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Exoskeletons in Rehabilitation Applications

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A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Physical Sensors".

Deadline for manuscript submissions: closed (31 May 2023) | Viewed by 14472

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Special Issue Editor

Dr. Sebastian Głowiński

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Guest Editor

Department of Mechatronics and Automatics, Koszalin Technical University, Koszalin, Poland
Interests: IMU; exoskeletons; sensors; kinematic; dynamic; human gait
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In recent years, extensive research has been conducted around the world on wearable robots and orthotic devices that support the movement of lower limbs. Wearable robots are devices that constitute a new class of articulated mechanical systems. These particular types of robots operate in close contact with a human user. They are worn by an operator like a suit, and their kinematic structure is similar to a human limb. Wearable robots are called exoskeletons. Exoskeleton robots integrate sensing, control, and other technologies and exhibit the characteristics of bionics, robotics, information and control science, medicine, and other interdisciplinary areas.

In this Special Issue, we collect research on the following topics, but not are limited to them:

The mechanical design and control of exoskeletons;
Human–robot integration;
Gait studying and measurement;
Rehabilitation exoskeleton robots;
Multimodal information fusion;
Algorithms for exoskeleton sensors and control;
Exoskeleton sensory system;
Applications in rehabilitation and operation assistance;
Inertial sensors, resistive sensors, capacitive sensors;
Flexible wearable sensor and e-skins;
Multifunctional sensor array;
Distributed sensory network.

Dr. Sebastian Głowiński
Guest Editor

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Keywords

exoskeletons
modeling, kinematic
dynamic
trajectory control
human–robot interaction
inertial measurement units

Published Papers (7 papers)

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Research

13 pages, 510 KiB

Open AccessArticle

Effect of Gait Speed on Trajectory Prediction Using Deep Learning Models for Exoskeleton Applications

by Rania Kolaghassi, Gianluca Marcelli and Konstantinos Sirlantzis

Sensors 2023, 23(12), 5687; https://doi.org/10.3390/s23125687 - 18 Jun 2023

Viewed by 1070

Abstract

Gait speed is an important biomechanical determinant of gait patterns, with joint kinematics being influenced by it. This study aims to explore the effectiveness of fully connected neural networks (FCNNs), with a potential application for exoskeleton control, in predicting gait trajectories at varying speeds (specifically, hip, knee, and ankle angles in the sagittal plane for both limbs). This study is based on a dataset from 22 healthy adults walking at 28 different speeds ranging from 0.5 to 1.85 m/s. Four FCNNs (a generalised-speed model, a low-speed model, a high-speed model, and a low-high-speed model) are evaluated to assess their predictive performance on gait speeds included in the training speed range and on speeds that have been excluded from it. The evaluation involves short-term (one-step-ahead) predictions and long-term (200-time-step) recursive predictions. The results show that the performance of the low- and high-speed models, measured using the mean absolute error (MAE), decreased by approximately 43.7% to 90.7% when tested on the excluded speeds. Meanwhile, when tested on the excluded medium speeds, the performance of the low-high-speed model improved by 2.8% for short-term predictions and 9.8% for long-term predictions. These findings suggest that FCNNs are capable of interpolating to speeds within the maximum and minimum training speed ranges, even if not explicitly trained on those speeds. However, their predictive performance decreases for gaits at speeds beyond or below the maximum and minimum training speed ranges. Full article

(This article belongs to the Special Issue Exoskeletons in Rehabilitation Applications)

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15 pages, 7666 KiB

Open AccessArticle

Bi-Planar Trajectory Tracking with a Novel 3DOF Cable Driven Lower Limb Rehabilitation Exoskeleton (C-LREX)

by Rajan Prasad, Marwan El-Rich, Mohammad I. Awad, Sunil K. Agrawal and Kinda Khalaf

Sensors 2023, 23(3), 1677; https://doi.org/10.3390/s23031677 - 3 Feb 2023

Cited by 4 | Viewed by 1814

Abstract

Although Cable-driven rehabilitation devices (CDRDs) have several advantages over traditional link-driven devices, including their light weight, ease of reconfiguration, and remote actuation, the majority of existing lower-limb CDRDs are limited to rehabilitation in the sagittal plane. In this work, we proposed a novel three degrees of freedom (DOF) lower limb model which accommodates hip abduction/adduction motion in the frontal plane, as well as knee and hip flexion/extension in the sagittal plane. The proposed model was employed to investigate the feasibility of using bi-planar cable routing to track a bi-planar reference healthy trajectory. Various possible routings of four cable configurations were selected and studied with the 3DOF model. The optimal locations of the hip cuffs were determined using optimization. When compared with the five-cable routing configuration, the four-cable routing produced higher joint forces, which motivated the future study of other potential cable routing configurations and their ability to track bi-planar motion. Full article

