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Force and Pressure Based Sensing Medical Application
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Force and Pressure Based Sensing Medical Application

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

Deadline for manuscript submissions: closed (31 December 2017) | Viewed by 143100

Special Issue Editor

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

Special Issue Information

Dear Colleagues,

Continued advances in healthcare are dependent upon the development of disruptive technology. The technological innovation of the past two decades has enabled the massively beneficial introduction of computer and robotic assisted technology into modern patient healthcare. The miniaturization of sensors and actuators, combined with real-time computer processing, optics, and robotics has transformed the way maintenance and restoration of health by medication or surgical intervention are performed.

For this forthcoming Special Issue, we invite manuscripts in all aspects pertinent to medical applications of force and pressure sensors. 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 sensor applications for stand-alone diagnostic devices or integrated into medical devices; MRI-compatible sensors; trends for the continuous and remote monitoring of medical parameters; sensors for robot-assisted surgery, etc. Original research papers that describe the medical utilization of force and pressure sensors; modelling and evaluation; sensors materials; processing; fabrication and calibration; and optical fiber sensing; or new concepts and fundamental studies with potential relevance to medical applications, are of interest. 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
Guest Editor

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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

  • force sensor

  • pressure sensor

  • medical application

  • MRI-compatible sensor

  • stand-alone diagnostic device

  • medical device

  • optical fiber

  • sensor modeling

  • evaluation

  • fabrication

  • calibration

Published Papers (20 papers)

