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A special issue of Micromachines (ISSN 2072-666X). This special issue belongs to the section "E：Engineering and Technology".

Deadline for manuscript submissions: closed (30 April 2023) | Viewed by 19998

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Special Issue Editors

Dr. Mohammad H. Rahman

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Guest Editor

BioRobotics Lab, Mechanical/Biomedical Engineering Department, University of Wisconsin-Milwaukee, Milwaukee, WI 53201, USA
Interests: upper limb orthosis; wearable robots; exoskeletorobots; nonlinear control; lower limb orthosis; rehabilitation; power augmentation; smart prosthetics
Special Issues, Collections and Topics in MDPI journals

Dr. Jawhar Ghommam

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Guest Editor

Department of Electrical and Computer Engineering, Sultan Qaboos University, Muscat, ‎Oman
Interests: nonlinear control; adaptive control; guidance; navigation and control; autonomous vehicles; multiagent systems; cooperative control; robotic applications
Special Issues, Collections and Topics in MDPI journals

Dr. Raouf Fareh

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Assistant Guest Editor

Electrical Engineering Department, University of Sharjah, University City, Sharjah 27272, United Arab Emirates
Interests: advanced control engineering; rigid and flexible manipulators; mobile robots; mobile manipulators; path planning; vision guided robotic systems

Special Issue Information

Dear Colleagues,

Around 15% of the world’s population live with some form of disability that significantly affects the quality of life of individuals. With the advancement of science and technology, assistive robots nowadays contribute to many areas, including human augmentation, rehabilitation, mobility assistance, and activities of daily living (ADL) assistance such as ambulating, feeding, dressing, taking medications, grooming, opening/closing a door/drawer, picking/placing an object, exercising, toileting, bathing, transferring, and socializing.

Assistive robots have enormous potential to reduce the dependency of individuals with disabilities on their caregivers/family caregivers and enhance their quality of life. Moreover, such robots can support and relieve caregivers from their work burden and injury resulting from handling people, especially transferring them. According to the most recent reports and data analyses, the global assistive robotics market is estimated to reach USD 25.16 billion in 2028, with a CAGR of 22.1 percent over the forecast period. Recent advances in artificial intelligence (AI) and robotics will likely fuel global revenue growth. Though significant advancement has been made in recent decades in the development and control of assistive robots, few such assistive robots exist to cover essential ADLs and mobility assistance. This Special Issue aims to gather cutting-edge research on assistive robotics and focus on the novel design, development, control, and evaluation of such assistive robots for ADL assistance, mobility assistance, rehabilitation, and power augmentation in different application settings, including home/clinical use, industry, and military applications.

Dr. Mohammad H. Rahman
Dr. Jawhar Ghommam
Dr. Raouf Fareh
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.

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Keywords

physically assistive robots, social robots, stoically assistive robots
exoskeleton
wearable robots
wheelchair mounted assistive robots
assistive robots
rehabilitation
activities of daily living assistance, assistive technology, assistive robotic manipulator
robotics
disability
wheelchair
human–machine interaction
therapeutic robots
elderly care
ADL
mobility assistance

Published Papers (10 papers)

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Research

16 pages, 3647 KiB

Open AccessArticle

Soft Pneumatic Muscles: Revolutionizing Human Assistive Devices with Geometric Design and Intelligent Control

by Mahmoud Elsamanty, Mohamed A. Hassaan, Mostafa Orban, Kai Guo, Hongbo Yang, Saber Abdrabbo and Mohamed Selmy

Micromachines 2023, 14(7), 1431; https://doi.org/10.3390/mi14071431 - 16 Jul 2023

Viewed by 2186

Abstract

Soft robotics, a recent advancement in robotics systems, distinguishes itself by utilizing soft and flexible materials like silicon rubber, prioritizing safety during human interaction, and excelling in handling complex or delicate objects. Soft pneumatic actuators, a prevalent type of soft robot, are the focus of this paper. A new geometrical parameter for soft artificial pneumatic muscles is introduced, enabling the prediction of actuation behavior using analytical models based on specific design parameters. The study investigated the impact of the chamber pitch parameter and actuation conditions on the deformation direction and internal stress of three tested soft pneumatic muscle (SPM) models. Simulation involved the modeling of hyperelastic materials using finite element analysis. Additionally, an artificial neural network (ANN) was employed to predict pressure values in three chambers at desired Cartesian positions. The trained ANN model demonstrated exceptional performance. It achieved high accuracy with training, validation, and testing residuals of 99.58%, 99.89%, and 99.79%, respectively. During the validation simulations and neural network results, the maximum errors in the x, y, and z coordinates were found to be 9.3%, 7.83%, and 8.8%, respectively. These results highlight the successful performance and efficacy of the trained ANN model in accurately predicting pressure values for the desired positions in the soft pneumatic muscles. Full article

