and a consistent sampling period. Data collection involved moving the ankle through 33 unique pre-selected ankle configurations nine times. The system allowed for quick movement (mean settling time 0.192 s), reliable synchronization (standard deviation of 4.51 microseconds for sampling period), and precise movement (mean movement error less than 0.2 deg) for ankle angle changes and also a high update rate (250 microseconds sampling period) with modest CPU load (12.48%). This system aims to allow for the prosthesis to move within a single swing phase, enabling it to efficiently adapt to various speeds and terrains, such as walking on slopes, stairs, or around corners. Full article
(This article belongs to the Special Issue Intelligent Systems, Robots and Devices for Healthcare and Rehabilitation)
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15 pages, 2824 KiB  
Article
The Technical Development of a Prototype Lower-Limb Therapy Device for Bed-Resting Users
by Juan Fang, Adrien Cerrito, Simón Gamero Schertenleib, Patrick von Raumer and Kai-Uwe Schmitt
Actuators 2025, 14(2), 60; https://doi.org/10.3390/act14020060 - 26 Jan 2025
Viewed by 641
Abstract
It is generally recommended that bed-resting patients be mobilised early to promote recovery. The aim of this work was to develop and evaluate the usability of a prototype in-bed lower-limb therapy device that offers various training patterns for the feet and legs, featuring [...] Read more.
It is generally recommended that bed-resting patients be mobilised early to promote recovery. The aim of this work was to develop and evaluate the usability of a prototype in-bed lower-limb therapy device that offers various training patterns for the feet and legs, featuring an intuitive user interface and interactive exergames. Based on clinical interviews, the user requirements for the device were determined. The therapy device consisted of two compact foot platforms with integrated electric motors and force sensors. Movement control strategies and a user interface with computer games were developed. Through a touch screen, the target force and position trajectories were defined. Using automatic position and force control algorithms, the device produced leg flexion/extension with synchronised ankle plantarflexion/dorsiflexion as well as leg pressing with adjustable resistive loading. An evaluation test on 12 able-bodied participants showed that the device produced passive (mean position control errors: 8.91 mm linearly and 1.62° in the ankle joints) and active leg training (force control error: 2.52 N). The computer games were proven to be interesting, engaging, and responsive to the training movement. It was demonstrated that the device was technically usable in terms of mechatronics, movement control, user interface, and computer games. The advancements in well-controlled movement, multi-modal training patterns, convenient operation, and intuitive feedback enable the compact therapy device to be a potential system for bed-resting users to improve physical activity and cognitive functionality. Full article
(This article belongs to the Special Issue Intelligent Systems, Robots and Devices for Healthcare and Rehabilitation)
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13 pages, 4213 KiB  
Article
Machine Learning Models for Assistance from Soft Robotic Elbow Exoskeleton to Reduce Musculoskeletal Disorders
by Sanjana Suresh, Inderjeet Singh and Muthu B. J. Wijesundara
Actuators 2025, 14(2), 44; https://doi.org/10.3390/act14020044 - 22 Jan 2025
Viewed by 1078
Abstract
Musculoskeletal disorders are very common injuries among occupational and healthcare workers. These injuries are preventable in many scenarios using exoskeleton-based assistive technology. Soft robotics initiates an evolution in exoskeleton devices due to their safe human interactions, ergonomic design, and adaptive characteristics. Despite their [...] Read more.
Musculoskeletal disorders are very common injuries among occupational and healthcare workers. These injuries are preventable in many scenarios using exoskeleton-based assistive technology. Soft robotics initiates an evolution in exoskeleton devices due to their safe human interactions, ergonomic design, and adaptive characteristics. Despite their enormous advantages, it is a challenging task to model and control soft robotic devices due to their inherent nonlinearity and hysteresis. Learning-based approaches are becoming more popular to overcome these limitations. This work proposes an approach to estimate the pressure input for a pneumatically actuated soft robotic elbow exoskeleton to assist occupational workers to avoid musculoskeletal disorders. An elbow exoskeleton design made up of modular pneumatic soft actuators is discussed, which helps to flex/extend an elbow joint. Machine learning (ML) approaches are used to develop a relationship between the air pressure, the bending angle of the elbow, and the percentage of the weight of the arm to be assisted by the exoskeleton. The most popular and widely used regression-based ML approaches are applied and compared in terms of accuracy and computation cost. Further, a modified KNN (K-Nearest Neighbor) approach is proposed, which outperforms the accuracy of other approaches. Full article
(This article belongs to the Special Issue Intelligent Systems, Robots and Devices for Healthcare and Rehabilitation)
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12 pages, 796 KiB  
Article
Tug-of-War-Style High-Force Fluidic Actuation for Small Diameter Steerable Instruments
by Robert Lathrop, Mouloud Ourak, Jan Deprest and Emmanuel Vander Poorten
Actuators 2024, 13(11), 444; https://doi.org/10.3390/act13110444 - 7 Nov 2024
Viewed by 940
Abstract
Miniature steerable instruments have the potential to reduce the invasiveness of therapeutic interventions and enable new treatment options. Traditional ways of driving such instruments rely on extrinsic systems due to the challenge of miniaturizing and embedding intrinsic actuators that are powerful enough near [...] Read more.