(This article belongs to the Special Issue Exoskeletons in Rehabilitation Applications)

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18 pages, 3753 KiB

Open AccessArticle

Soft Robots’ Dynamic Posture Perception Using Kirigami-Inspired Flexible Sensors with Porous Structures and Long Short-Term Memory (LSTM) Neural Networks

by Jing Shu, Junming Wang, Sanders Cheuk Yin Lau, Yujie Su, Kelvin Ho Lam Heung, Xiangqian Shi, Zheng Li and Raymond Kai-yu Tong

Sensors 2022, 22(20), 7705; https://doi.org/10.3390/s22207705 - 11 Oct 2022

Cited by 6 | Viewed by 2089

Abstract

Soft robots can create complicated structures and functions for rehabilitation. The posture perception of soft actuators is critical for performing closed-loop control for a precise location. It is essential to have a sensor with both soft and flexible characteristics that does not affect the movement of a soft actuator. This paper presents a novel end-to-end posture perception method that employs flexible sensors with kirigami-inspired structures and long short-term memory (LSTM) neural networks. The sensors were developed with conductive sponge materials. With one-step calibration from the sensor output, the posture of the soft actuator could be calculated by the LSTM network. The method was validated by attaching the developed sensors to a soft fiber-reinforced bending actuator. The results showed the accuracy of posture prediction of sponge sensors with three kirigami-inspired structures ranged from 0.91 to 0.97 in terms of

R^{2}

. The sponge sensors only generated a resistive torque value of 0.96 mNm at the maximum bending position when attached to a soft actuator, which would minimize the effect on actuator movement. The kirigami-inspired flexible sponge sensor could in future enhance soft robotic development. Full article

(This article belongs to the Special Issue Exoskeletons in Rehabilitation Applications)

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13 pages, 4365 KiB

Open AccessArticle

Biomechanical Analysis Suggests Myosuit Reduces Knee Extensor Demand during Level and Incline Gait

by Jaewook Kim, Yekwang Kim, Seonghyun Kang and Seung-Jong Kim

Sensors 2022, 22(16), 6127; https://doi.org/10.3390/s22166127 - 16 Aug 2022

Cited by 4 | Viewed by 1899

Abstract

An FDA-approved soft wearable robot, the Myosuit, which was designed to provide hip and knee extension torque has recently been commercialized. While studies have reported reductions in metabolic costs, increased gait speeds, and improvements in clinical test scores, a comprehensive analysis of electromyography (EMG) signals and joint kinematics is warranted because the recruitment of appropriate muscle groups during physiological movement patterns facilitates effective motor learning. Here, we compared the lower limb joint kinematics and EMG patterns while wearing the Myosuit with that of unassisted conditions when performing level overground and incline treadmill gait. The level overground gait sessions (seven healthy subjects) were performed at self-selected speeds and the incline treadmill gait sessions (four healthy subjects) were performed at 2, 3, 4, and 5 km/h. In order to evaluate how the user is assisted, we conducted a biomechanical analysis according to the three major gait tasks: weight acceptance (WA), single-limb support, and limb advancement. The results from the gait sessions suggest that Myosuit not only well preserves the users’ natural patterns, but more importantly reduce knee extensor demand during the WA phase for both level and incline gait. Full article

(This article belongs to the Special Issue Exoskeletons in Rehabilitation Applications)

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15 pages, 2887 KiB

Open AccessArticle

Relation between Cortical Activation and Effort during Robot-Mediated Walking in Healthy People: A Functional Near-Infrared Spectroscopy Neuroimaging Study (fNIRS)

by Julien Bonnal, Fanny Monnet, Ba-Thien Le, Ophélie Pila, Anne-Gaëlle Grosmaire, Canan Ozsancak, Christophe Duret and Pascal Auzou

