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15 pages, 1808 KiB

Open AccessArticle

Autonomous Exercise Generator for Upper Extremity Rehabilitation: A Fuzzy-Logic-Based Approach

by Tanjulee Siddique, Raouf Fareh, Mahmoud Abdallah, Zaina Ahmed and Mohammad Habibur Rahman

Micromachines 2022, 13(6), 842; https://doi.org/10.3390/mi13060842 - 28 May 2022

Cited by 8 | Viewed by 2079

Abstract

In this paper, an autonomous exercise generation system based of fuzzy logic approach is presented. This work attempts to close a gap in the design of a completely autonomous robotic rehabilitation system that can recommend exercises to patients based on their data, such [...] Read more.

In this paper, an autonomous exercise generation system based of fuzzy logic approach is presented. This work attempts to close a gap in the design of a completely autonomous robotic rehabilitation system that can recommend exercises to patients based on their data, such as shoulder range of motion (ROM) and muscle strength, from a pre-set library of exercises. The input parameters are fed into a system that uses Mamdani-style fuzzy logic rules to process them. In medical applications, the rationale behind decision making is a sophisticated process that involves a certain amount of uncertainty and ambiguity. In this instance, a fuzzy-logic-based system emerges as a viable option for dealing with the uncertainty. The system’s rules have been reviewed by a therapist to ensure that it adheres to the relevant healthcare standards. Moreover, the system has been tested with a series of test data and the results obtained ensures the proposed idea’s feasibility. Full article

(This article belongs to the Special Issue Wearable Robotics)

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12 pages, 4487 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

Wireless Control Combining Myoelectric Signal and Human Body Communication for Wearable Robots

by Taisuke Iguchi, Ikuma Kondo and Jianqing Wang

Micromachines 2022, 13(2), 290; https://doi.org/10.3390/mi13020290 - 12 Feb 2022

Cited by 2 | Viewed by 2176

Abstract

In this study, a communication module based on human body communication was developed to wirelessly control a wearable robot hand based on myoelectric signals. The communication module adopts 10–60 MHz band and an impulse radio multi-pulse position modulation method to achieve low transmission [...] Read more.

In this study, a communication module based on human body communication was developed to wirelessly control a wearable robot hand based on myoelectric signals. The communication module adopts 10–60 MHz band and an impulse radio multi-pulse position modulation method to achieve low transmission loss and high data rate. A technique to reduce the module size was developed by sharing the myoelectric signal detection electrode and transmitting electrode, and three receiving electrode structures were investigated to improve signal transmission performance. As a result, the developed communication module provides a packet detection rate of 100% and a bit error rate of less than 10

^{- 6}

up to at least 110 cm along the arm, and a wearable robot hand was demonstrated to be properly controlled based on a human subject’s myoelectric signals. Full article

(This article belongs to the Special Issue Wearable Robotics)

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15 pages, 4361 KiB

Open AccessArticle

Design of an Effective Prosthetic Hand System for Adaptive Grasping with the Control of Myoelectric Pattern Recognition Approach

by Yanchao Wang, Ye Tian, Haotian She, Yinlai Jiang, Hiroshi Yokoi and Yunhui Liu

Micromachines 2022, 13(2), 219; https://doi.org/10.3390/mi13020219 - 29 Jan 2022

Cited by 16 | Viewed by 10105

Abstract

In this paper, we develop a prosthetic bionic hand system to realize adaptive gripping with two closed-loop control loops by using a linear discriminant analysis algorithm (LDA). The prosthetic hand contains five fingers and each finger is driven by a linear servo motor. [...] Read more.

