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

Deadline for manuscript submissions: closed (20 September 2022) | Viewed by 44601

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Special Issue Editor

Prof. Dr. Víctor Fernando Muñoz Martínez

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Guest Editor

Ingenieria de Sistemas y Automatica, University of Malaga, 29016 Málaga, Spain
Interests: surgical collaborative robots; cognitive medical applications; autonomous robot motion control; fault tolerance architectures for surgical robots

Special Issue Information

Dear Colleagues,

Sensor technologies are present along the entire wide range of medical robot applications, which mainly include surgery, rehabilitation, therapeutics treatments, as well as prothesis and orthosis. The common challenge is defined as moving to a close human–robot interaction in such a way that these applications are following the concept of Industry 4.0. Along these lines, the concept of co-worker robots in the medical field has been coined, which also includes the use of both medical smart tools as well as support interfaces in a safe framework. New sensor technologies will provide these kinds of robots with the ability to be integrated in the cyberphysics system of the medical environment. This means the development of robotic systems able to communicate with other smart devices or humans, fault tolerance control, medical task planification and coordination, qualitative goal-based robot motion, and medical procedure supervision. Therefore, this Special Issue, devoted to sensor technology for medical robots, seeks current research and actual applications that represent a step forward in this field. Some of the topics which are welcome in this Special Issue include but are not limited to:

Medical robot autonomy;
Human–robot interfaces in medical applications;
Medical robot environment awareness;
Human–robot task coordination in medical applications;
Sensor-based fault tolerant control;
Detection of human intention in medical applications;
Medical procedure supervision.

Prof. Dr. Víctor Fernando Muñoz Martínez
Guest Editor

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Keywords

Sensor-based cognitive architectures
Smart sensors
Autonomous robots
Co-worker robots
Biomechatronics devices for medical robots
A.I. sensor-based techniques
Biosensors in robotics applications
Human motion detection for HRI
In vitro, in vivo, and clinical trials

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Published Papers (12 papers)

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Editorial

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3 pages, 191 KiB

Open AccessEditorial

Sensors Technology for Medical Robotics

by Víctor F. Muñoz

Sensors 2022, 22(23), 9290; https://doi.org/10.3390/s22239290 - 29 Nov 2022

Cited by 1 | Viewed by 1389

Abstract

There are many definitions for the concept of a robot, perhaps too many; it has even been said that we do not know how to define them, but when we see a robot, we identify it [...] Full article

(This article belongs to the Special Issue Sensors Technology for Medical Robotics)

Research

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17 pages, 2844 KiB

Open AccessArticle

Understanding Emotions in Children with Developmental Disabilities during Robot Therapy Using EDA

by Taisuke Nagae and Jaeryoung Lee

Sensors 2022, 22(14), 5116; https://doi.org/10.3390/s22145116 - 7 Jul 2022

Cited by 8 | Viewed by 2360

Abstract

Recent technological advancements have led to the emergence of supportive robotics to help children with developmental disabilities become independent. In conventional research, in robot therapy, experiments are often conducted by operating the robot out of the subject’s sight. In this paper, robot therapy using a system that can autonomously recognize the emotions of a child with developmental disabilities and provide feedback was developed. The aim was to quantitatively infer emotional changes in children using skin conductance (EDA) during robot therapy. It was demonstrated that the robot could recognize emotions autonomously and provide feedback to the subjects. Additionally, a quantitative evaluation was conducted using EDA. By analyzing the symptoms related to developmental disorders, it may be possible to improve the recognition rate and tailor therapy based on symptoms. Full article

(This article belongs to the Special Issue Sensors Technology for Medical Robotics)

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16 pages, 4227 KiB

Open AccessArticle

Dual Mode pHRI-teleHRI Control System with a Hybrid Admittance-Force Controller for Ultrasound Imaging

by Teng Li, Xiao Meng and Mahdi Tavakoli

Sensors 2022, 22(11), 4025; https://doi.org/10.3390/s22114025 - 26 May 2022

Cited by 9 | Viewed by 1989

Abstract

The COVID-19 pandemic has brought unprecedented extreme pressure on the medical system due to the physical distance policy, especially for procedures such as ultrasound (US) imaging, which are usually carried out in person. Tele-operation systems are a promising way to avoid physical human–robot interaction (pHRI). However, the system usually requires another robot on the remote doctor side to provide haptic feedback, which makes it expensive and complex. To reduce the cost and system complexity, in this paper, we present a low-cost, easy-to-use, dual-mode pHRI-

t e l e

HRI control system with a custom-designed hybrid admittance-force controller for US imaging. The proposed system requires only a tracking camera rather than a sophisticated robot on the remote side. An audio feedback is designed for replacing haptic feedback on the remote side, and its sufficiency is experimentally verified. The experimental results indicate that the designed hybrid controller can significantly improve the task performance in both modes. Furthermore, the proposed system enables the user to conduct US imaging while complying with the physical distance policy, and allows them to seamlessly switch modes from one to another in an online manner. The novel system can be easily adapted to other medical applications beyond the pandemic, such as tele-healthcare, palpation, and auscultation. Full article