Miniature steerable instruments have the potential to reduce the invasiveness of therapeutic interventions and enable new treatment options. Traditional ways of driving such instruments rely on extrinsic systems due to the challenge of miniaturizing and embedding intrinsic actuators that are powerful enough near the instrument tip or within the instrument shaft. This work introduces a method to amplify the output force of fluidic actuators by connecting their outputs in parallel but distributing them serially in currently underutilized space along the device’s long axis. It is shown that this new approach makes it possible to realize a significant force amplification within the same instrument diameter, producing a 380% higher static force and a further driving motion of the steerable bending segment 55.6° than an actuator representing the current state of the art, all while occupying a similar footprint. Full article
(This article belongs to the Special Issue Intelligent Systems, Robots and Devices for Healthcare and Rehabilitation)
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22 pages, 8855 KiB  
Article
Passive and Active Training Control of an Omnidirectional Mobile Exoskeleton Robot for Lower Limb Rehabilitation
by Suyang Yu, Congcong Liu, Changlong Ye and Rongtian Fu
Actuators 2024, 13(6), 202; https://doi.org/10.3390/act13060202 - 25 May 2024
Cited by 3 | Viewed by 1651
Abstract
As important auxiliary equipment, rehabilitation robots are widely used in rehabilitation treatment and daily life assistance. The rehabilitation robot proposed in this paper is mainly composed of an omnidirectional mobile platform module, a lower limb exoskeleton module, and a support module. According to [...] Read more.
As important auxiliary equipment, rehabilitation robots are widely used in rehabilitation treatment and daily life assistance. The rehabilitation robot proposed in this paper is mainly composed of an omnidirectional mobile platform module, a lower limb exoskeleton module, and a support module. According to the characteristics of the robot’s omnidirectional mobility and good stiffness, the overall kinematic model of the robot is established using the analytical method. Passive and active training control strategies for an omnidirectional mobile lower limb exoskeleton robot are proposed. The passive training mode facilitates the realization of the goal of walking guidance and assistance to the human lower limb. The active training mode can realize the cooperative movement between the robot and the human through the admittance controller and the tension sensor and enhance the active participation of the patient. In the simulation experiment, a set of optimal admittance parameters was obtained, and the parameters were substituted into the controller for the prototype experiment. The experimental results show that the admittance-controlled rehabilitation robot can perceive the patient’s motion intention and realize the two walking training modes. In summary, the passive and active training control strategies based on admittance control proposed in this paper achieve the expected purpose and effectively improve the patient’s active rehabilitation willingness and rehabilitation effect. Full article
(This article belongs to the Special Issue Intelligent Systems, Robots and Devices for Healthcare and Rehabilitation)
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Review

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22 pages, 296 KiB  
Review
Next-Generation Tools for Patient Care and Rehabilitation: A Review of Modern Innovations
by Faisal Mehmood, Nazish Mumtaz and Asif Mehmood
Actuators 2025, 14(3), 133; https://doi.org/10.3390/act14030133 - 8 Mar 2025
Viewed by 1101
Abstract
This review article explores the transformative impact of next-generation technologies on patient care and rehabilitation. The advent of next-generation tools has revolutionized the fields of patient care and rehabilitation, providing modern solutions to improve scientific outcomes and affected person studies. Powered through improvements [...] Read more.
This review article explores the transformative impact of next-generation technologies on patient care and rehabilitation. The advent of next-generation tools has revolutionized the fields of patient care and rehabilitation, providing modern solutions to improve scientific outcomes and affected person studies. Powered through improvements in artificial intelligence, robotics, and smart devices, these improvements are reshaping healthcare with the aid of improving therapeutic approaches and personalizing treatments. In the world of rehabilitation, robotic devices and assistive technology are supplying essential help for people with mobility impairments, promoting more independence and healing. Additionally, wearable technology and real-time tracking systems permit continuous fitness information monitoring, taking into consideration early analysis and extra effective, tailored interventions. In clinical settings, these modern-day innovations have automated diagnostics, enabled remote patient-monitoring, and brought virtual rehabilitation systems that expand the reach of clinical experts. This comprehensive review delves into the evolution, cutting-edge programs, and destiny potential of that equipment by examining their capability to deliver progressed care even while addressing growing needs for efficient healthcare solutions. Furthermore, this review explores the challenges related to their adoption, including ethical considerations, accessibility barriers, and the need for refined regulatory standards to ensure their safe and widespread use. Full article
(This article belongs to the Special Issue Intelligent Systems, Robots and Devices for Healthcare and Rehabilitation)
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