In this paper, we develop a prosthetic bionic hand system to realize adaptive gripping with two closed-loop control loops by using a linear discriminant analysis algorithm (LDA). The prosthetic hand contains five fingers and each finger is driven by a linear servo motor. When grasping objects, four fingers except the thumb would adjust automatically and bend with an appropriate gesture, while the thumb is stretched and bent by the linear servo motor. Since the change of the surface electromechanical signal (sEMG) occurs before human movement, the recognition of sEMG signal with LDA algorithm can help to obtain people’s action intention in advance, and then timely send control instructions to assist people to grasp. For activity intention recognition, we extract three features, Variance (VAR), Root Mean Square (RMS) and Minimum (MIN) for recognition. As the results show, it can achieve an average accuracy of 96.59%. This helps our system perform well for disabilities to grasp objects of different sizes and shapes adaptively. Finally, a test of the people with disabilities grasping 15 objects of different sizes and shapes was carried out and achieved good experimental results. Full article

(This article belongs to the Special Issue Wearable Robotics)

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16 pages, 31917 KiB

Open AccessArticle

Embedded Machine Learning Using a Multi-Thread Algorithm on a Raspberry Pi Platform to Improve Prosthetic Hand Performance

by Triwiyanto Triwiyanto, Wahyu Caesarendra, Mauridhi Hery Purnomo, Maciej Sułowicz, I Dewa Gede Hari Wisana, Dyah Titisari, Lamidi Lamidi and Rismayani Rismayani

Micromachines 2022, 13(2), 191; https://doi.org/10.3390/mi13020191 - 26 Jan 2022

Cited by 15 | Viewed by 4330

Abstract

High accuracy and a real-time system are priorities in the development of a prosthetic hand. This study aimed to develop and evaluate a real-time embedded time-domain feature extraction and machine learning on a system on chip (SoC) Raspberry platform using a multi-thread algorithm [...] Read more.

High accuracy and a real-time system are priorities in the development of a prosthetic hand. This study aimed to develop and evaluate a real-time embedded time-domain feature extraction and machine learning on a system on chip (SoC) Raspberry platform using a multi-thread algorithm to operate a prosthetic hand device. The contribution of this study is that the implementation of the multi-thread in the pattern recognition improves the accuracy and decreases the computation time in the SoC. In this study, ten healthy volunteers were involved. The EMG signal was collected by using two dry electrodes placed on the wrist flexor and wrist extensor muscles. To reduce the complexity, four time-domain features were applied to extract the EMG signal. Furthermore, these features were used as the input of the machine learning. The machine learning evaluated in this study were k-nearest neighbor (k-NN), Naive Bayes (NB), decision tree (DT), and support vector machine (SVM). In the SoC implementation, the data acquisition, feature extraction, machine learning, and motor control process were implemented using a multi-thread algorithm. After the evaluation, the result showed that the pairing of the MAV feature and machine learning DT resulted in higher accuracy among other combinations (98.41%) with a computation time of ~1 ms. The implementation of the multi-thread algorithm in the pattern recognition system resulted in significant impact on the time processing. Full article

(This article belongs to the Special Issue Wearable Robotics)

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15 pages, 1181 KiB

Open AccessArticle

A Portable Waist-Loaded Soft Exosuit for Hip Flexion Assistance with Running

by Lingxing Chen, Chunjie Chen, Xin Ye, Zhuo Wang, Yao Liu, Wujing Cao, Shaocong Chen and Xinyu Wu

Micromachines 2022, 13(2), 157; https://doi.org/10.3390/mi13020157 - 21 Jan 2022

Cited by 4 | Viewed by 3766

Abstract

The soft exosuit is an emerging robotics, which has been proven to considerably reduce the metabolic consumption of human walking and running. However, compared to walking, relatively few soft exosuits have been studied for running. Many soft exosuits used for running are worn [...] Read more.