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16 pages, 5887 KiB  
Article
Self-Calibration Algorithm for a Pressure Sensor with a Real-Time Approach Based on an Artificial Neural Network
by Ahmed M. M. Almassri, Wan Zuha Wan Hasan, Siti Anom Ahmad, Suhaidi Shafie, Chikamune Wada and Keiichi Horio
Sensors 2018, 18(8), 2561; https://doi.org/10.3390/s18082561 - 05 Aug 2018
Cited by 29 | Viewed by 5957
Abstract
This paper presents a novel approach to predicting self-calibration in a pressure sensor using a proposed Levenberg Marquardt Back Propagation Artificial Neural Network (LMBP-ANN) model. The self-calibration algorithm should be able to fix major problems in the pressure sensor such as hysteresis, variation [...] Read more.
This paper presents a novel approach to predicting self-calibration in a pressure sensor using a proposed Levenberg Marquardt Back Propagation Artificial Neural Network (LMBP-ANN) model. The self-calibration algorithm should be able to fix major problems in the pressure sensor such as hysteresis, variation in gain and lack of linearity with high accuracy. The traditional calibration process for this kind of sensor is a time-consuming task because it is usually done through manual and repetitive identification. Furthermore, a traditional computational method is inadequate for solving the problem since it is extremely difficult to resolve the mathematical formula among multiple confounding pressure variables. Accordingly, this paper describes a new self-calibration methodology for nonlinear pressure sensors based on an LMBP-ANN model. The proposed method was achieved using a collected dataset from pressure sensors in real time. The load cell will be used as a reference for measuring the applied force. The proposed method was validated by comparing the output pressure of the trained network with the experimental target pressure (reference). This paper also shows that the proposed model exhibited a remarkable performance than traditional methods with a max mean square error of 0.17325 and an R-value over 0.99 for the total response of training, testing and validation. To verify the proposed model’s capability to build a self-calibration algorithm, the model was tested using an untrained input data set. As a result, the proposed LMBP-ANN model for self-calibration purposes is able to successfully predict the desired pressure over time, even the uncertain behaviour of the pressure sensors due to its material creep. This means that the proposed model overcomes the problems of hysteresis, variation in gain and lack of linearity over time. In return, this can be used to enhance the durability of the grasping mechanism, leading to a more robust and secure grasp for paralyzed hands. Furthermore, the exposed analysis approach in this paper can be a useful methodology for the user to evaluate the performance of any measurement system in a real-time environment. Full article
(This article belongs to the Special Issue Force and Pressure Based Sensing Medical Application)
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11 pages, 2734 KiB  
Article
Pressure Distribution during Negative Pressure Wound Therapy of Experimental Abdominal Compartment Syndrome in a Porcine Model
by Adrienn Csiszkó, Klaudia Balog, Zoltán Attila Godó, Gyula Juhász, Katalin Pető, Ádám Deák, Mariann Berhés, Norbert Németh, Zsolt Bodnár and Zsolt Szentkereszty
Sensors 2018, 18(3), 897; https://doi.org/10.3390/s18030897 - 17 Mar 2018
Cited by 5 | Viewed by 6248
Abstract
(1) Introduction: Negative pressure wound therapy (NPWT) is a frequently applied open abdomen (OA) treatment. There are only a few experimental data supporting this method and describing the optimal settings and pressure distribution in the abdominal cavity during this procedure. The aim of [...] Read more.
(1) Introduction: Negative pressure wound therapy (NPWT) is a frequently applied open abdomen (OA) treatment. There are only a few experimental data supporting this method and describing the optimal settings and pressure distribution in the abdominal cavity during this procedure. The aim of our study was to evaluate pressure values at different points in the abdominal cavity during NPWT in experimental abdominal compartment syndrome (ACS) animal model; (2) Methods: In this study (permission Nr. 13/2014/UDCAW), 27 Hungahib pigs (15.4–20.2 kg) were operated on. ACS was generated by implanting a plastic bag in the abdomen through mini-laparotomy and filled with 2100–3300 mL saline solution (37 °C) to an intraabdominal pressure (IAP) of 30 mmHg. After 3 h, NPWT (Vivano Med® Abdominal Kit, Paul Hartmann AG, Germany) or a Bogota bag was applied. The NPWT group was divided into −50, −100 and −150 mmHg suction groups. Pressure distribution to the abdominal cavity was monitored at 6 different points of the abdomen via a multichannel pressure monitoring system; (3) Results: The absolute pressure levels were significantly higher above than below the protective layer. The values of the pressure were similar in the midline and laterally. Amongst the bowels, the pressure values changed periodically between 0 and −12 mmHg which might be caused by peristaltic movements; (4) Conclusions: The porcine model of the present study seems to be well applicable for investigating ACS and NPWT. It was possible to provide valuable information for clinicians. The pressure was well distributed by the protective layer to the lateral parts of the abdomen and this phenomenon did not change considerably during the therapy. Full article
(This article belongs to the Special Issue Force and Pressure Based Sensing Medical Application)
