Special Issue "Robotics in Healthcare: Automation, Sensing and Application"
Deadline for manuscript submissions: 31 October 2021.
Interests: medical robots; brain diseases; medical sensors
Global healthcare systems must deal with challenges related to population aging, the rise of the prevalence of chronic diseases, and the logical desire and need of patients for more personalized medicine and closer care. This situation puts pressure on the system and compromises sustainability due to budget constraints, and available resources are not enough to cover increasing demand.
The introduction of innovative technology, new service models, and digitalization is needed to ensure the adequate, sustainable, and efficient adaptation of our healthcare systems for them to be able to respond to actual and future health needs from a more demanding population.
Robotics combined with sensors, smart communication, artificial intelligence, and easy-to-use medical interfaces are promising solutions to overcome problems in many healthcare areas, such as care planning, procedure performance, diagnostics, infection control, medication management, and the improvement of patient experience or monitoring.
These technologies have the potential to dramatically transform the current concept of a healthcare system. Homes, schools, jobs, gyms, and any other environment can be part of the health system for those patients that could be remotely followed, outside of hospitals or clinics.
The deployment and integration of these technologies into digital healthcare systems, their logistics, and management procedures address a wide range of healthcare applications, for example, in patient care, prevention, diagnosis, or treatment surveillance. Regulations related to medical-device, ethical, data-protection, and cybersecurity issues are also key in the success of this novel concept.
In this Special Issue, possible contributions may include realistic clinical/medical applications of robots combined with sensors and other technologies (hardware and software) to transform current healthcare models and enhance personalized medicine.
Furthermore, contributions should demonstrate how the combination of digital and physical services or systems arises as a care solution for hospitals, clinics, primary care centers, rehabilitation centers, care homes, etc.
Novel contributions around the automation of any medical procedure including robots or sensor networks, data processing and analysis, and staff/patient–machine interfaces are welcome.
Prof. Dr. Cecilia Garcia
Prof. Dr. Changsheng Li
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 papers will be 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. Sensors is an international peer-reviewed open access semimonthly 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 2200 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.
- medical robots
- autonomous medical sensors
- intelligence systems
- aging and chronic diseases
The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.
Title: Artificial Intelligence Surgery: How Do We Get to Autonomous Actions in Surgery
Authors: Andrew Gumbs; Isabella Frigerio; Eyad Elyan; Gaya Spolverato; Elie Chouillard
1Centre Hospitalier Intercommunal de; POISSY/SAINT-GERMAIN-EN-LAYE, 10, Rue Champ de Gaillard, Poissy, France.
2School of Computing Science and Digital Media, Robert Gordon University, UK.
3Department of Hepato-Pancreato-Biliary Surgery, Pederzoli Hospital, Peschiera del Garda, Italy.
4Department of Surgical, Oncological and Gastroenterological Sciences, University of Padova, Padova, Italy.
5Centre Hospitalier Intercommunal de; POISSY/SAINT-GERMAIN-EN-LAYE, 10, Rue Champ de Gaillard, Poissy, France.
Abstract: Artificial intelligence surgery (AIS) is another term for autonomously acting machines that can do surgical gestures. According to the Gartner Hype Cycle we are languishing in the "Trough of Disillusionment," and the promise of autonomous surgery seems like a "pipe dream" for most modern day surgeons. However, the reality is that instances of autonomous actions in surgery already exist. Unfortunately, the reluctance of many laparoscopic surgeons to give up on haptics, or the sense of touch, is actually hindering progress in artificial intelligence surgery because of the refusal to embrace robotic telemanipulation technology. Machine Learning (ML), Deep Learning (DP), Natural Language Processing (NLP) and Computer Vision (CV) will ultimately be the path towards artificial intelligence surgery, but in the meantime, handheld robotics and complete robotic surgical systems are a necessary step that modern day minimally invasive surgeons will need to embrace to ultimately realize the dream of autonomously functioning robots in surgery. This manuscript will review the literature on ML, D, NLP and CV as it pertains to autonomous robotics, to attempt to ascertain the current obstacles and next steps necessary in the evolution towards AIS.
Title: Robot-assisted Gait Training Intensity is a Determinant of Functional Recovery Early after Stroke? A Pragmatic Observational Study of Clinical Care.
