EditorialRehabilitation Robotics and Systems

Rafael Morales ,1 Jose A. Somolinos,2 Antonio Fernandez-Caballero ,1

and Carlo Ferraresi3

1Escuela de Ingenieros Industriales de Albacete, Universidad de Castilla-La Mancha, 02071 Albacete, Spain2Escuela de Ingenieros Navales, Universidad Politecnica de Madrid, Madrid, Spain3Politecnico di Torino, Torino, Italy

Correspondence should be addressed to Rafael Morales; rafael.morales@uclm.es

Received 9 September 2018; Accepted 10 September 2018; Published 17 December 2018

Copyright © 2018 RafaelMorales et al.#is is an open access article distributed under the Creative Commons Attribution License,which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

1. Introduction

Development of novel engineering solutions that incorporaterobotic systems offers huge potential, as both assistive devicesand therapeutic aids, for patients with reduced motor and/orcognitive abilities. Indeed, such technologies are capable ofoutperforming existing therapeutic systems for improvingpatients’ achievable functional recovery. As a result, advancedengineering solutions for rehabilitation robotics have receiveda considerable amount of interest in recent years, from boththe academic community and the industrial sector. Emphasisis typically focused on the improvement of sensor systems,control engineering, computer vision, robotic mechanics,human-machine interfaces, modelling and simulation, in-built intelligence, and informatics, to meet the broad rangeof challenges posed during patient rehabilitation.

#is special issue is aimed at exhibiting the latest researchachievements, findings, and ideas in the field of rehabilitationrobotics and systems. Researchers were invited to contributewith their original research articles, as well as review articles,that summarize the most recent developments in the field ofrehabilitation robotics and systems.

Potential topics included but were not limited to thefollowing:

(i) Plasticity and motor-learning robotic devices(ii) Assistive and therapeutic robotic aids(iii) Upper and lower limb rehabilitation robotics(iv) Human-machine and brain-machine interfaces(v) Mobile, wearable, and prosthetic robotic devices(vi) Sensors, intelligent sensors, and sensor networks

(vii) Artificial intelligence-based rehabilitation systems(viii) Complex, nonlinear, and intelligent systems(ix) Vision, awareness, perception, and signal

processing(x) Sensor networks for precise motion control and

visual servoing(xi) Adaptive control, robust control, and active dis-

turbance rejection control(xii) Modelling and simulation for robotic re-

habilitation systems(xiii) Networked rehabilitation robotics(xiv) Intelligent automation of rehabilitation robotics(xv) Informational monitoring, control, and data fu-

sion for rehabilitation systems

2. The Papers

A total of 22 papers were submitted to this special issue.After peer review, finally 13 of them were accepted andpublished, covering a wide range of the topics proposed inthe call for papers.

#ree interesting papers are based on reviews of lit-erature papers on rehabilitation robotics and systems.Firstly, a work by G. Carpino et al. includes a meta-analysisof robot-mediated lower limbs rehabilitation for stroke-affected patients; it is aimed at evaluating the effectivenessof the robotic approach using wearable robots or opera-tional machines with respect to the conventional approach.#e primary assessed outcome is the patient’s ability toregain walking independence, whereas the secondary

HindawiJournal of Healthcare EngineeringVolume 2018, Article ID 5370127, 3 pageshttps://doi.org/10.1155/2018/5370127

outcome is the average walking speed. Also, E. D. Oña et al.conduct a systematic literature review to identify thecontribution of robotics to upper limb neurorehabilitation,highlighting its relationship with the rehabilitation cycle,and to clarify the prospective research directions in thedevelopment of more autonomous rehabilitation processes.In addition, a series of technical requirements that shouldbe considered when designing and implementing auton-omous robotic systems for rehabilitation are presented anddiscussed. Lastly, T. Eiammanussakul and V. Sangver-aphunsiri review the training activities that were realized byrehabilitation robots in the literature to offer insights intodeveloping a novel robot suitable for stroke rehabilitation.#e control system of the lower limb rehabilitation robot insitting position of the authors’ previous work is discussedin detail to demonstrate the behavior of the robot whiletraining a subject. A preliminary experiment is conductedon a healthy subject to show that the robot can performactive assistive exercises with various training activities andassist the subject to complete the training with a desiredlevel of assistance.