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20 pages, 22613 KiB  
Article
Enhancing Perception with Tactile Object Recognition in Adaptive Grippers for Human–Robot Interaction
by Juan M. Gandarias, Jesús M. Gómez-de-Gabriel and Alfonso J. García-Cerezo
Sensors 2018, 18(3), 692; https://doi.org/10.3390/s18030692 - 26 Feb 2018
Cited by 48 | Viewed by 8907
Abstract
The use of tactile perception can help first response robotic teams in disaster scenarios, where visibility conditions are often reduced due to the presence of dust, mud, or smoke, distinguishing human limbs from other objects with similar shapes. Here, the integration of the [...] Read more.
The use of tactile perception can help first response robotic teams in disaster scenarios, where visibility conditions are often reduced due to the presence of dust, mud, or smoke, distinguishing human limbs from other objects with similar shapes. Here, the integration of the tactile sensor in adaptive grippers is evaluated, measuring the performance of an object recognition task based on deep convolutional neural networks (DCNNs) using a flexible sensor mounted in adaptive grippers. A total of 15 classes with 50 tactile images each were trained, including human body parts and common environment objects, in semi-rigid and flexible adaptive grippers based on the fin ray effect. The classifier was compared against the rigid configuration and a support vector machine classifier (SVM). Finally, a two-level output network has been proposed to provide both object-type recognition and human/non-human classification. Sensors in adaptive grippers have a higher number of non-null tactels (up to 37% more), with a lower mean of pressure values (up to 72% less) than when using a rigid sensor, with a softer grip, which is needed in physical human–robot interaction (pHRI). A semi-rigid implementation with 95.13% object recognition rate was chosen, even though the human/non-human classification had better results (98.78%) with a rigid sensor. Full article
(This article belongs to the Special Issue Force and Pressure Based Sensing Medical Application)
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13 pages, 2946 KiB  
Article
Compact Hip-Force Sensor for a Gait-Assistance Exoskeleton System
by Hyundo Choi, Keehong Seo, Seungyong Hyung, Youngbo Shim and Soo-Chul Lim
Sensors 2018, 18(2), 566; https://doi.org/10.3390/s18020566 - 13 Feb 2018
Cited by 33 | Viewed by 9994
Abstract
In this paper, we propose a compact force sensor system for a hip-mounted exoskeleton for seniors with difficulties in walking due to muscle weakness. It senses and monitors the delivered force and power of the exoskeleton for motion control and taking urgent safety [...] Read more.
In this paper, we propose a compact force sensor system for a hip-mounted exoskeleton for seniors with difficulties in walking due to muscle weakness. It senses and monitors the delivered force and power of the exoskeleton for motion control and taking urgent safety action. Two FSR (force-sensitive resistors) sensors are used to measure the assistance force when the user is walking. The sensor system directly measures the interaction force between the exoskeleton and the lower limb of the user instead of a previously reported force-sensing method, which estimated the hip assistance force from the current of the motor and lookup tables. Furthermore, the sensor system has the advantage of generating torque in the walking-assistant actuator based on directly measuring the hip-assistance force. Thus, the gait-assistance exoskeleton system can control the delivered power and torque to the user. The force sensing structure is designed to decouple the force caused by hip motion from other directional forces to the sensor so as to only measure that force. We confirmed that the hip-assistance force could be measured with the proposed prototype compact force sensor attached to a thigh frame through an experiment with a real system. Full article
(This article belongs to the Special Issue Force and Pressure Based Sensing Medical Application)
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16 pages, 4817 KiB  
Article
Monitoring Walker Assistive Devices: A Novel Approach Based on Load Cells and Optical Distance Measurements
by Vítor Viegas, J. M. Dias Pereira, Octavian Postolache and Pedro Silva Girão
Sensors 2018, 18(2), 540; https://doi.org/10.3390/s18020540 - 10 Feb 2018
Cited by 6 | Viewed by 4367
Abstract
This paper presents a measurement system intended to monitor the usage of walker assistive devices. The goal is to guide the user in the correct use of the device in order to prevent risky situations and maximize comfort. Two risk indicators are defined: [...] Read more.
This paper presents a measurement system intended to monitor the usage of walker assistive devices. The goal is to guide the user in the correct use of the device in order to prevent risky situations and maximize comfort. Two risk indicators are defined: one related to force unbalance and the other related to motor incoordination. Force unbalance is measured by load cells attached to the walker legs, while motor incoordination is estimated by synchronizing force measurements with distance data provided by an optical sensor. The measurement system is equipped with a Bluetooth link that enables local supervision on a computer or tablet. Calibration and experimental results are included in the paper. Full article
(This article belongs to the Special Issue Force and Pressure Based Sensing Medical Application)
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18 pages, 2428 KiB  