(This article belongs to the Special Issue Sensors Technology for Medical Robotics)

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12 pages, 3272 KiB

Open AccessArticle

An Analysis of Respiration with the Smart Sensor SENSIRIB in Patients Undergoing Thoracic Surgery

by Marco Ceccarelli, Riccardo Taje, Paula Elena Papuc and Vincenzo Ambrogi

Sensors 2022, 22(4), 1561; https://doi.org/10.3390/s22041561 - 17 Feb 2022

Cited by 3 | Viewed by 2796

Abstract

The paper examines the problem of respiration monitoring with easily wearable instrumentation by using a smart device that is properly designed and implemented with small and light components. The practical implementation is presented both in practical aspects and from experimental results by following a properly defined method with a medical-like protocol and specific procedure of testing. The results of a statistically significant campaign of experimental tests are reported with the characteristic data from the angles and acceleration components of a sensed rib both to validate the smart device and the procedure for respiration monitoring. Full article

(This article belongs to the Special Issue Sensors Technology for Medical Robotics)

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15 pages, 6459 KiB

Open AccessArticle

A Cylindrical Grip Type of Tactile Device Using Magneto-Responsive Materials Integrated with Surgical Robot Console: Design and Analysis

by Yu-Jin Park, Eun-Sang Lee and Seung-Bok Choi

Sensors 2022, 22(3), 1085; https://doi.org/10.3390/s22031085 - 30 Jan 2022

Cited by 11 | Viewed by 5333

Abstract

This paper proposes a cylindrical grip type of tactile device that is effectively integrated to a surgical robot console so that a surgeon can easily touch and feel the same stiffness as the operating organs. This is possible since the yield stress (or stiffness) of magnetic-responsive materials can be tuned or controlled by the magnetic field intensity. The proposed tactile device consists of two main parts: a magnetorheological elastomer (MRE) layer and a magnetorheological fluid (MRF) core. The grip shape of the device to be positioned on the handle part of the master of the surgical robot is configured and its operating principle is discussed. Then, a couple of equations to calculate the stiffness from the gripping force and the field-dependent yield stress of MRF are derived and integrated using the finite element analysis (FEA) model. After simulating the stiffness of the proposed tactile device as a function of the magnetic field intensity (or current), the stiffnesses of various human organs, including the liver and heart, are calculated from known data of an elastic modulus. It is demonstrated from comparative data between calculated stiffness from human tissues and simulated stiffness from FEA that the proposed tactile device can generate sufficient stiffness with a low current level to recognize various human organs which are significantly required in the surgical robot system. Full article

(This article belongs to the Special Issue Sensors Technology for Medical Robotics)

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16 pages, 10189 KiB

Open AccessArticle

Optical Fiber Array Sensor for Force Estimation and Localization in TAVI Procedure: Design, Modeling, Analysis and Validation

by Naghmeh Bandari, Javad Dargahi and Muthukumaran Packirisamy

Sensors 2021, 21(16), 5377; https://doi.org/10.3390/s21165377 - 9 Aug 2021

Cited by 6 | Viewed by 2692

Abstract

Transcatheter aortic valve implantation has shown superior clinical outcomes compared to open aortic valve replacement surgery. The loss of the natural sense of touch, inherited from its minimally invasive nature, could lead to misplacement of the valve in the aortic annulus. In this study, a cylindrical optical fiber sensor is proposed to be integrated with valve delivery catheters. The proposed sensor works based on intensity modulation principle and is capable of measuring and localizing lateral force. The proposed sensor was constituted of an array of optical fibers embedded on a rigid substrate and covered by a flexible shell. The optical fibers were modeled as Euler–Bernoulli beams with both-end fixed boundary conditions. To study the sensing principle, a parametric finite element model of the sensor with lateral point loads was developed and the deflection of the optical fibers, as the determinant of light intensity modulation was analyzed. Moreover, the sensor was fabricated, and a set of experiments were performed to study the performance of the sensor in lateral force measurement and localization. The results showed that the transmitted light intensity decreased up to 24% for an external force of 1 N. Additionally, the results showed the same trend between the simulation predictions and experimental results. The proposed sensor was sensitive to the magnitude and position of the external force which shows its capability for lateral force measurement and localization. Full article

(This article belongs to the Special Issue Sensors Technology for Medical Robotics)