Sensors 2022, 22(15), 5542; https://doi.org/10.3390/s22155542 - 25 Jul 2022

Cited by 5 | Viewed by 2466

Abstract

Force and effort are important components of a motor task that can impact rehabilitation effectiveness. However, few studies have evaluated the impact of these factors on cortical activation during gait. The purpose of the study was to investigate the relation between cortical activation and effort required during exoskeleton-mediated gait at different levels of physical assistance in healthy individuals. Twenty-four healthy participants walked 10 m with an exoskeleton that provided four levels of assistance: 100%, 50%, 0%, and 25% resistance. Functional near-infrared spectroscopy (fNIRS) was used to measure cerebral flow dynamics with a 20-channel (plus two reference channels) device that covered most cortical motor regions bilaterally. We measured changes in oxyhemoglobin (HbO₂) and deoxyhemoglobin (HbR). According to HbO₂ levels, cortical activation only differed slightly between the assisted conditions and rest. In contrast, bilateral and widespread cortical activation occurred during the two unassisted conditions (somatosensory, somatosensory association, primary motor, premotor, and supplementary motor cortices). A similar pattern was seen for HbR levels, with a smaller number of significant channels than for HbO₂. These results confirmed the hypothesis that there is a relation between cortical activation and level of effort during gait. This finding should help to optimize neurological rehabilitation strategies to drive neuroplasticity. Full article

(This article belongs to the Special Issue Exoskeletons in Rehabilitation Applications)

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12 pages, 5216 KiB

Open AccessArticle

Development of an Exoskeleton Platform of the Finger for Objective Patient Monitoring in Rehabilitation

by Nikolas Jakob Wilhelm, Sami Haddadin, Jan Josef Lang, Carina Micheler, Florian Hinterwimmer, Anselm Reiners, Rainer Burgkart and Claudio Glowalla

Sensors 2022, 22(13), 4804; https://doi.org/10.3390/s22134804 - 25 Jun 2022

Cited by 2 | Viewed by 1651

Abstract

This paper presents the application of an adaptive exoskeleton for finger rehabilitation. The system consists of a force-controlled exoskeleton of the finger and wireless coupling to a mobile application for the rehabilitation of complex regional pain syndrome (CRPS) patients. The exoskeleton has sensors for motion detection and force control as well as a wireless communication module. The proposed mobile application allows to interactively control the exoskeleton, store collected patient-specific data, and motivate the patient for therapy by means of gamification. The exoskeleton was applied to three CRPS patients over a period of six weeks. We present the design of the exoskeleton, the mobile application with its game content, and the results of the performed preliminary patient study. The exoskeleton system showed good applicability; recorded data can be used for objective therapy evaluation. Full article

(This article belongs to the Special Issue Exoskeletons in Rehabilitation Applications)

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17 pages, 4070 KiB

Open AccessArticle

Integration of Inertial Sensors in a Lower Limb Robotic Exoskeleton

by John Calle-Siguencia, Mauro Callejas-Cuervo and Sebastián García-Reino

Sensors 2022, 22(12), 4559; https://doi.org/10.3390/s22124559 - 16 Jun 2022

Cited by 4 | Viewed by 2157

Abstract

Motion assistance exoskeletons are designed to support the joint movement of people who perform repetitive tasks that cause damage to their health. To guarantee motion accompaniment, the integration between sensors and actuators should ensure a near-zero delay between the signal acquisition and the actuator response. This study presents the integration of a platform based on Imocap-GIS inertial sensors, with a motion assistance exoskeleton that generates joint movement by means of Maxon motors and Harmonic drive reducers, where a near zero-lag is required for the gait accompaniment to be correct. The Imocap-GIS sensors acquire positional data from the user’s lower limbs and send the information through the UDP protocol to the CompactRio system, which constitutes a high-performance controller. These data are processed by the card and subsequently a control signal is sent to the motors that move the exoskeleton joints. Simulations of the proposed controller performance were conducted. The experimental results show that the motion accompaniment exhibits a delay of between 20 and 30 ms, and consequently, it may be stated that the integration between the exoskeleton and the sensors achieves a high efficiency. In this work, the integration between inertial sensors and an exoskeleton prototype has been proposed, where it is evident that the integration met the initial objective. In addition, the integration between the exoskeleton and IMOCAP is among the highest efficiency ranges of similar systems that are currently being developed, and the response lag that was obtained could be improved by means of the incorporation of complementary systems. Full article

(This article belongs to the Special Issue Exoskeletons in Rehabilitation Applications)

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