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Robotics
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Robots and Artificial Intelligence for a Better Future of Health...
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Robots and Artificial Intelligence for a Better Future of Health Care

A special issue of Robotics (ISSN 2218-6581). This special issue belongs to the section "Medical Robotics and Service Robotics".

Deadline for manuscript submissions: closed (30 April 2024) | Viewed by 8412

Special Issue Editor

Dr. Sylwia Łukasik

E-Mail Website
Guest Editor
Institute of Human Biology and Evolution, Faculty of Biology, Adam Mickiewicz University in Poznań, 61-614 Poznań, Poland
Interests: assistive robots; technology acceptance; e-health; healthcare

Special Issue Information

Dear Colleagues,

In recent decades, there has been tremendous technological advancement, which is particularly visible in the field of artificial intelligence and robotics. Various types of robots are increasingly being used in healthcare, including assistive robots, surgery robots, rehabilitation robots, service robots, and cognitive therapy robots. Artificial intelligence can also support medical personnel in numerous tasks. It is used not only in administrative work, documentation flow, and patient outreach, but also in the analysis of imaging data and patient monitoring. The increasing complexity of medical data and a significant increase in their quantity, compounded by insufficient staff and the increased demand for medical services, make it reasonable to assume that robots and artificial intelligence will become progressively more common in healthcare. However, it should be borne in mind that the development of technology not only brings new opportunities and numerous benefits but may also pose certain threats in areas such as data protection and ethics.

This Special Issue is dedicated to research and review articles focusing on the use of robotics and artificial intelligence to improve the efficiency and quality of healthcare, including ethical issues and privacy, as well as the safety and security of data.

I look forward to receiving your contributions.

Dr. Sylwia Łukasik
Guest Editor

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.

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. Robotics is an international peer-reviewed open access monthly 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 1800 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.

Keywords

  • robots
  • artificial intelligence
  • machine learning
  • healthcare
  • human–robot interaction (HRI)
  • technology acceptance
  • ethics and privacy
  • data safety and security

Published Papers (4 papers)

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Research

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15 pages, 7475 KiB  
Article
A Deep Learning Approach to Merge Rule-Based and Human-Operated Camera Control for Teleoperated Robotic Systems
by Luay Jawad, Arshdeep Singh-Chudda, Abhishek Shankar and Abhilash Pandya
Robotics 2024, 13(3), 47; https://doi.org/10.3390/robotics13030047 - 11 Mar 2024
Viewed by 1091
Abstract
Controlling a laparoscopic camera during robotic surgery represents a multifaceted challenge, demanding considerable physical and cognitive exertion from operators. While manual control presents the advantage of enabling optimal viewing angles, it is offset by its taxing nature. In contrast, current autonomous camera systems [...] Read more.
Controlling a laparoscopic camera during robotic surgery represents a multifaceted challenge, demanding considerable physical and cognitive exertion from operators. While manual control presents the advantage of enabling optimal viewing angles, it is offset by its taxing nature. In contrast, current autonomous camera systems offer predictability in tool tracking but are often rigid, lacking the adaptability of human operators. This research investigates the potential of two distinct network architectures: a dense neural network (DNN) and a recurrent network (RNN), both trained using a diverse dataset comprising autonomous and human-driven camera movements. A comparative assessment of network-controlled, autonomous, and human-operated camera systems is conducted to gauge network efficacies. While the dense neural network exhibits proficiency in basic tool tracking, it grapples with inherent architectural limitations that hinder its ability to master the camera’s zoom functionality. In stark contrast, the recurrent network excels, demonstrating a capacity to sufficiently replicate the behaviors exhibited by a mixture of both autonomous and human-operated methods. In total, 96.8% of the dense network predictions had up to a one-centimeter error when compared to the test datasets, while the recurrent network achieved a 100% sub-millimeter testing error. This paper trains and evaluates neural networks on autonomous and human behavior data for camera control. Full article
(This article belongs to the Special Issue Robots and Artificial Intelligence for a Better Future of Health Care)
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20 pages, 3754 KiB  
Article
A Robotic System to Anchor a Patient in a Lateral Position and Reduce Nurses’ Physical Strain
by Pascal Hinrichs, Kathrin Seibert, Pedro Arizpe Gómez, Max Pfingsthorn and Andreas Hein
Robotics 2023, 12(5), 144; https://doi.org/10.3390/robotics12050144 - 17 Oct 2023
Cited by 1 | Viewed by 1979
Abstract
Robotic manipulators can interact with large, heavy objects through whole-arm manipulation. Combined with direct physical interaction between humans and robots, the patient can be anchored in care. However, the complexity of this scenario requires control by a caregiver. We are investigating how such [...] Read more.
Robotic manipulators can interact with large, heavy objects through whole-arm manipulation. Combined with direct physical interaction between humans and robots, the patient can be anchored in care. However, the complexity of this scenario requires control by a caregiver. We are investigating how such a complex form of manipulation can be controlled by nurses and whether the use of such a system creates physical relief. The use case chosen was washing the back of a patient in the lateral position. The operability of the remote control from the tele-nurse’s point of view, the change in the posture of the nurse on site, the execution times, the evaluation of the cooperation between human and robot, and the evaluation of the system from the nurse’s point of view and from the patient’s point of view were evaluated. The results show that the posture of the worker improved by 11.93% on average, and by a maximum of 26.13%. Ease of use is rated as marginally high. The manipulator is considered helpful. The study shows that remote whole-arm manipulation can anchor bedridden patients in the lateral position and that this system can be operated by nurses and leads to an improvement in working posture. Full article
(This article belongs to the Special Issue Robots and Artificial Intelligence for a Better Future of Health Care)
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25 pages, 364 KiB  
Article
Beyond the Metal Flesh: Understanding the Intersection between Bio- and AI Ethics for Robotics in Healthcare
by Auxane Boch, Seamus Ryan, Alexander Kriebitz, Lameck Mbangula Amugongo and Christoph Lütge
Robotics 2023, 12(4), 110; https://doi.org/10.3390/robotics12040110 - 01 Aug 2023
Cited by 3 | Viewed by 4003
Abstract
As we look towards the future of healthcare, integrating Care Robots (CRs) into health systems is a practical approach to address challenges such as an ageing population and caregiver shortages. However, ethical discussions about the impact of CRs on patients, caregivers, healthcare systems, [...] Read more.
As we look towards the future of healthcare, integrating Care Robots (CRs) into health systems is a practical approach to address challenges such as an ageing population and caregiver shortages. However, ethical discussions about the impact of CRs on patients, caregivers, healthcare systems, and society are crucial. This normative research seeks to define an integrative and comprehensive ethical framework for CRs, encompassing a wide range of AI-related issues in healthcare. To build the framework, we combine principles of beneficence, non-maleficence, autonomy, justice, and explainability by integrating the AI4People framework for a Good AI Society and the traditional bioethics perspective. Using the integrated framework, we conduct an ethical assessment of CRs. Next, we identify three key ethical trade-offs and propose remediation strategies for the technology. Finally, we offer design recommendations for responsible development and usage of CRs. In conclusion, our research highlights the critical need for sector-specific ethical discussions in healthcare to fully grasp the potential implications of integrating AI technology. Full article
(This article belongs to the Special Issue Robots and Artificial Intelligence for a Better Future of Health Care)