Article
Neuromorphic Vibrotactile Stimulation of Fingertips for Encoding Object Stiffness in Telepresence Sensory Substitution and Augmentation Applications
by Francesca Sorgini, Luca Massari, Jessica D’Abbraccio, Eduardo Palermo, Arianna Menciassi, Petar B. Petrovic, Alberto Mazzoni, Maria Chiara Carrozza, Fiona N. Newell and Calogero M. Oddo
Sensors 2018, 18(1), 261; https://doi.org/10.3390/s18010261 - 17 Jan 2018
Cited by 19 | Viewed by 6175
Abstract
We present a tactile telepresence system for real-time transmission of information about object stiffness to the human fingertips. Experimental tests were performed across two laboratories (Italy and Ireland). In the Italian laboratory, a mechatronic sensing platform indented different rubber samples. Information about rubber [...] Read more.
We present a tactile telepresence system for real-time transmission of information about object stiffness to the human fingertips. Experimental tests were performed across two laboratories (Italy and Ireland). In the Italian laboratory, a mechatronic sensing platform indented different rubber samples. Information about rubber stiffness was converted into on-off events using a neuronal spiking model and sent to a vibrotactile glove in the Irish laboratory. Participants discriminated the variation of the stiffness of stimuli according to a two-alternative forced choice protocol. Stiffness discrimination was based on the variation of the temporal pattern of spikes generated during the indentation of the rubber samples. The results suggest that vibrotactile stimulation can effectively simulate surface stiffness when using neuronal spiking models to trigger vibrations in the haptic interface. Specifically, fractional variations of stiffness down to 0.67 were significantly discriminated with the developed neuromorphic haptic interface. This is a performance comparable, though slightly worse, to the threshold obtained in a benchmark experiment evaluating the same set of stimuli naturally with the own hand. Our paper presents a bioinspired method for delivering sensory feedback about object properties to human skin based on contingency–mimetic neuronal models, and can be useful for the design of high performance haptic devices. Full article
(This article belongs to the Special Issue Force and Pressure Based Sensing Medical Application)
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19 pages, 2095 KiB  
Article
Data-Driven Modeling and Rendering of Force Responses from Elastic Tool Deformation
by Arsen Abdulali, Ruslan Rakhmatov, Tatyana Ogay and Seokhee Jeon
Sensors 2018, 18(1), 237; https://doi.org/10.3390/s18010237 - 15 Jan 2018
Cited by 11 | Viewed by 4871
Abstract
This article presents a new data-driven model design for rendering force responses from elastic tool deformation. The new design incorporates a six-dimensional input describing the initial position of the contact, as well as the state of the tool deformation. The input-output relationship of [...] Read more.
This article presents a new data-driven model design for rendering force responses from elastic tool deformation. The new design incorporates a six-dimensional input describing the initial position of the contact, as well as the state of the tool deformation. The input-output relationship of the model was represented by a radial basis functions network, which was optimized based on training data collected from real tool-surface contact. Since the input space of the model is represented in the local coordinate system of a tool, the model is independent of recording and rendering devices and can be easily deployed to an existing simulator. The model also supports complex interactions, such as self and multi-contact collisions. In order to assess the proposed data-driven model, we built a custom data acquisition setup and developed a proof-of-concept rendering simulator. The simulator was evaluated through numerical and psychophysical experiments with four different real tools. The numerical evaluation demonstrated the perceptual soundness of the proposed model, meanwhile the user study revealed the force feedback of the proposed simulator to be realistic. Full article
(This article belongs to the Special Issue Force and Pressure Based Sensing Medical Application)
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11 pages, 9329 KiB  
Article
Surgical Dynamometer to Simultaneously Measure the Tension Forces and the Distance between Wound Edges during the Closure of a Laparotomy
by Joan Roca, Miquel Nogués, Rafael Villalobos, María Carmen Mías, Martí Comellas, Cristina Gas and Jorge Juan Olsina
Sensors 2018, 18(1), 189; https://doi.org/10.3390/s18010189 - 11 Jan 2018
Cited by 5 | Viewed by 4567
Abstract
The closure of the abdominal wall after making a laparotomy is a major challenge for surgeons, since a significant percentage of closures fail and incisional hernias rise. The suture has to withstand the forces required to close the incision, while not hindering the [...] Read more.
