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Multisensor Intelligent Medical Robotics
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Multisensor Intelligent Medical Robotics

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

Deadline for manuscript submissions: closed (30 November 2019) | Viewed by 22734

Special Issue Editors

Prof. Dr. Iulian I. Iordachita

E-Mail Website
Guest Editor
Scholl of Engineering, Department of Mechanical Engineering Laboratory for Computational Sensing and Robotics, Johns Hopkins University, Hackerman Hall 125, 3400 North Charles Street Baltimore, MD 21218-2682, USA
Interests: surgical robotics; medical instrumentation; smart surgical tools; image-guided surgery; computer assisted surgery; mechanisms and mechanical transmissions for robots
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Axel Krieger

E-Mail Website
Guest Editor
Department of Mechanical Engineering, University of Maryland, 2151 Glenn Martin Hall College Park, MD 20742, USA
Interests: medical robotics; surgical robotics; autonomous surgery; robot control; surgical image guidance; medical device development

Special Issue Information

Dear Colleagues,

Medical robotics has a great potential to fundamentally change surgery and more generally clinical practice, by combining human strengths with computer and sensor-based technology in an information-driven environment with the ultimate goal to treat the patient with greater safety and efficiency, and to reduce morbidity. Sensors have critical role in virtually all applications across the medical robotics for accurate information acquisition, effective monitoring, optimal decision making, and efficient operation The miniaturization of sensors and actuators, combined with real-time computer processing, optics, and robotics has transformed the way modern therapies, interventions, and surgeries are performed. Sensor-based medical robotics has reached a turning point, with clinically proven systems and market successes.

For this forthcoming Special Issue, we invite manuscripts on all aspects pertinent to medical robotics applications of multisensor technology. Both reviews and original research articles are welcome. Reviews should provide an up-to-date and critical overview of state-of-the-art technologies such as multisensor applications for medical robotics or integration into medical devices, MRI-compatible sensors, trends for continuous and/or remote monitoring of medical robotic devices, sensors for robot-assisted surgery, etc. Original research papers that describe the use of multisensor technology in medical robotics, modelling and evaluation, sensors materials, processing, fabrication and calibration, optical fiber sensing, or new concepts and fundamental studies with potential relevance to medical robotics applications are of interest. Single sensor medical robotics papers can also be included in our Special Issue. If you have suggestions that you would like to discuss beforehand, please feel free to contact us. We look forward to and welcome your participation in this Special Issue.

Prof. Dr. Iulian I. Iordachita
Prof. Dr. Axel Krieger
Guest Editors

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. 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 2600 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

  • Multisensor
  • Sensor fusion
  • MRI-compatible sensor
  • Medical robotics
  • Surgical robotics
  • Image-guided surgery
  • Multisensor-based control
  • Sensorized medical device
  • Optical sensor
  • Sensor modeling
  • Sensor fabrication
  • Sensor calibration

Published Papers (5 papers)