The soft exosuit is an emerging robotics, which has been proven to considerably reduce the metabolic consumption of human walking and running. However, compared to walking, relatively few soft exosuits have been studied for running. Many soft exosuits used for running are worn on the back and with a heavy weight load, which may cause instability while running and potentially increase metabolic consumption. Therefore, reducing the weight of the whole soft exosuit system as much as possible and keeping the soft exosuit close to the center of gravity, may improve running stability and further reduce metabolic consumption. In this paper, a portable waist-loaded soft exosuit, the weight of which is almost entirely concentrated at the waist, is shown to assist hip flexion during running, and justifies choosing to assist hip flexion while running. As indicated by the experiments of motion flexibility, wearing the waist-loaded soft exosuit can assist in performing many common and complex motions. The metabolic consumption experiments proved that the portable waist-loaded soft exosuit reduces the metabolic consumption rate of wearers when jogging on the treadmill at 6 km per hour by 7.79% compared with locomotion without the exosuit. Additionally, at the running speed of 8 km per hour, using the waist-loaded soft exosuit can reduce metabolic consumption rate by 4.74%. Similarly, at the running speed of 10 km per hour, it also can be reduced by 6.12%. It is demonstrated that assisting hip flexion for running is also a reasonable method, and wearing the waist-loaded soft exosuit can keep human motion flexibility and reduce metabolic consumption. Full article

(This article belongs to the Special Issue Wearable Robotics)

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13 pages, 3305 KiB

Open AccessArticle

Soft Ionic Pressure Sensor with Aloe Vera Gel for Low-Pressure Applications

by Vishnu Sujeesh, Godwin Ponraj and Hongliang Ren

Micromachines 2022, 13(2), 146; https://doi.org/10.3390/mi13020146 - 18 Jan 2022

Cited by 6 | Viewed by 2333

Abstract

Ionic pressure sensors are made of ionic compounds suspended in a suitable solvent mixture. When external pressure is exerted on them, it is reflected as a change in electrical parameters due to physical deformation and a redistribution of ions within the sensing medium. [...] Read more.

Ionic pressure sensors are made of ionic compounds suspended in a suitable solvent mixture. When external pressure is exerted on them, it is reflected as a change in electrical parameters due to physical deformation and a redistribution of ions within the sensing medium. Variations in the composition and material of the sensing medium result in different pressure sensors with varying operating ranges and sensitivity. This work presents the design and fabrication procedure of a novel soft-pressure sensor for a very low-pressure range (<20 mm Hg) using Aloe vera gel and Glycerin as the solvent for the ionic sensing medium. We also provide a comparative study on the performance of sensor prototypes with varying solvent concentrations and geometric parameters based on a series of characterization experiments. Maximum sensitivity (

7.498 \times 10^{- 4} Ω / mmHg

) was observed when using 40% glycerin in the sensing medium, filled in a toroidal geometry with outer and inner channel diameters of 8 mm and 7 mm, respectively. The proposed sensor is entirely soft and can be designed to conform to any desired geometry. Full article

(This article belongs to the Special Issue Wearable Robotics)

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24 pages, 25265 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

Flexohand: A Hybrid Exoskeleton-Based Novel Hand Rehabilitation Device

by Tanvir Ahmed, Md Assad-Uz-Zaman, Md Rasedul Islam, Drew Gottheardt, Erin McGonigle, Brahim Brahmi and Mohammad Habibur Rahman

Micromachines 2021, 12(11), 1274; https://doi.org/10.3390/mi12111274 - 20 Oct 2021

Cited by 12 | Viewed by 4409

Abstract

Home-based hand rehabilitation has excellent potential as it may reduce patient dropouts due to travel, transportation, and insurance constraints. Being able to perform exercises precisely, accurately, and in a repetitive manner, robot-aided portable devices have gained much traction these days in hand rehabilitation. [...] Read more.