The closure of the abdominal wall after making a laparotomy is a major challenge for surgeons, since a significant percentage of closures fail and incisional hernias rise. The suture has to withstand the forces required to close the incision, while not hindering the adequate wound healing progression. Currently, there is no surgical measuring device that could be used to determine the required closing forces, which can be very different depending on the patient. This paper presents a dynamometer to measure the tension forces to be applied while closing a surgical incision, and it simultaneously measures the distance between wound edges. It is a compass-like instrument. A mechanism between the two legs incorporates a load cell, whose signal is read by an electronic device that computes the values of the tension forces between wound edges. An angular position sensor at the pin joint between legs provides the distance between both sides of the incision. Measuring capabilities of the instrument prototype were verified at the laboratory. Thereafter, its functionality was demonstrated in experimental surgery tests. Therefore, the instrument could be very useful in clinical applications, assisting personalized surgical techniques. Full article
(This article belongs to the Special Issue Force and Pressure Based Sensing Medical Application)
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3552 KiB  
Article
Ex Vivo Evaluation of Cementless Acetabular Cup Stability Using Impact Analyses with a Hammer Instrumented with Strain Sensors
by Antoine Tijou, Giuseppe Rosi, Philippe Hernigou, Charles-Henri Flouzat-Lachaniette and Guillaume Haïat
Sensors 2018, 18(1), 62; https://doi.org/10.3390/s18010062 - 27 Dec 2017
Cited by 11 | Viewed by 4097
Abstract
The acetabular cup (AC) implant stability is determinant for the success of cementless hip arthroplasty. A method based on the analysis of the impact force applied during the press-fit insertion of the AC implant using a hammer instrumented with a force sensor was [...] Read more.
The acetabular cup (AC) implant stability is determinant for the success of cementless hip arthroplasty. A method based on the analysis of the impact force applied during the press-fit insertion of the AC implant using a hammer instrumented with a force sensor was developed to assess the AC implant stability. The aim of the present study was to investigate the performance of a method using a hammer equipped with strain sensors to retrieve the AC implant stability. Different AC implants were inserted in five bovine samples with different stability conditions leading to 57 configurations. The AC implant was impacted 16 times by the two hammers consecutively. For each impact; an indicator IS (respectively IF) determined by analyzing the time variation of the signal corresponding to the averaged strain (respectively force) obtained with the stress (respectively strain) hammer was calculated. The pull-out force F was measured for each configuration. F was significantly correlated with IS (R2 = 0.79) and IF (R2 = 0.80). The present method has the advantage of not modifying the shape of the hammer that can be sterilized easily. This study opens new paths towards the development of a decision support system to assess the AC implant stability. Full article
(This article belongs to the Special Issue Force and Pressure Based Sensing Medical Application)
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4282 KiB  
Article
Evaluation of Pressure Capacitive Sensors for Application in Grasping and Manipulation Analysis
by Paola Pessia, Francesca Cordella, Emiliano Schena, Angelo Davalli, Rinaldo Sacchetti and Loredana Zollo
Sensors 2017, 17(12), 2846; https://doi.org/10.3390/s17122846 - 08 Dec 2017
Cited by 5 | Viewed by 3952
Abstract
The analysis of the human grasping and manipulation capabilities is paramount for investigating human sensory-motor control and developing prosthetic and robotic hands resembling the human ones. A viable solution to perform this analysis is to develop instrumented objects measuring the interaction forces with [...] Read more.
The analysis of the human grasping and manipulation capabilities is paramount for investigating human sensory-motor control and developing prosthetic and robotic hands resembling the human ones. A viable solution to perform this analysis is to develop instrumented objects measuring the interaction forces with the hand. In this context, the performance of the sensors embedded in the objects is crucial. This paper focuses on the experimental characterization of a class of capacitive pressure sensors suitable for biomechanical analysis. The analysis was performed in three loading conditions (Distributed load, 9 Tips load, and Wave-shaped load, thanks to three different inter-elements) via a traction/compression testing machine. Sensor assessment was also carried out under human- like grasping condition by placing a silicon material with the same properties of prosthetic cosmetic gloves in between the sensor and the inter-element in order to simulate the human skin. Data show that the input–output relationship of the analyzed, sensor is strongly influenced by both the loading condition (i.e., type of inter-element) and the grasping condition (with or without the silicon material). This needs to be taken into account to avoid significant measurement error. To go over this hurdle, the sensors have to be calibrated under each specific condition in order to apply suitable corrections to the sensor output and significantly improve the measurement accuracy. Full article
(This article belongs to the Special Issue Force and Pressure Based Sensing Medical Application)
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5403 KiB  
Article
Assessment of Embedded Conjugated Polymer Sensor Arrays for Potential Load Transmission Measurement in Orthopaedic Implants
by Carolina Micolini, Frederick Benjamin Holness, James A. Johnson and Aaron David Price
Sensors 2017, 17(12), 2768; https://doi.org/10.3390/s17122768 - 29 Nov 2017
Cited by 7 | Viewed by 4811
Abstract