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23 pages, 9953 KiB

Open AccessArticle

A New Tactile Transfer Cell Using Magnetorheological Materials for Robot-Assisted Minimally Invasive Surgery

by Yu-Jin Park and Seung-Bok Choi

Sensors 2021, 21(9), 3034; https://doi.org/10.3390/s21093034 - 26 Apr 2021

Cited by 18 | Viewed by 3358

Abstract

This paper proposes a new type of tactile transfer cell which can be effectively applied to robot-assisted minimally invasive surgery (RMIS). The proposed tactile device is manufactured from two smart materials, a magnetorheological fluid (MRF) and a magnetorheological elastomer (MRE), whose viscoelastic properties are controllable by an external magnetic field. Thus, it can produce field-dependent repulsive forces which are equivalent to several human organs (or tissues) such as a heart. As a first step, an appropriate tactile sample is made using both MRF and MRE associated with porous foam. Then, the microstructures of these materials taken from Scanning Electron Microscope (SEM) images are presented, showing the particle distribution with and without the magnetic field. Subsequently, the field-dependent repulsive force of the sample, which is equivalent to the stress relaxation property of viscoelastic materials, are measured at several compressive deformation depths. Then, the measured values are compared with the calculated values obtained from Young’s modulus of human tissue data via the finite element method. It is identified from this comparison that the proposed tactile transfer cell can mimic the repulsive force (or hardness) of several human organs. This directly indicates that the proposed MR materials-based tactile transfer cell (MRTTC in short) can be effectively applied to RMIS in which the surgeon can feel the strength or softness of the human organ by just changing the magnetic field intensity. In this work, to reflect a more practical feasibility, a psychophysical test is also carried out using 20 volunteers, and the results are analyzed, presenting the standard deviation. Full article

(This article belongs to the Special Issue Sensors Technology for Medical Robotics)

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17 pages, 6715 KiB

Open AccessArticle

Collaborative Robotic Assistant Platform for Endonasal Surgery: Preliminary In-Vitro Trials

by Victor F. Muñoz, Isabel Garcia-Morales, Juan Carlos Fraile-Marinero, Javier Perez-Turiel, Alvaro Muñoz-Garcia, Enrique Bauzano, Irene Rivas-Blanco, Jose María Sabater-Navarro and Eusebio de la Fuente

Sensors 2021, 21(7), 2320; https://doi.org/10.3390/s21072320 - 26 Mar 2021

Cited by 8 | Viewed by 2800

Abstract

Endonasal surgery is a minimally invasive approach for the removal of pituitary tumors (sarcomas). In this type of procedure, the surgeon has to complete the surgical maneuvers for sarcoma resection with extreme precision, as there are many vital structures in this area. Therefore, the use of robots for this type of intervention could increase the success of the intervention by providing accurate movements. Research has focused on the development of teleoperated robots to handle a surgical instrument, including the use of virtual fixtures to delimit the working area. This paper aims to go a step further with a platform that includes a teleoperated robot and an autonomous robot dedicated to secondary tasks. In this way, the aim is to reduce the surgeon’s workload so that he can concentrate on his main task. Thus, the article focuses on the description and implementation of a navigator that coordinates both robots via a force/position control. Finally, both the navigation and control scheme were validated by in-vitro tests. Full article

(This article belongs to the Special Issue Sensors Technology for Medical Robotics)

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13 pages, 3322 KiB

Open AccessArticle

Effect of a Brain–Computer Interface Based on Pedaling Motor Imagery on Cortical Excitability and Connectivity

by Vivianne Flávia Cardoso, Denis Delisle-Rodriguez, Maria Alejandra Romero-Laiseca, Flávia A. Loterio, Dharmendra Gurve, Alan Floriano, Carlos Valadão, Leticia Silva, Sridhar Krishnan, Anselmo Frizera-Neto and Teodiano Freire Bastos-Filho

Sensors 2021, 21(6), 2020; https://doi.org/10.3390/s21062020 - 12 Mar 2021

Cited by 14 | Viewed by 4128

Abstract

Recently, studies on cycling-based brain–computer interfaces (BCIs) have been standing out due to their potential for lower-limb recovery. In this scenario, the behaviors of the sensory motor rhythms and the brain connectivity present themselves as sources of information that can contribute to interpreting the cortical effect of these technologies. This study aims to analyze how sensory motor rhythms and cortical connectivity behave when volunteers command reactive motor imagery (MI) BCI that provides passive pedaling feedback. We studied 8 healthy subjects who performed pedaling MI to command an electroencephalography (EEG)-based BCI with a motorized pedal to receive passive movements as feedback. The EEG data were analyzed under the following four conditions: resting, MI calibration, MI online, and receiving passive pedaling (on-line phase). Most subjects produced, over the foot area, significant event-related desynchronization (ERD) patterns around Cz when performing MI and receiving passive pedaling. The sharpest decrease was found for the low beta band. The connectivity results revealed an exchange of information between the supplementary motor area (SMA) and parietal regions during MI and passive pedaling. Our findings point to the primary motor cortex activation for most participants and the connectivity between SMA and parietal regions during pedaling MI and passive pedaling. Full article