Home-based hand rehabilitation has excellent potential as it may reduce patient dropouts due to travel, transportation, and insurance constraints. Being able to perform exercises precisely, accurately, and in a repetitive manner, robot-aided portable devices have gained much traction these days in hand rehabilitation. However, existing devices fall short in allowing some key natural movements, which are crucial to achieving full potential motion in performing activities of daily living. Firstly, existing exoskeleton type devices often restrict or suffer from uncontrolled wrist and forearm movement during finger exercises due to their setup of actuation and transmission mechanism. Secondly, they restrict passive metacarpophalangeal (MCP) abduction–adduction during MCP flexion–extension motion. Lastly, though a few of them can provide isolated finger ROM, none of them can offer isolated joint motion as per therapeutic need. All these natural movements are crucial for effective robot-aided finger rehabilitation. To bridge these gaps, in this research, a novel lightweight robotic device, namely “Flexohand”, has been developed for hand rehabilitation. A novel compliant mechanism has been developed and included in Flexohand to compensate for the passive movement of MCP abduction–adduction. The isolated and composite digit joint flexion–extension has been achieved by integrating a combination of sliding locks for IP joints and a wire locking system for finger MCP joints. Besides, the intuitive design of Flexohand inherently allows wrist joint movement during hand digit exercises. Experiments of passive exercises involving isolated joint motion, composite joint motions of individual fingers, and isolated joint motion of multiple fingers have been conducted to validate the functionality of the developed device. The experimental results show that Flexohand addresses the limitations of existing robot-aided hand rehabilitation devices. Full article

(This article belongs to the Special Issue Wearable Robotics)

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16 pages, 994 KiB

Open AccessArticle

Design and Development of a Wearable Assistive Device Integrating a Fuzzy Decision Support System for Blind and Visually Impaired People

by Yassine Bouteraa

Micromachines 2021, 12(9), 1082; https://doi.org/10.3390/mi12091082 - 7 Sep 2021

Cited by 21 | Viewed by 4297

Abstract

In this article, a new design of a wearable navigation support system for blind and visually impaired people (BVIP) is proposed. The proposed navigation system relies primarily on sensors, real-time processing boards, a fuzzy logic-based decision support system, and a user interface. It [...] Read more.

In this article, a new design of a wearable navigation support system for blind and visually impaired people (BVIP) is proposed. The proposed navigation system relies primarily on sensors, real-time processing boards, a fuzzy logic-based decision support system, and a user interface. It uses sensor data as inputs and provides the desired safety orientation to the BVIP. The user is informed about the decision based on a mixed voice–haptic interface. The navigation aid system contains two wearable obstacle detection systems managed by an embedded controller. The control system adopts the Robot Operating System (ROS) architecture supported by the Beagle Bone Black master board that meets the real-time constraints. The data acquisition and obstacle avoidance are carried out by several nodes managed by the ROS to finally deliver a mixed haptic–voice message for guidance of the BVIP. A fuzzy logic-based decision support system was implemented to help BVIP to choose a safe direction. The system has been applied to blindfolded persons and visually impaired persons. Both types of users found the system promising and pointed out its potential to become a good navigation aid in the future. Full article

(This article belongs to the Special Issue Wearable Robotics)

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19 pages, 8326 KiB

Open AccessArticle

A Vacuum-Powered Artificial Muscle Designed for Infant Rehabilitation

by Mijaíl Jaén Mendoza, Samuel Dutra Gollob, Diego Lavado, Bon Ho Brandon Koo, Segundo Cruz, Ellen T. Roche and Emir A. Vela

Micromachines 2021, 12(8), 971; https://doi.org/10.3390/mi12080971 - 16 Aug 2021

Cited by 13 | Viewed by 3939

Abstract

The majority of soft pneumatic actuators for rehabilitation exercises have been designed for adult users. Specifically, there is a paucity of soft rehabilitative devices designed for infants with upper and lower limb motor disabilities. We present a low-profile vacuum-powered artificial muscle (LP-VPAM) with [...] Read more.