Load transfer through orthopaedic joint implants is poorly understood. The longer-term outcomes of these implants are just starting to be studied, making it imperative to monitor contact loads across the entire joint implant interface to elucidate the force transmission and distribution mechanisms exhibited [...] Read more.
Load transfer through orthopaedic joint implants is poorly understood. The longer-term outcomes of these implants are just starting to be studied, making it imperative to monitor contact loads across the entire joint implant interface to elucidate the force transmission and distribution mechanisms exhibited by these implants in service. This study proposes and demonstrates the design, implementation, and characterization of a 3D-printed smart polymer sensor array using conductive polyaniline (PANI) structures embedded within a polymeric parent phase. The piezoresistive characteristics of PANI were investigated to characterize the sensing behaviour inherent to these embedded pressure sensor arrays, including the experimental determination of the stable response of PANI to continuous loading, stability throughout the course of loading and unloading cycles, and finally sensor repeatability and linearity in response to incremental loading cycles. This specially developed multi-material additive manufacturing process for PANI is shown be an attractive approach for the fabrication of implant components having embedded smart-polymer sensors, which could ultimately be employed for the measurement and analysis of joint loads in orthopaedic implants for in vitro testing. Full article
(This article belongs to the Special Issue Force and Pressure Based Sensing Medical Application)
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7976 KiB  
Article
Towards Robot-Assisted Retinal Vein Cannulation: A Motorized Force-Sensing Microneedle Integrated with a Handheld Micromanipulator †
by Berk Gonenc, Jeremy Chae, Peter Gehlbach, Russell H. Taylor and Iulian Iordachita
Sensors 2017, 17(10), 2195; https://doi.org/10.3390/s17102195 - 23 Sep 2017
Cited by 26 | Viewed by 7552
Abstract
Retinal vein cannulation is a technically demanding surgical procedure where therapeutic agents are injected into the retinal veins to treat occlusions. The clinical feasibility of this approach has been largely limited by the technical challenges associated with performing the procedure. Among the challenges [...] Read more.
Retinal vein cannulation is a technically demanding surgical procedure where therapeutic agents are injected into the retinal veins to treat occlusions. The clinical feasibility of this approach has been largely limited by the technical challenges associated with performing the procedure. Among the challenges to successful vein cannulation are identifying the moment of venous puncture, achieving cannulation of the micro-vessel, and maintaining cannulation throughout drug delivery. Recent advances in medical robotics and sensing of tool-tissue interaction forces have the potential to address each of these challenges as well as to prevent tissue trauma, minimize complications, diminish surgeon effort, and ultimately promote successful retinal vein cannulation. In this paper, we develop an assistive system combining a handheld micromanipulator, called “Micron”, with a force-sensing microneedle. Using this system, we examine two distinct methods of precisely detecting the instant of venous puncture. This is based on measured tool-tissue interaction forces and also the tracked position of the needle tip. In addition to the existing tremor canceling function of Micron, a new control method is implemented to actively compensate unintended movements of the operator, and to keep the cannulation device securely inside the vein following cannulation. To demonstrate the capabilities and performance of our uniquely upgraded system, we present a multi-user artificial phantom study with subjects from three different surgical skill levels. Results show that our puncture detection algorithm, when combined with the active positive holding feature enables sustained cannulation which is most evident in smaller veins. Notable is that the active holding function significantly attenuates tool motion in the vein, thereby reduces the trauma during cannulation. Full article
(This article belongs to the Special Issue Force and Pressure Based Sensing Medical Application)
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5820 KiB  
Article
Evaluation of Flexible Force Sensors for Pressure Monitoring in Treatment of Chronic Venous Disorders
by Suresh Parmar, Iryna Khodasevych and Olga Troynikov
Sensors 2017, 17(8), 1923; https://doi.org/10.3390/s17081923 - 21 Aug 2017
Cited by 55 | Viewed by 8656
Abstract
The recent use of graduated compression therapy for treatment of chronic venous disorders such as leg ulcers and oedema has led to considerable research interest in flexible and low-cost force sensors. Properly applied low pressure during compression therapy can substantially improve the treatment [...] Read more.