Next, other six papers are more directed towards theexperimental evaluation of rehabilitation mechanics. #us,W. Liang and Y. Yu propose the so-called manipulabilityinclusive principle (MIP) to evaluate the assistive mech-anism’s assistive feasibility and assistive effect through themanipulability comparison between the assisted limb andslave-active-assistive mechanism. #e optimization basedon MIP can make the assistive mechanism realize betterkinematical performance and assistance. Another paper byB. D. M. Chaparro-Rico et al. presents an experimentalcharacterization of NURSE, a device for arm motionguidance. #e laboratory setup and testing modes arepresented. Two exercises for the upper limb are used to testthe NURSE behavior. Trajectories and linear accelerationsare tested when the device performs the exercises with andwithout load. Z. Ray and E. D. Engeberg face the problem ofautonomously preventing grasped objects from slippingout of prosthetic hands for limb-absent people. #eir paperexplores a human-inspired grasp reflex controller forprosthetic hands to prevent slip of objects when they arerotated. #is human-inspired grasped object slip pre-vention controller is evaluated with six different objects inbenchtop tests and by 12 able-bodied subjects during re-alistic tasks of daily life. Moreover, in another article, M.Wu, M. R. Haque, and X. Shen present a new sit-to-stand(STS) control approach for powered lower limb prostheses,which can regulate the power delivery of the prostheticknee joint to obtain natural STS motion like that displayedby healthy subjects. Mimicking the dynamic behavior of theknee in both phases of the STS, a unified control structureprovides the desired control actions by combining animpedance function with a time-based ramp-up function.In addition, H. Guang et al. present an interactive upperlimb rehabilitation robot with a parallel mechanism and anisometric screen embedded in the platform to displaytrajectories. In the dynamic modeling for impedancecontrol, the effects of friction and inertia are reduced byintroducing the principle of virtual work and derivative of

the Jacobian matrix. To achieve the assist-as-needed im-pedance control for arbitrary trajectories, the strategybased on orthogonal deviations is proposed. Simulationsand experiments were performed to validate the dynamicmodeling and impedance control. Lastly, in a study by M.R. Afzal et al., a wearable system based on the reactionwheel is used to deliver light-touch-based balance bio-feedback on the subject’s back. #e system can sense torsotilt and, using reaction wheels, generates light-touch. Agroup of 7 healthy young individuals performed balancetasks under 12 trial combinations based on two conditionseach of standing stance and surface types and three ofbiofeedback device status.

A last group of four papers is directly focused demon-strating implementations for rehabilitation. A paper by J.Cantillo-Negrete et al. presents the implementation of abrain-computer interface system, coupled to a robotic handorthosis, driven by hand motor imagery of healthy subjectsand the paralyzed hand of stroke patients. A novel pro-cessing stage is designed using a bank of temporal filters, thecommon spatial patterns algorithm for feature extraction,and particle swarm optimization for feature selection. #esystem’s performance shows that it has potential to be usedfor hand rehabilitation of stroke patients. #e aim of anarticle by J. C. Castillo et al. is in the line of robotic therapiesin which a robot can perform partially or autonomously atherapy session, endowing a social robot with the ability ofassisting therapists in apraxia of speech rehabilitation ex-ercises. #e authors integrate computer vision and machine-learning techniques to detect themouth pose of the user, andon top of that, our social robot performs autonomously thedifferent steps of the therapy using multimodal interaction.#en, M. A. Padilla-Castañeda et al. introduce the devel-opment and evaluation of a robotic-assisted rehabilitationsystem as a new methodology of assisted physiotherapy inorthopedics. #e proposal consists of an enhanced end-effector haptic interface mounted in a passive mechanismfor allowing patients to perform upper limb exercising andintegrates virtual reality games conceived explicitly forassisting the treatment of the forearm after injuries at thewrist or elbow joints. #e authors design specific gamescenarios enriched by proprioceptive and haptic forcefeedback in three training modes: passive, active, andassisted exercising. Finally, in a study by E. Beretta et al., agroup of 18 children and adolescents with hemiplegia, animpairment due to acquired brain injuries, was enrolledand underwent intensive rehabilitation treatment in-cluding flank physical therapy and constrained-inducedmovement therapy or Armeo®Spring therapy. #e effectsof the treatments are assessed using clinical functionalscales and upper limb kinematic analysis during horizontaland vertical motor tasks. #e results of this study may be ofhelp to define the best rehabilitation treatment for eachpatient, depending on the goal, and may thus supportclinical decision.

Conflicts of Interest

#e editors declare that they have no conflicts of interest.

2 Journal of Healthcare Engineering

Acknowledgments

#is special issue would not be possible without the con-tributions of the authors who submitted their valuable pa-pers. We would like to thank all reviewers and editorial teamof Journal of Healthcare Engineering for their great work.Lastly, we acknowledge the financial support from SpanishMinisterio de Ciencia, Innovacion y Universidades andAgencia Estatal de Investigacion (AEI)/European RegionalDevelopment Fund (FEDER, EU) under DPI2016-80894-Rgrant.

Rafael MoralesJose A. Somolinos

Antonio Fernandez-CaballeroCarlo Ferraresi

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