Authors: Luc Oscar Lissom1, MS, Nicola Lamberti2, MS, PhD, Fabio Manfredini2,3, MD, PhD, Susanna Lavezzi3, MD, Nino Basaglia3, MD, Sofia Straudi3, MD, PhD
Affiliation: 1Ferrara University, Doctoral Program in Translational Neurosciences and Neurotechnologies, Ferrara, Italy 2Department of Neuroscience and Rehabilitation, University of Ferrara, Ferrara, Italy 3Neuroscience and Rehabilitation Department, Ferrara University Hospital, Ferrara, Italy
Abstract: Background An early, high intensity rehabilitation seems to promote functional recovery in patients with stroke and robot-assisted gait training (RAGT) can be considered an a valuable option to deliver an high dose stepping activity. Objectives The aim of this pragmatic observational study was to identify the optimal dose and timing of RAGT that can lead to a favourable outcome in a sample of subacute stroke survivors. We hypothesized that patients who received an higher RAGT dose at an early stage of recovery will recover better than the others. Methods Subacute patients with stroke who underwent a RAGT within a multidisciplinary rehabilitation program were enrolled. A set of clinical (i.e. age, type of stroke, time since stroke) and rehabilitation stay outcome (Rehabilitation Length of Stay, RAGT number of sessions) were recorded to evaluate their impact on functional outcome measures by Functional Independence Measure (FIM) or Functional Ambulation Classification (FAC). Results We included 236 patients (62.73±11.82 year old), 38.44% were female, 59.32% were ischemic stroke. Hemorrhagic stroke patients were younger (p=0.019) received rehabilitation later (p=0.013) and had a lower FIM score at admission (p=0.005) especially the cognitive domain (p=0.001). Patients that received at least 14 RAGT sessions, had 15.83% more chance to be responders compared to those that receive less sessions (p=0.006). Similarly, younger patients (≤60 years) were more prone to be responders (+15.1%). Lastly, an early rehabilitation was found to be more efficient (+21.09%) in determining responsiveness (p <0.001). Becoming newly independent for gait, that refers to a FAC score ≥ 4, was related only with age (p=0.001). Conclusion A younger age (< 60 years), an early rehabilitation (< 6 weeks since stroke) and an higher RAGT dose (at least 14 sessions) were related with a favourable outcome in patients with subacute stroke. Key words: robot-assisted gait training, stroke, rehabilitation, functional independence
Title: The barriers of the assistive robotics market - What inhibits health innovation?
Authors: Gabriel Aguiar Noury; Andreas Walmsley; Ray Jones; Swen E Gaudl
Affiliation: School of Engineering, Computing and Mathematics, University of Plymouth
Abstract: Demographic changes are putting the healthcare industry under pressure. However, while other industries have been able to automate their operation through robotic and autonomous systems, the healthcare sector is still reluctant to change. What makes robotic innovation in healthcare so difficult? Despite offering more efficient, and consumer-friendly care, the assistive robotics market has lacked penetration. To answer this question, we have broken down the development process, taking a market transformation perspective. By interviewing assistive robotics companies at different business stages, this paper identifies new insight into the main barriers of the assistive robotics market that are inhibiting the sector. Their impact is analysed during the different stages of the development, exploring how these barriers affect the planning, conceptualisation and adoption of these solutions. This research presents a foundation for understanding innovation barriers that high-tech ventures face in the healthcare industry, and the need for public-policy measures to support these technology-based firms.