Review

Jump to: Research

40 pages, 2806 KiB  
Review
Radiological Crossroads: Navigating the Intersection of Virtual Reality and Digital Radiology through a Comprehensive Narrative Review of Reviews
by Andrea Lastrucci and Daniele Giansanti
Robotics 2024, 13(5), 69; https://doi.org/10.3390/robotics13050069 (registering DOI) - 30 Apr 2024
Viewed by 194
Abstract
The integration of Virtual Reality with radiology is the focus of this study. A narrative review has been proposed to delve into emerging themes within the integration of Virtual Reality in radiology by scrutinizing reviews gathered from PubMed and Scopus. The proposed approach [...] Read more.
The integration of Virtual Reality with radiology is the focus of this study. A narrative review has been proposed to delve into emerging themes within the integration of Virtual Reality in radiology by scrutinizing reviews gathered from PubMed and Scopus. The proposed approach was based on a standard narrative checklist and a qualification process. The selection process identified 20 review studies. Integration of Virtual Reality (VR) in radiology offers potential transformative opportunities also integrated with other emerging technologies. In medical education, VR and AR, using 3D images from radiology, can enhance learning, emphasizing the need for standardized integration. In radiology, VR combined with Artificial Intelligence (AI) and Augmented Reality (AR) shows promising prospectives to give a complimentary contribution to diagnosis, treatment planning, and education. Challenges in clinical integration and User Interface design must be addressed. Innovations in medical education, like 3D modeling and AI, has the potential to enable personalized learning, but face standardization challenges. While robotics play a minor role, advancements and potential perspectives are observed in neurosurgery and endovascular systems. Ongoing research and standardization efforts are crucial for maximizing the potential of these integrative technologies in healthcare. In conclusion, the synthesis of these findings underscores the opportunities for advancements in digital radiology and healthcare through the integration of VR. However, challenges exist, and continuous research, coupled with technological refinements, is imperative to unlock the full potential of these integrative approaches in the dynamic and evolving field of medical imaging. Full article
(This article belongs to the Special Issue Robots and Artificial Intelligence for a Better Future of Health Care)
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