The recent use of graduated compression therapy for treatment of chronic venous disorders such as leg ulcers and oedema has led to considerable research interest in flexible and low-cost force sensors. Properly applied low pressure during compression therapy can substantially improve the treatment of chronic venous disorders. However, achievement of the recommended low pressure levels and its accurate determination in real-life conditions is still a challenge. Several thin and flexible force sensors, which can also function as pressure sensors, are commercially available, but their real-life sensing performance has not been evaluated. Moreover, no researchers have reported information on sensor performance during static and dynamic loading within the realistic test conditions required for compression therapy. This research investigated the sensing performance of five low-cost commercial pressure sensors on a human-leg-like test apparatus and presents quantitative results on the accuracy and drift behaviour of these sensors in both static and dynamic conditions required for compression therapy. Extensive experimental work on this new human-leg-like test setup demonstrated its utility for evaluating the sensors. Results showed variation in static and dynamic sensing performance, including accuracy and drift characteristics. Only one commercially available pressure sensor was found to reliably deliver accuracy of 95% and above for all three test pressure points of 30, 50 and 70 mmHg. Full article
(This article belongs to the Special Issue Force and Pressure Based Sensing Medical Application)
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4254 KiB  
Article
A Compressed Sensing Based Method for Reducing the Sampling Time of A High Resolution Pressure Sensor Array System
by Chenglu Sun, Wei Li and Wei Chen
Sensors 2017, 17(8), 1848; https://doi.org/10.3390/s17081848 - 10 Aug 2017
Cited by 11 | Viewed by 9111
Abstract
For extracting the pressure distribution image and respiratory waveform unobtrusively and comfortably, we proposed a smart mat which utilized a flexible pressure sensor array, printed electrodes and novel soft seven-layer structure to monitor those physiological information. However, in order to obtain high-resolution pressure [...] Read more.
For extracting the pressure distribution image and respiratory waveform unobtrusively and comfortably, we proposed a smart mat which utilized a flexible pressure sensor array, printed electrodes and novel soft seven-layer structure to monitor those physiological information. However, in order to obtain high-resolution pressure distribution and more accurate respiratory waveform, it needs more time to acquire the pressure signal of all the pressure sensors embedded in the smart mat. In order to reduce the sampling time while keeping the same resolution and accuracy, a novel method based on compressed sensing (CS) theory was proposed. By utilizing the CS based method, 40% of the sampling time can be decreased by means of acquiring nearly one-third of original sampling points. Then several experiments were carried out to validate the performance of the CS based method. While less than one-third of original sampling points were measured, the correlation degree coefficient between reconstructed respiratory waveform and original waveform can achieve 0.9078, and the accuracy of the respiratory rate (RR) extracted from the reconstructed respiratory waveform can reach 95.54%. The experimental results demonstrated that the novel method can fit the high resolution smart mat system and be a viable option for reducing the sampling time of the pressure sensor array. Full article
(This article belongs to the Special Issue Force and Pressure Based Sensing Medical Application)
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17242 KiB  
Article
Energy-Based Metrics for Arthroscopic Skills Assessment
by Behnaz Poursartip, Marie-Eve LeBel, Laura C. McCracken, Abelardo Escoto, Rajni V. Patel, Michael D. Naish and Ana Luisa Trejos
Sensors 2017, 17(8), 1808; https://doi.org/10.3390/s17081808 - 05 Aug 2017
Cited by 7 | Viewed by 4073
Abstract
Minimally invasive skills assessment methods are essential in developing efficient surgical simulators and implementing consistent skills evaluation. Although numerous methods have been investigated in the literature, there is still a need to further improve the accuracy of surgical skills assessment. Energy expenditure can [...] Read more.
Minimally invasive skills assessment methods are essential in developing efficient surgical simulators and implementing consistent skills evaluation. Although numerous methods have been investigated in the literature, there is still a need to further improve the accuracy of surgical skills assessment. Energy expenditure can be an indication of motor skills proficiency. The goals of this study are to develop objective metrics based on energy expenditure, normalize these metrics, and investigate classifying trainees using these metrics. To this end, different forms of energy consisting of mechanical energy and work were considered and their values were divided by the related value of an ideal performance to develop normalized metrics. These metrics were used as inputs for various machine learning algorithms including support vector machines (SVM) and neural networks (NNs) for classification. The accuracy of the combination of the normalized energy-based metrics with these classifiers was evaluated through a leave-one-subject-out cross-validation. The proposed method was validated using 26 subjects at two experience levels (novices and experts) in three arthroscopic tasks. The results showed that there are statistically significant differences between novices and experts for almost all of the normalized energy-based metrics. The accuracy of classification using SVM and NN methods was between 70% and 95% for the various tasks. The results show that the normalized energy-based metrics and their combination with SVM and NN classifiers are capable of providing accurate classification of trainees. The assessment method proposed in this study can enhance surgical training by providing appropriate feedback to trainees about their level of expertise and can be used in the evaluation of proficiency. Full article