(This article belongs to the Special Issue Assistive Robots)

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17 pages, 7839 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

Research on Intelligent Wheelchair Attitude-Based Adjustment Method Based on Action Intention Recognition

by Jianwei Cui, Zizheng Huang, Xiang Li, Linwei Cui, Yucheng Shang and Liyan Tong

Micromachines 2023, 14(6), 1265; https://doi.org/10.3390/mi14061265 - 17 Jun 2023

Cited by 2 | Viewed by 1301

Abstract

At present, research on intelligent wheelchairs mostly focuses on motion control, while research on attitude-based adjustment is relatively insufficient. The existing methods for adjusting wheelchair posture generally lack collaborative control and good human–machine collaboration. This article proposes an intelligent wheelchair posture-adjustment method based on action intention recognition by studying the relationship between the force changes on the contact surface between the human body and the wheelchair and the action intention. This method is applied to a multi-part adjustable electric wheelchair, which is equipped with multiple force sensors to collect pressure information from various parts of the passenger’s body. The upper level of the system converts the pressure data into the form of a pressure distribution map, extracts the shape features using the VIT deep learning model, identifies and classifies them, and ultimately identifies the action intentions of the passengers. Based on different action intentions, the electric actuator is controlled to adjust the wheelchair posture. After testing, this method can effectively collect the body pressure data of passengers, with an accuracy of over 95% for the three common intentions of lying down, sitting up, and standing up. The wheelchair can adjust its posture based on the recognition results. By adjusting the wheelchair posture through this method, users do not need to wear additional equipment and are less affected by the external environment. The target function can be achieved with simple learning, which has good human–machine collaboration and can solve the problem of some people having difficulty adjusting the wheelchair posture independently during wheelchair use. Full article

(This article belongs to the Special Issue Assistive Robots)

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11 pages, 4859 KiB

Open AccessArticle

Comparison of Robot-Assisted and Manual Cannula Insertion in Simulated Big-Bubble Deep Anterior Lamellar Keratoplasty

by Yinzheng Zhao, Anne-Marie Jablonka, Niklas A. Maierhofer, Hessam Roodaki, Abouzar Eslami, Mathias Maier, Mohammad Ali Nasseri and Daniel Zapp

Micromachines 2023, 14(6), 1261; https://doi.org/10.3390/mi14061261 - 16 Jun 2023

Cited by 1 | Viewed by 856

Abstract

This study aimed to compare the efficacy of robot-assisted and manual cannula insertion in simulated big-bubble deep anterior lamellar keratoplasty (DALK). Novice surgeons with no prior experience in performing DALK were trained to perform the procedure using manual or robot-assisted techniques. The results showed that both methods could generate an airtight tunnel in the porcine cornea, and result in successful generation of a deep stromal demarcation plane representing sufficient depth reached for big-bubble generation in most cases. However, the combination of intraoperative OCT and robotic assistance received a significant increase in the depth of achieved detachment in non-perforated cases, comprising a mean of 89% as opposed to 85% of the cornea in manual trials. This research suggests that robot-assisted DALK may offer certain advantages over manual techniques, particularly when used in conjunction with intraoperative OCT. Full article

(This article belongs to the Special Issue Assistive Robots)

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25 pages, 27207 KiB

Open AccessArticle

A Novel Multi-Modal Teleoperation of a Humanoid Assistive Robot with Real-Time Motion Mimic

by Julio C. Cerón, Md Samiul Haque Sunny, Brahim Brahmi, Luis M. Mendez, Raouf Fareh, Helal Uddin Ahmed and Mohammad H. Rahman

Micromachines 2023, 14(2), 461; https://doi.org/10.3390/mi14020461 - 16 Feb 2023

Cited by 2 | Viewed by 2107

Abstract

This research shows the development of a teleoperation system with an assistive robot (NAO) through a Kinect V2 sensor, a set of Meta Quest virtual reality glasses, and Nintendo Switch controllers (Joycons), with the use of the Robot Operating System (ROS) framework to implement the communication between devices. In this paper, two interchangeable operating models are proposed. An exclusive controller is used to control the robot’s movement to perform assignments that require long-distance travel. Another teleoperation protocol uses the skeleton joints information readings by the Kinect sensor, the orientation of the Meta Quest, and the button press and thumbstick movements of the Joycons to control the arm joints and head of the assistive robot, and its movement in a limited area. They give image feedback to the operator in the VR glasses in a first-person perspective and retrieve the user’s voice to be spoken by the assistive robot. Results are promising and can be used for educational and therapeutic purposes. Full article

(This article belongs to the Special Issue Assistive Robots)

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17 pages, 4095 KiB

Open AccessArticle

A Deep-Learning-Based Guidewire Compliant Control Method for the Endovascular Surgery Robot

by Chuqiao Lyu, Shuxiang Guo, Wei Zhou, Yonggan Yan, Chenguang Yang, Yue Wang and Fanxu Meng