The majority of soft pneumatic actuators for rehabilitation exercises have been designed for adult users. Specifically, there is a paucity of soft rehabilitative devices designed for infants with upper and lower limb motor disabilities. We present a low-profile vacuum-powered artificial muscle (LP-VPAM) with dimensions suitable for infants. The actuator produced a maximum force of 26 N at vacuum pressures of −40 kPa. When implemented in an experimental model of an infant leg in an antagonistic-agonist configuration to measure resultant knee flexion, the actuator generated knee flexion angles of 43° and 61° in the prone and side-lying position, respectively. Full article

(This article belongs to the Special Issue Wearable Robotics)

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30 pages, 12508 KiB

Open AccessArticle

Design and Development of an Upper Limb Rehabilitative Robot with Dual Functionality

by Md Rasedul Islam, Md Assad-Uz-Zaman, Brahim Brahmi, Yassine Bouteraa, Inga Wang and Mohammad Habibur Rahman

Micromachines 2021, 12(8), 870; https://doi.org/10.3390/mi12080870 - 24 Jul 2021

Cited by 34 | Viewed by 5161

Abstract

The design of an upper limb rehabilitation robot for post-stroke patients is considered a benchmark problem regarding improving functionality and ensuring better human–robot interaction (HRI). Existing upper limb robots perform either joint-based exercises (exoskeleton-type functionality) or end-point exercises (end-effector-type functionality). Patients may need [...] Read more.

The design of an upper limb rehabilitation robot for post-stroke patients is considered a benchmark problem regarding improving functionality and ensuring better human–robot interaction (HRI). Existing upper limb robots perform either joint-based exercises (exoskeleton-type functionality) or end-point exercises (end-effector-type functionality). Patients may need both kinds of exercises, depending on the type, level, and degree of impairments. This work focused on designing and developing a seven-degrees-of-freedom (DoFs) upper-limb rehabilitation exoskeleton called ‘u-Rob’ that functions as both exoskeleton and end-effector types device. Furthermore, HRI can be improved by monitoring the interaction forces between the robot and the wearer. Existing upper limb robots lack the ability to monitor interaction forces during passive rehabilitation exercises; measuring upper arm forces is also absent in the existing devices. This research work aimed to develop an innovative sensorized upper arm cuff to measure the wearer’s interaction forces in the upper arm. A PID control technique was implemented for both joint-based and end-point exercises. The experimental results validated both types of functionality of the developed robot. Full article

(This article belongs to the Special Issue Wearable Robotics)

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20 pages, 8952 KiB

Open AccessArticle

Development of a Low-Cost Wearable Data Glove for Capturing Finger Joint Angles

by Changcheng Wu, Keer Wang, Qingqing Cao, Fei Fei, Dehua Yang, Xiong Lu, Baoguo Xu, Hong Zeng and Aiguo Song

Micromachines 2021, 12(7), 771; https://doi.org/10.3390/mi12070771 - 30 Jun 2021

Cited by 14 | Viewed by 3229

Abstract

Capturing finger joint angle information has important applications in human–computer interaction and hand function evaluation. In this paper, a novel wearable data glove is proposed for capturing finger joint angles. A sensing unit based on a grating strip and an optical detector is [...] Read more.

Capturing finger joint angle information has important applications in human–computer interaction and hand function evaluation. In this paper, a novel wearable data glove is proposed for capturing finger joint angles. A sensing unit based on a grating strip and an optical detector is specially designed for finger joint angle measurement. To measure the angles of finger joints, 14 sensing units are arranged on the back of the glove. There is a sensing unit on the back of each of the middle phalange, proximal phalange, and metacarpal of each finger, except for the thumb. For the thumb, two sensing units are distributed on the back of the proximal phalange and metacarpal, respectively. Sensing unit response tests and calibration experiments are conducted to evaluate the feasibility of using the designed sensing unit for finger joint measurement. Experimental results of calibration show that the comprehensive precision of measuring the joint angle of a wooden finger model is 1.67%. Grasping tests and static digital gesture recognition experiments are conducted to evaluate the performance of the designed glove. We achieve a recognition accuracy of 99% by using the designed glove and a generalized regression neural network (GRNN). These preliminary experimental results indicate that the designed data glove is effective in capturing finger joint angles. Full article

(This article belongs to the Special Issue Wearable Robotics)