Title: EXPLORING A NOVEL MULTIPLE-QUERY RESISTIVE GRID-BASED PLANNING METHOD APPLIED TO HIGH DOF ROBOTIC MANIPULATORS
Authors: J. Huerta-Chua; G. Diaz-Arango; H. Vazquez-Leal; J. Flores-Mendez; M. Moreno-Moreno; R. C. Ambrosio-Lazaro; C. Hernandez-Mejia
Affiliation: Consejo Veracruzano de Investigacion Cientifica y Desarrollo Tecnologico (COVEICYDET), Av. Rafael Murillo Vidal No. 1735, Cuauhtemoc, 91069, Mexico, Facultad de Instrumentacion Electronica, Universidad Veracruzana, Cto. Gonzalo Aguirre Beltran S/N, Xalapa, Veracruz, 91000, Mexico; [email protected]
Abstract: Applicability of the path planning strategy on the robotic manipulator has been an exciting topic for researchers in the last decades due to its great demand in the industrial sector and its enormous potential development in surgical and pharmaceutical applications. Commonly, this task is performed with a human operator’s intervention by using a teach pendant device; thus, the operator selects a sequence of collision-free configurations from an initial position to a final position. If well it is a simple strategy, some drawbacks must be taken into account; first, the path’s success, length, and execution time depend on operator experience. Second, for most manipulator applications, the task is executed in a structured environment with few objects. Due to, for environments with many objects (obstacles), planning a collision-free trajectory becomes challenging. A technique capable of obtaining a free-collisions path based on a Resistive Grid Method (RGBPM) is exploring in this work, and the most important contributions fall on I) The strategy to solve and to model the configuration space of a redundant manipulator employing multiple dimensions resistive grids, II) A novel technique to recycle previous simulations and results of large sparse matrices to convert the RGBPM into a multiple-query planner, and III) The strategy to extend this planner to applications in high DOF industrial manipulators. Furthermore, the efficacy of obtaining free-collision paths for manipulators whit 3, 5, and 6 DOF on environments with dozens of circular and torus shapes obstacles is presented. The case studies results show the applicability of the novel proposed strategy to fast computing new collision-free paths using the first execution data. For which, each new query takes less than 0.2 seconds for 3-DOF manipulator in a configuration space free modeled by a 7291×7291 sparse matrix and less than thirty seconds for 5-DOF and 6-DOF manipulators in a configuration space free modeled by a 313958×313958 and 204087×204087 sparse matrices respectively. Finally, simulation results using the KUKA LBR iiwa 14R820 manipulator are presented to analyze the performance of the proposed RGBPM planner.
Title: Wearable and non-invasive multi-sensor system to measure the respiratory dynamics. Proof of concept in post-COVID-19 patients
Authors: Luís Silva; María Islán Moríñigo; Mariana Campos Costa; Cristina P. Santos; Julián Benito León; David Gómez-Andrés; Cecilia García Cena
Affiliation: University of Minho, Spain
Abstract: Nowadays, the measurement of respiratory dynamics is underrated at clinical setting and in the daily life of a subject and it still represents a challenge from technical and medical point of view. In this article we propose a concept to measure some of its parameters, such as the respiratory rate (RR), using four inertial sensors. Two different experiments were performed to validate the concept. We analyzed the most suitable placement of each sensor to measure those features and we studied the reliability of the system to measure abnormal parameters of respiratory (tachypnea, bradypnea and breath holding). Finally we measured post-COVID-19 patients, some of them with breath alterations after one year of the diagnosis. Experimental results show that the proposed system could be potentially used to measure the respiratory dynamics at clinical setting, however current technology available in the market is not suitable to measure the respiratory dynamics in the daily life. Moreover, while RR can be easily calculated by any sensor, other parameters need to be measured with a sensor in a particular position.
Title: Measurements and characterization of binocular eye movement alterations in post-COVID-19 patients
Authors: Mariana Campos Costa; Luís Silva; Julian Benito León; Cristina P. Santos; Roque Saltaren; David Gómez-Andrés; Cecilia García Cena
Affiliation: Portugal, Industrial Eletronics Department, University of Minho, Guimarães, Portugal2ETSIDI-Centre for Automation and Robotics from Universidad Politecnica de Madrid. Spain. C. Ronda deValencia 3, 28012. Madrid. Spain
Abstract: In this article, the results related to the measurements of the eye movements with a wearable gaze-tracker to post-COVID-19 patients are presented. This study is the first one that related alterations in the behaviour of the eye movements with subjective memory complaints reported by the included patients. The typical saccadic paradigm in gap condition for the visual stimulus was implemented. The saccadic paradigm includes visually guided saccades, memory guided saccades and antisaccades in horizontal axis. The duration of the test was around 5 minutes per volunteer. Two groups of people were recruited: in group G1 (n=9, healthy volunteers) the reliability of the measurement was validated and group G2 (n=9) was composed by post-COVID-19 patients with subjective memory complaints. Features such as latencies, success rates in memory saccades and antisaccade or blinks were computed. Our results reveal that post-COVID-19 patients have alteration in the performance of the eye movements compared with normal values reported by the literature.