Micromachines 2022, 13(12), 2237; https://doi.org/10.3390/mi13122237 - 16 Dec 2022

Cited by 6 | Viewed by 1889

Abstract

Endovascular surgery is a high-risk operation with limited vision and intractable guidewires. At present, endovascular surgery robot (ESR) systems based on force feedback liberates surgeons’ operation skills, but it lacks the ability to combine force perception with vision. In this study, a deep learning-based guidewire-compliant control method (GCCM) is proposed, which guides the robot to avoid surgical risks and improve the efficiency of guidewire operation. First, a deep learning-based model called GCCM-net is built to identify whether the guidewire tip collides with the vascular wall in real time. The experimental results in a vascular phantom show that the best accuracy of GCCM-net is 94.86 ± 0.31%. Second, a real-time operational risk classification method named GCCM-strategy is proposed. When the surgical risks occur, the GCCM-strategy uses the result of GCCM-net as damping and decreases the robot’s running speed through virtual resistance. Compared with force sensors, the robot with GCCM-strategy can alleviate the problem of force position asynchrony caused by the long and soft guidewires in real-time. Experiments run by five guidewire operators show that the GCCM-strategy can reduce the average operating force by 44.0% and shorten the average operating time by 24.6%; therefore the combination of vision and force based on deep learning plays a positive role in improving the operation efficiency in ESR. Full article

(This article belongs to the Special Issue Assistive Robots)

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23 pages, 6432 KiB

Open AccessArticle

Evaluation of Objective Functions for the Optimal Design of an Assistive Robot

by Javier Dario Sanjuan De Caro, Md Samiul Haque Sunny, Elias Muñoz, Jaime Hernandez, Armando Torres, Brahim Brahmi, Inga Wang, Jawhar Ghommam and Mohammad H. Rahman

Micromachines 2022, 13(12), 2206; https://doi.org/10.3390/mi13122206 - 13 Dec 2022

Cited by 3 | Viewed by 1240

Abstract

The number of individuals with upper or lower extremities dysfunction (ULED) has considerably increased in the past few decades, resulting in a high economic burden for their families and society. Individuals with ULEDs require assistive robots to fulfill all their activities of daily living (ADLs). However, a theory for the optimal design of assistive robots that reduces energy consumption while increasing the workspace is unavailable. Thus, this research presents an algorithm for the optimal link length selection of an assistive robot mounted on a wheelchair to minimize the torque demands of each joint while increasing the workspace coverage. For this purpose, this research developed a workspace to satisfy a list of 18 ADLs. Then, three torque indices from the literature were considered as performance measures to minimize; the three torque measures are the quadratic average torque (QAT), the weighted root square mean (WRMS), and the absolute sum of torques (AST). The proposed algorithm evaluates any of the three torque measures within the workspace, given the robot dimensions. This proposed algorithm acts as an objective function, which is optimized using a genetic algorithm for each torque measure. The results show that all tree torque measures are suitable criteria for assistance robot optimization. However, each torque measures yield different optimal results; in the case of the QAT optimization, it produces the least workspace with the minimum overall torques of all the joints. Contrarily, the WRMS and AST optimization yield similar results generating the maximum workspace coverage but with a greater overall torque of all joints. Thus, the selection between the three methods depends on the designer’s criteria. Based on the results, the presented methodology is a reliable tool for the optimal dimensioning of assistive robots. Full article

(This article belongs to the Special Issue Assistive Robots)

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18 pages, 12416 KiB

Open AccessArticle

Study on Flexible sEMG Acquisition System and Its Application in Muscle Strength Evaluation and Hand Rehabilitation

by Chang Liu, Jiuqiang Li, Senhao Zhang, Hongbo Yang and Kai Guo

Micromachines 2022, 13(12), 2047; https://doi.org/10.3390/mi13122047 - 22 Nov 2022

Cited by 5 | Viewed by 2025

Abstract

Wearable devices based on surface electromyography (sEMG) to detect muscle activity can be used to assess muscle strength with the development of hand rehabilitation applications. However, conventional acquisition devices are usually complicated to operate and poorly comfortable for more medical and scientific application scenarios. Here, we report a flexible sEMG acquisition system that combines a graphene-based flexible electrode with a signal acquisition flexible printed circuit (FPC) board. Our system utilizes a polydimethylsiloxane (PDMS) substrate combined with graphene transfer technology to develop a flexible sEMG sensor. The single-lead sEMG acquisition system was designed and the FPC board was fabricated considering the requirements of flexible bending and twisting. We demonstrate the above design approach and extend this flexible sEMG acquisition system to applications for assessing muscle strength and hand rehabilitation training using a long- and short-term memory network training model trained to predict muscle strength, with 98.81% accuracy in the test set. The device exhibited good flexion and comfort characteristics. In general, the ability to accurately and imperceptibly monitor surface electromyography (EMG) signals is critical for medical professionals and patients. Full article