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19 pages, 7590 KiB

Open AccessArticle

Development and Evaluation of an Adaptive Multi-DOF Finger with Mechanical-Sensor Integrated for Prosthetic Hand

by Changcheng Wu, Tianci Song, Zilong Wu, Qingqing Cao, Fei Fei, Dehua Yang, Baoguo Xu and Aiguo Song

Micromachines 2021, 12(1), 33; https://doi.org/10.3390/mi12010033 - 30 Dec 2020

Cited by 7 | Viewed by 3131

Abstract

To realize the adaptive grasping of objects with diverse shapes and to capture the joint angles of the finger, a multi degree of freedom (DOF) adaptive finger for prosthetic hand is proposed in this paper. The fingers are designed with three joints. The [...] Read more.

To realize the adaptive grasping of objects with diverse shapes and to capture the joint angles of the finger, a multi degree of freedom (DOF) adaptive finger for prosthetic hand is proposed in this paper. The fingers are designed with three joints. The maximum rotation angle of the finger joints is 90°. The angle at which the finger joints bend can be captured. Firstly, the prototype design, forward kinematics and force analysis of phalanges are described in detail. In order to achieve an adaptive motion pattern similar to that of the human hand, this paper investigates the optimization of the torsion spring stiffness coefficient so that the metacarpophalangeal (MCP) joints, proximal interphalangeal (PIP) joints, and distal interphalangeal (DIP) joints of the bionic finger meet a motion ratio of approximately 3:3:1. Then, in order to realize the joint angle measurement in the process of grasping an object, the mechanical-sensor integrated finger joint is designed, and the composition, angle measurement principle and measurement circuit are introduced in detail. Finally, joint angle measurement, movement law evaluation and object grasping experiments are performed to verify the validity of the designed finger. The experimental results show that the root-mean-square (RMS) of the DIP, PIP and MCP angle measurement errors are 0.36°, 0.59° and 0.32°, respectively. The designed finger is able to grasp objects with different shapes stably. Full article

(This article belongs to the Special Issue Wearable Robotics)

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13 pages, 3719 KiB

Open AccessFeature PaperEditor’s ChoiceTechnical Note

Design and Massaging Force Analysis of Wearable Flexible Single Point Massager Imitating Traditional Chinese Medicine

by Zhou Zhou, Yixuan Wang, Chenjun Zhang, Ao Meng, Bingshan Hu and Hongliu Yu

Micromachines 2022, 13(3), 370; https://doi.org/10.3390/mi13030370 - 26 Feb 2022

Cited by 3 | Viewed by 3692

Abstract

In the theory of traditional Chinese medicine, acupoints refer to special points and areas on the meridian line of the human body. Traditional Chinese medicine believes that the application of unique techniques such as pressing, kneading, rubbing, pushing, and patting to acupoints or [...] Read more.

In the theory of traditional Chinese medicine, acupoints refer to special points and areas on the meridian line of the human body. Traditional Chinese medicine believes that the application of unique techniques such as pressing, kneading, rubbing, pushing, and patting to acupoints or massage with the help of specific tools has the effects of promoting blood circulation, dredging meridians, and eliminating fatigue. At present, most automatic massage devices are for large-area massage of the trunk, and few are specifically for acupoint massage of the limbs. First, this paper analyzes the characteristics of traditional Chinese medical acupoint massage and then obtains the design index of an automatic acupoint massage device. After that, based on the principle of a series elastic actuating mechanism, a flexible uni-acupoint massage device and control system, imitating the acupoint massage technique of traditional Chinese medicine, were designed. In order to analyze the massage force of the massage device, the man–machine contact dynamic model of the massage device was established, and the force of the massage device was simulated and analyzed. Finally, an experimental platform was built to verify the massage force and massage process of the massage device. The experimental results show that the massage device designed in this paper meets the indexes of traditional Chinese medical massage, in terms of the massage process and massage force, and verify the rationality of the design. Full article

(This article belongs to the Special Issue Wearable Robotics)

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