(This article belongs to the Special Issue Sensors Technology for Medical Robotics)

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13 pages, 3109 KiB

Open AccessArticle

Vision-Based Suture Tensile Force Estimation in Robotic Surgery

by Won-Jo Jung, Kyung-Soo Kwak and Soo-Chul Lim

Sensors 2021, 21(1), 110; https://doi.org/10.3390/s21010110 - 26 Dec 2020

Cited by 24 | Viewed by 4925

Abstract

Compared to laparoscopy, robotics-assisted minimally invasive surgery has the problem of an absence of force feedback, which is important to prevent a breakage of the suture. To overcome this problem, surgeons infer the suture force from their proprioception and 2D image by comparing them to the training experience. Based on this idea, a deep-learning-based method using a single image and robot position to estimate the tensile force of the sutures without a force sensor is proposed. A neural network structure with a modified Inception Resnet-V2 and Long Short Term Memory (LSTM) networks is used to estimate the suture pulling force. The feasibility of proposed network is verified using the generated DB, recording the interaction under the condition of two different artificial skins and two different situations (in vivo and in vitro) at 13 viewing angles of the images by changing the tool positions collected from the master-slave robotic system. From the evaluation conducted to show the feasibility of the interaction force estimation, the proposed learning models successfully estimated the tensile force at 10 unseen viewing angles during training. Full article

(This article belongs to the Special Issue Sensors Technology for Medical Robotics)

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Review

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23 pages, 2203 KiB

Open AccessReview

Robot-Aided Systems for Improving the Assessment of Upper Limb Spasticity: A Systematic Review

by Rubén de-la-Torre, Edwin Daniel Oña, Carlos Balaguer and Alberto Jardón

Sensors 2020, 20(18), 5251; https://doi.org/10.3390/s20185251 - 14 Sep 2020

Cited by 27 | Viewed by 5895

Abstract

Spasticity is a motor disorder that causes stiffness or tightness of the muscles and can interfere with normal movement, speech, and gait. Traditionally, the spasticity assessment is carried out by clinicians using standardized procedures for objective evaluation. However, these procedures are manually performed and, thereby, they could be influenced by the clinician’s subjectivity or expertise. The automation of such traditional methods for spasticity evaluation is an interesting and emerging field in neurorehabilitation. One of the most promising approaches is the use of robot-aided systems. In this paper, a systematic review of systems focused on the assessment of upper limb (UL) spasticity using robotic technology is presented. A systematic search and review of related articles in the literature were conducted. The chosen works were analyzed according to the morphology of devices, the data acquisition systems, the outcome generation method, and the focus of intervention (assessment and/or training). Finally, a series of guidelines and challenges that must be considered when designing and implementing fully-automated robot-aided systems for the assessment of UL spasticity are summarized. Full article

(This article belongs to the Special Issue Sensors Technology for Medical Robotics)

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Other

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11 pages, 17623 KiB

Open AccessLetter

Exploring New Potential Applications for Hand Exoskeletons: Power Grip to Assist Human Standing

by Jorge A. Diez, Victor Santamaria, Moiz I. Khan, José M. Catalán, Nicolas Garcia-Aracil and Sunil K. Agrawal

Sensors 2021, 21(1), 30; https://doi.org/10.3390/s21010030 - 23 Dec 2020

Cited by 5 | Viewed by 3819

Abstract

Hand exoskeleton potential applications reach further than grasping or assistance during manipulation. In this paper, we present a preliminary study of how this technology can be applied in order to improve performance during standing to help the user to keep balance under perturbations. Non-impaired users wearing a hand exoskeleton gripping a hand rail were pushed by a cable-driven robot, so that their standing equilibrium was perturbed. The center of pressure, surface electromyography, and interaction force data were recorded in order to assess the performance of users and their postural strategy. The results showed that users could keep their balance with the same outcomes using their bare hands and the hand exoskeleton. However, when wearing the exoskeleton, a higher muscular activity was registered in hand flexor muscles. This is also supported by the grasping force, which shows that users stretched their hand more than expected when wearing the hand exoskeleton. This paper concludes that it is possible that the lack of tactile feedback could lead to over compensation in the grasping. Therefore, the next studies will aim to check whether this effect can be reversed by training users to wear the exoskeleton. Full article

(This article belongs to the Special Issue Sensors Technology for Medical Robotics)

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