(This article belongs to the Special Issue Assistive Robots)

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16 pages, 4443 KiB

Open AccessArticle

Novel Endovascular Interventional Surgical Robotic System Based on Biomimetic Manipulation

by Chao Song, Shibo Xia, Hao Zhang, Lei Zhang, Xiaoye Li, Kundong Wang and Qingsheng Lu

Micromachines 2022, 13(10), 1587; https://doi.org/10.3390/mi13101587 - 24 Sep 2022

Cited by 4 | Viewed by 2273

Abstract

Endovascular therapy has emerged as a crucial therapeutic method for treating vascular diseases. Endovascular surgical robots have been used to enhance endovascular therapy. However, to date, there are no universal endovascular surgical robots that support molds of different types of devices for treating vascular diseases. We developed a novel endovascular surgical robotic system that can independently navigate the intravascular region, advance and retract devices, and deploy stents. This robot has four features: (1) The bionic design of the robot can fully simulate the entire grasping process; (2) the V-shaped relay gripper waived the need to redesign special guidewires and catheters for continuous rotation; (3) the handles designed based on the feedback mechanism can simulate push resistance and reduce iatrogenic damage; and (4) the detachable design of the grippers can reduce cross-infection risk and medical costs. We verified its performance by demonstrating six different types of endovascular surgeries. Early evaluation of the novel endovascular robotic system demonstrated its practicability and safety in endovascular surgeries. Full article

(This article belongs to the Special Issue Assistive Robots)

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18 pages, 42084 KiB

Open AccessArticle

IoT Wheelchair Control System Based on Multi-Mode Sensing and Human-Machine Interaction

by Jianwei Cui, Linwei Cui, Zizheng Huang, Xiang Li and Fei Han

Micromachines 2022, 13(7), 1108; https://doi.org/10.3390/mi13071108 - 15 Jul 2022

Cited by 9 | Viewed by 2891

Abstract

Traditional wheelchairs are unable to actively sense the external environment during use and have a single control method. Therefore, this paper develops an intelligent IoT wheelchair with the three functions, as follows. (1) Occupant-wheelchair-environment multimode sensing: the PAJ7620 sensor is used to recognize gesture information, while GPS (Global Positioning System) and IMU (Inertial Measurement Unit) sensors are used to sense positioning, speed and postural information. In addition, Lidar, DHT11, and BH1750 sensors obtain environmental information such as road information, temperature and humidity and light intensity. (2) Fusion control scheme: a mobile control scheme based on rocker and gesture recognition, as well as a backrest and footrest lifting, lowering and movement control scheme based on Tencent Cloud and mobile APP (Application). (3) Human-machine interaction: the wheelchair is docked to Tencent IoT Explorer through ESP8266 WiFi module, using MQTT (Message Queuing Telemetry Transport) protocol is used to upload sensory data, while the wheelchair status can be viewed and controlled on the APP. The wheelchair designed in this paper can sense and report the status of the occupant, environment and wheelchair in real time, while the user can view the sensory data on the mobile APP and control the wheelchair using the rocker, gestures and APP. Full article

(This article belongs to the Special Issue Assistive Robots)

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19 pages, 7875 KiB

Open AccessArticle

Design and Development of a Smart IoT-Based Robotic Solution for Wrist Rehabilitation

by Yassine Bouteraa, Ismail Ben Abdallah, Khaled Alnowaiser, Md Rasedul Islam, Atef Ibrahim and Fayez Gebali

Micromachines 2022, 13(6), 973; https://doi.org/10.3390/mi13060973 - 19 Jun 2022

Cited by 10 | Viewed by 2190

Abstract

In this study, we present an IoT-based robot for wrist rehabilitation with a new protocol for determining the state of injured muscles as well as providing dynamic model parameters. In this model, the torque produced by the robot and the torque provided by the patient are determined and updated taking into consideration the constraints of fatigue. Indeed, in the proposed control architecture based on the EMG signal extraction, a fuzzy classifier was designed and implemented to estimate muscle fatigue. Based on this estimation, the patient’s torque is updated during the rehabilitation session. The first step of this protocol consists of calculating the subject-related parameters. This concerns axis offset, inertial parameters, passive stiffness, and passive damping. The second step is to determine the remaining component of the wrist model, including the interaction torque. The subject must perform the desired movements providing the torque necessary to move the robot in the desired direction. In this case, the robot applies a resistive torque to calculate the torque produced by the patient. After that, the protocol considers the patient and the robot as active and all exercises are performed accordingly. The developed robotics-based solution, including the proposed protocol, was tested on three subjects and showed promising results. Full article

(This article belongs to the Special Issue Assistive Robots)

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