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Research

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18 pages, 11142 KiB  
Article
Human Body Mixed Motion Pattern Recognition Method Based on Multi-Source Feature Parameter Fusion
by Jiyuan Song, Aibin Zhu, Yao Tu, Yingxu Wang, Muhammad Affan Arif, Huang Shen, Zhitao Shen, Xiaodong Zhang and Guangzhong Cao
Sensors 2020, 20(2), 537; https://doi.org/10.3390/s20020537 - 18 Jan 2020
Cited by 19 | Viewed by 3459
Abstract
Aiming at the requirement of rapid recognition of the wearer’s gait stage in the process of intelligent hybrid control of an exoskeleton, this paper studies the human body mixed motion pattern recognition technology based on multi-source feature parameters. We obtain information on human [...] Read more.
Aiming at the requirement of rapid recognition of the wearer’s gait stage in the process of intelligent hybrid control of an exoskeleton, this paper studies the human body mixed motion pattern recognition technology based on multi-source feature parameters. We obtain information on human lower extremity acceleration and plantar analyze the relationship between these parameters and gait cycle studying the motion state recognition method based on feature evaluation and neural network. Based on the actual requirements of exoskeleton per use, 15 common gait patterns were determined. Using this, the studies were carried out on the time domain, frequency domain, and energy feature extraction of multi-source lower extremity motion information. The distance-based feature screening method was used to extract the optimal features. Finally, based on the multi-layer BP (back propagation) neural network, a nonlinear mapping model between feature quantity and motion state was established. The experimental results showed that the recognition accuracy in single motion mode can reach up to 98.28%, while the recognition accuracy of the two groups of experiments in mixed motion mode was found to be 92.7% and 97.4%, respectively. The feasibility and effectiveness of the model were verified. Full article
(This article belongs to the Special Issue Multisensor Intelligent Medical Robotics)
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14 pages, 72779 KiB  
Article
Demonstration of Optical Coherence Tomography Guided Big Bubble Technique for Deep Anterior Lamellar Keratoplasty (DALK)
by Shoujing Guo, Nicolas R. Sarfaraz, William G. Gensheimer, Axel Krieger and Jin U. Kang
Sensors 2020, 20(2), 428; https://doi.org/10.3390/s20020428 - 12 Jan 2020
Cited by 11 | Viewed by 3888
Abstract
Deep anterior lamellar keratoplasty (DALK) is a highly challenging procedure for cornea transplant that involves removing the corneal layers above Descemet’s membrane (DM). This is achieved by a “big bubble” technique where a needle is inserted into the stroma of the cornea down [...] Read more.
Deep anterior lamellar keratoplasty (DALK) is a highly challenging procedure for cornea transplant that involves removing the corneal layers above Descemet’s membrane (DM). This is achieved by a “big bubble” technique where a needle is inserted into the stroma of the cornea down to DM and the injection of either air or liquid. DALK has important advantages over penetrating keratoplasty (PK) including lower rejection rate, less endothelial cell loss, and increased graft survival. In this paper, we successfully designed and evaluated the optical coherence tomography (OCT) distal sensor integrated needle for a precise big bubble technique. We successfully used this sensor for micro-control of a robotic DALK device termed AUTO-DALK for autonomous big bubble needle insertion. The OCT distal sensor was integrated inside a 25-gauge needle, which was used for pneumo-dissection. The AUTO-DALK device is built on a manual trephine platform which includes a vacuum ring to fix the device on the eye and add a needle driver at an angle of 60 degrees from vertical. During the test on five porcine eyes with a target depth of 90%, the measured insertion depth as a percentage of cornea thickness for the AUTO-DALK device was 90.05 % ± 2.33 % without any perforation compared to 79.16 % ± 5.68 % for unassisted free-hand insertion and 86.20 % ± 5.31 % for assisted free-hand insertion. The result showed a higher precision and consistency of the needle placement with AUTO-DALK, which could lead to better visual outcomes and fewer complications. Full article
(This article belongs to the Special Issue Multisensor Intelligent Medical Robotics)
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17 pages, 6265 KiB  
Article
New Calibrator with Points Distributed Conical Helically for Online Calibration of C-Arm
by Na Guo, Biao Yang, Yuhan Wang, Hongsheng Liu, Lei Hu and Tianmiao Wang
Sensors 2019, 19(9), 1989; https://doi.org/10.3390/s19091989 - 28 Apr 2019
Cited by 1 | Viewed by 3138
Abstract
To improve the accuracy of calibration of C-arm, and overcome the space limitation in surgery, we proposed a new calibrator for online calibration of C-arm. After the image rectification by a polynomial fitting-based global correction method, the C-arm was assumed as an ideal [...] Read more.