Title: Robot-Assisted Autism Therapy (RAT). Criteria and Types of Experiments Using Anthropomorphic and Zoomorphic Robots. Review of the Research
Authors: Barbara Szymona; Marcin Maciejewski; Robert Karpiński; Kamil Jonak; Elżbieta Radzikowska-Buchner; Konrad Niderla; Anna Prokopiak
Affiliation: Department of Electronics and Information Technology, Faculty of Electrical Engineering and Computer Science, Lublin University of Technology, Nadbystrzycka 36, 20-618 Lublin, Poland
Abstract: Supporting the development of a child with autism is a multi-profile therapeutic work on disturbed areas, especially understanding and linguistic expression used in social communication and development of social contacts. Previous studies show that it is possible to perform some therapy using a robot. This article is a synthesis review of the literature on research with the use of robots in the therapy of children with the diagnosis of early childhood autism. The review includes scientific journals from 2005–2019. Using descriptors: ASD (Autism Spectrum Disorders), Social robots, Robot-based interventions, analysis of available research in PubMed, Scopus and Web of Science were made. The results showed that a robot seems to be a great tool that encourages contact and involvement in joint activities. The review of the literature indicates the potential value of the use of robots in the therapy of people with autism as a facilitator in social contacts. RAT can encourage child to talk or do exercises. In the second aspect (prompting during a conversation), a robot encourages eye contact and suggests possible answers, e.g. during free conversation with a peer. In the third aspect (teaching, entertainment) the robot could play with autistic children in games supporting the development of joint attention. These types of games stimulate the development of motor skills and orientation in the body schema. In future work, a validation test would be desirable to check whether children with ASD are able to do the same with a real person by learning distrust and cheating the robot.
Title: Robot-assisted gait training: rating of the level achieved
Authors: Andrea Scheidig; Horst-Michael Gross
Affiliation: Neuroinformatics and Cognitive Robotics Lab of Technische Universität Ilmenau, 98684 Ilmenau, Germany
Abstract: This paper presents the technological status of a robot assisted gait training under real clinical environment conditions. A successful rehabilitation after surgery in hip endoprosthetics comprises self-training of the lessons taught by physiotherapists. While doing this, immediate feedback to the patient about deviations from pysiological gait patterns during training is important. The therefore developed Socially Assistive Robot (SAR) employs task-specific, user-centered navigation and autonomous, real-time gait feature classification techniques to enrich the self-training through companionship and timely corrective feedback. The evaluation of the system was performed in regard to the view from technology, from different user groups and from an economic perspective. In this paper, the following questions are primarily considered. Does the level of technology achieved enable autonomous use in every day clinical practice? Has the gait pattern of patients who used additional robot-assisted gait self-training for several days been changed or improved compared to patients without this additional training? How does the use of a robot gait coach affect the motivation of the patient?
Title: Assist-as-needed exoskeleton for hand joint rehabilitation based on muscle effort detection
Authors: Jenny Carolina Castiblanco; Ivan Fernando Mondragon; Catalina Alvarado-Rojas; Julian D. Colorado
Affiliation: Pontificia Universidad Javeriana, Colombia
Abstract: Robotic-assisted systems have gained significant traction in post-stroke therapies to support rehabilitation, since these systems can provide high intensity and frequency treatment while allowing accurate motion-control over the patient's progress. In this paper, we tackle how to provide active support through a robotic-assisted exoskeleton by developing a novel closed-loop architecture that continually measures electromyographic signals (EMG), in order to adjust the assistance given by the exoskeleton. We used EMG signals acquired from 4 patients with post-stroke hand impairments for training machine-learning models used to characterize muscle effort by classifying 3 muscular condition levels based on contraction strength, co-activation and muscular activation measurements. The proposed closed-loop system takes into account the EMG muscle effort to modulate the exoskeleton velocity during the rehabilitation therapy. Experimental results indicate the maximum variation on velocity was 0.7mm/s, while the proposed control system effectively modulated the movements of the exoskeleton based on the EMG readings, keeping a reference tracking error <5%.
Title: Torque control of a parallel robot for shoulder rehabilitation
Authors: Paul Tucan
Affiliation: CESTER, Technical University of Cluj-Napoca, 400641 Cluj-Napoca, Romania
Abstract: Rehabilitation robots require a high degree of safety both for the patients and for the operators during the rehabilitation procedure. A way to assure the safety is a stable and intuitive control of the moving elements of the system combined with an external system of sensors able to monitor the position of every aspect of the rehabilitation system (operator, robot, and patient) and overcome in a certain measure all the events that may occur during the robotic rehabilitation procedure. In this paper is presented the torque control development of ASPIRE, a parallel robot for shoulder rehabilitation. First a full analysis regarding the components of the robotic system is carried on with the purpose of determining the dynamic behavior of the system, next, the torque control is implemented with respect to the previously obtained data. In the end several experimental tests are preformed using healthy subjects equipped with a series of biometric sensors with the purpose of validating the torque control system and in the same time to satisfy the degree of safety requested by the medical procedure.