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Robotics
Special Issues
Intelligent Medical Robotics
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Intelligent Medical Robotics

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 September 2020) | Viewed by 24708

Special Issue Editor

Prof. Dr. Allon Guez

E-Mail Website
Guest Editor
Electrical and Computer Engineering, Drexel University, Philadelphia, PA 19104, USA
Interests: control systems; robotics; artificial intelligence (A.I.); automated decision making; medical robotics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

AI and Medical Robotics are currently experiencing tremendous levels of activity and interest. Both fields are very large in terms of the number of people and organizations involved as well as the resources invested in them, and both deal with a broad range of theories and applications.

This Special Issue is focused on Intelligent Medical Robotics—the intersection of AI and Medical Robotics, which has already proven to be a viable, fruitful domain on its own. Joining together the recent progress in machine learning, AI, wearable sensors, medical automation, and robotics of all types offers exciting opportunities for creating truly intelligent and automatic medical diagnostics and therapeutic systems.

Many communities, conferences, and publications currently deal with Intelligent Medical Robotics. We hope, in this open-source Special Issue, to provide a good opportunity to present research results that are immediately readable and usable by the larger community.

The Special Issue aims to collect recent research on all of the below-listed topics. Review papers are also welcome.

Topics of interest include (but are not limited to) the use of AI in:

  • brain-computer interfaces;
  • autonomous robots;
  • mobile robots;
  • service robots;
  • robotic implants;
  • nano-, micro- and milli-robots;
  • educational (interactive) robots;
  • modular robots;
  • collaborative robots;
  • medical military robots;
  • surgical robots;
  • rehabilitation robots;
  • biorobots;
  • telepresence robots;
  • pharmacy/lab automation;
  • companion robots;
  • disinfection robots;
  • machine intelligence;
  • neural network;
  • deep learning;
  • medical big data;
  • medical predictive analytics; and
  • medical robotics.

Prof. Allon Guez
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.

Published Papers (2 papers)

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Review

19 pages, 883 KiB  
Review
Possible Life Saver: A Review on Human Fall Detection Technology
by Zhuo Wang, Vignesh Ramamoorthy, Udi Gal and Allon Guez
Robotics 2020, 9(3), 55; https://doi.org/10.3390/robotics9030055 - 19 Jul 2020
Cited by 42 | Viewed by 10496
Abstract
Among humans, falls are a serious health problem causing severe injuries and even death for the elderly population. Besides, falls are also a major safety threat to bikers, skiers, construction workers, and others. Fortunately, with the advancements of technologies, the number of proposed [...] Read more.
Among humans, falls are a serious health problem causing severe injuries and even death for the elderly population. Besides, falls are also a major safety threat to bikers, skiers, construction workers, and others. Fortunately, with the advancements of technologies, the number of proposed fall detection systems and devices has increased dramatically and some of them are already in the market. Fall detection devices/systems can be categorized based on their architectures as wearable devices, ambient systems, image processing-based systems, and hybrid systems, which employ a combination of two or more of these methodologies. In this review paper, a comparison is made among these major fall detection systems, devices, and algorithms in terms of their proposed approaches and measure of performance. Issues with the current systems such as lack of portability and reliability are presented as well. Development trends such as the use of smartphones, machine learning, and EEG are recognized. Challenges with privacy issues, limited real fall data, and ergonomic design deficiency are also discussed. Full article
(This article belongs to the Special Issue Intelligent Medical Robotics)
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23 pages, 1806 KiB  
Review
Laparoscopic Robotic Surgery: Current Perspective and Future Directions
by Sally Kathryn Longmore, Ganesh Naik and Gaetano D. Gargiulo
Robotics 2020, 9(2), 42; https://doi.org/10.3390/robotics9020042 - 27 May 2020
Cited by 30 | Viewed by 13537
Abstract
Just as laparoscopic surgery provided a giant leap in safety and recovery for patients over open surgery methods, robotic-assisted surgery (RAS) is doing the same to laparoscopic surgery. The first laparoscopic-RAS systems to be commercialized were the Intuitive Surgical, Inc. (Sunnyvale, CA, USA) [...] Read more.
Just as laparoscopic surgery provided a giant leap in safety and recovery for patients over open surgery methods, robotic-assisted surgery (RAS) is doing the same to laparoscopic surgery. The first laparoscopic-RAS systems to be commercialized were the Intuitive Surgical, Inc. (Sunnyvale, CA, USA) da Vinci and the Computer Motion Zeus. These systems were similar in many aspects, which led to a patent dispute between the two companies. Before the dispute was settled in court, Intuitive Surgical bought Computer Motion, and thus owned critical patents for laparoscopic-RAS. Recently, the patents held by Intuitive Surgical have begun to expire, leading to many new laparoscopic-RAS systems being developed and entering the market. In this study, we review the newly commercialized and prototype laparoscopic-RAS systems. We compare the features of the imaging and display technology, surgeons console and patient cart of the reviewed RAS systems. We also briefly discuss the future directions of laparoscopic-RAS surgery. With new laparoscopic-RAS systems now commercially available we should see RAS being adopted more widely in surgical interventions and costs of procedures using RAS to decrease in the near future. Full article
(This article belongs to the Special Issue Intelligent Medical Robotics)
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