To improve the accuracy of calibration of C-arm, and overcome the space limitation in surgery, we proposed a new calibrator for online calibration of C-arm. After the image rectification by a polynomial fitting-based global correction method, the C-arm was assumed as an ideal pinhole model. The relationships between two kinds of spatial calibration errors and the distribution of fiducial points were studied: the performance of FRE (Fiducial Registration Error) and TRE (Target Registration Error) were not consistent, but both were best at the 12 marked points; the TRE decreased with the increase of the uniformity of calibration points distribution, and with the decrease of the distance between the target point and the center of calibration points. A calibrator with 12 fiducial points conical helically distributed, which could be placed on the knee, was an attractive option. A total of 10 experiments on C-arm calibration accuracy were conducted and the mean value of mapping error was 0.41 mm. We designed an ACL reconstruction navigation system and carried out specimen experiments on 4 pairs of dry femur and tibia. The mean accuracy of navigation system was 0.85 mm, which is important to the tunnel positioning for ACL reconstruction. Full article
(This article belongs to the Special Issue Multisensor Intelligent Medical Robotics)
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12 pages, 20982 KiB  
Article
Optical Fiber Sensor Performance Evaluation in Soft Polyimide Film with Different Thickness Ratios
by Yanlin He, Xu Zhang, Lianqing Zhu, Guangkai Sun, Xiaoping Lou and Mingli Dong
Sensors 2019, 19(4), 790; https://doi.org/10.3390/s19040790 - 15 Feb 2019
Cited by 13 | Viewed by 4042
Abstract
To meet the application requirements of curvature measurement for soft biomedical robotics and flexible morphing wings of aircraft, the optical fiber Bragg grating (FBG) shape sensor for soft robots and flexible morphing wing was implemented. This optical FBG is embedded in polyimide film [...] Read more.
To meet the application requirements of curvature measurement for soft biomedical robotics and flexible morphing wings of aircraft, the optical fiber Bragg grating (FBG) shape sensor for soft robots and flexible morphing wing was implemented. This optical FBG is embedded in polyimide film and then fixed in the body of a soft robot and morphing wing. However, a lack of analysis on the embedded depth of FBG sensors in polyimide film and its sensitivity greatly limits their application potential. Herein, the relationship between the embedded depth of the FBG sensor in polyimide film and its sensitivity and stability are investigated. The sensing principle and structural design of the FBG sensor embedded in polyimide film are introduced; the bending curvatures of the FBG sensor and its wavelength shift in polyimide film are studied; and the relationship between the sensitivity, stability, and embedded depth of these sensors are verified experimentally. The results showed that wavelength shift and curvature have a linear relationship. With the sensor’s curvature ranging from 0 m−1 to 30 m−1, their maximum sensitivity is 50.65 pm/m−1, and their minimum sensitivity is 1.96 pm/m−1. The designed FBG sensor embedded in polyimide films shows good consistency in repeated experiments for soft actuator and morphing wing measurement; the FBG sensing method therefore has potential for real applications in shape monitoring in the fields of soft robotics and the flexible morphing wings of aircraft. Full article
(This article belongs to the Special Issue Multisensor Intelligent Medical Robotics)
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Review

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19 pages, 3234 KiB  
Review
Medical Robotics in Bone Fracture Reduction Surgery: A Review
by Long Bai, Jianxing Yang, Xiaohong Chen, Yuanxi Sun and Xingyu Li
Sensors 2019, 19(16), 3593; https://doi.org/10.3390/s19163593 - 18 Aug 2019
Cited by 48 | Viewed by 7435
Abstract
Since the advantages of precise operation and effective reduction of radiation, robots have become one of the best choices for solving the defects of traditional fracture reduction surgery. This paper focuses on the application of robots in fracture reduction surgery, design of the [...] Read more.
Since the advantages of precise operation and effective reduction of radiation, robots have become one of the best choices for solving the defects of traditional fracture reduction surgery. This paper focuses on the application of robots in fracture reduction surgery, design of the mechanism, navigation technology, robotic control, interaction technology, and the bone–robot connection technology. Through literature review, the problems in current fracture reduction robot and its future development are discussed. Full article
(This article belongs to the Special Issue Multisensor Intelligent Medical Robotics)
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