(This article belongs to the Special Issue Force and Pressure Based Sensing Medical Application)
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1491 KiB  
Article
Compact Eucapnic Voluntary Hyperpnoea Apparatus for Exercise-Induced Respiratory Disease Detection
by Lulu Wang and Ahmed Al-Jumaily
Sensors 2017, 17(5), 1139; https://doi.org/10.3390/s17051139 - 16 May 2017
Cited by 1 | Viewed by 4215
Abstract
Eucapnic voluntary hyperpnoea (EVH) challenge provides objective criteria for exercise-induced asthma (EIA) or exercise-induced bronchoconstriction (EIB), and it was recommended to justify the use of inhaled β2-agonists by athletes for the Olympics. This paper presents the development of a compact and [...] Read more.
Eucapnic voluntary hyperpnoea (EVH) challenge provides objective criteria for exercise-induced asthma (EIA) or exercise-induced bronchoconstriction (EIB), and it was recommended to justify the use of inhaled β2-agonists by athletes for the Olympics. This paper presents the development of a compact and easy-to-use EVH apparatus for assessing EIB in human subjects. The compact apparatus has been validated on human subjects and the results have been compared to the conventional EVH system. Twenty-two swimmers, including eleven healthy subjects and eleven subjects who had been physician-diagnosed with asthma, were recruited from sport and recreation centers throughout Auckland, New Zealand. Each subject performed two EVH challenge tests using the proposed breathing apparatus and the conventional Phillips EVH apparatus on separate days, respectively. Forced expiratory volume in one second (FEV1) was measured before and after the challenges. A reduction in FEV1 of 10% or more was considered positive. Of the eleven subjects who were previously diagnosed with asthma, EIB was present in all subjects (100%) in the compact EVH group, while it was presented in ten subjects (90.91%) in the conventional EVH challenge group. Of the eleven healthy subjects, EIB was present in one subject (4.55%) in the compact EVH group, while it was not present in the conventional EVH group. Experimental results showed that the compact EVH system has potential to become an alternative tool for EIB detection. Full article
(This article belongs to the Special Issue Force and Pressure Based Sensing Medical Application)
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8587 KiB  
Article
Mechanics Based Tomography: A Preliminary Feasibility Study
by Yue Mei, Sicheng Wang, Xin Shen, Stephen Rabke and Sevan Goenezen
Sensors 2017, 17(5), 1075; https://doi.org/10.3390/s17051075 - 09 May 2017
Cited by 15 | Viewed by 4373
Abstract
We present a non-destructive approach to sense inclusion objects embedded in a solid medium remotely from force sensors applied to the medium and boundary displacements that could be measured via a digital image correlation system using a set of cameras. We provide a [...] Read more.
We present a non-destructive approach to sense inclusion objects embedded in a solid medium remotely from force sensors applied to the medium and boundary displacements that could be measured via a digital image correlation system using a set of cameras. We provide a rationale and strategy to uniquely identify the heterogeneous sample composition based on stiffness (here, shear modulus) maps. The feasibility of this inversion scheme is tested with simulated experiments that could have clinical relevance in diagnostic imaging (e.g., tumor detection) or could be applied to engineering materials. No assumptions are made on the shape or stiffness quantity of the inclusions. We observe that the novel inversion method using solely boundary displacements and force measurements performs well in recovering the heterogeneous material/tissue composition that consists of one and two stiff inclusions embedded in a softer background material. Furthermore, the target shear modulus value for the stiffer inclusion region is underestimated and the inclusion size is overestimated when incomplete boundary displacements on some part of the boundary are utilized. For displacements measured on the entire boundary, the shear modulus reconstruction improves significantly. Additionally, we observe that with increasing number of displacement data sets utilized in solving the inverse problem, the quality of the mapped shear moduli improves. We also analyze the sensitivity of the shear modulus maps on the noise level varied between 0.1% and 5% white Gaussian noise in the boundary displacements, force and corresponding displacement indentation. Finally, a sensitivity analysis of the recovered shear moduli to the depth, stiffness and the shape of the stiff inclusion is performed. We conclude that this approach has potential as a novel imaging modality and refer to it as Mechanics Based Tomography (MBT). Full article
(This article belongs to the Special Issue Force and Pressure Based Sensing Medical Application)
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Review

Jump to: Research, Other

38 pages, 5115 KiB  
Review
Force Modeling, Identification, and Feedback Control of Robot-Assisted Needle Insertion: A Survey of the Literature
by Chongjun Yang, Yu Xie, Shuang Liu and Dong Sun
Sensors 2018, 18(2), 561; https://doi.org/10.3390/s18020561 - 12 Feb 2018
Cited by 68 | Viewed by 17419
Abstract
Robot-assisted surgery is of growing interest in the surgical and engineering communities. The use of robots allows surgery to be performed with precision using smaller instruments and incisions, resulting in shorter healing times. However, using current technology, an operator cannot directly feel the [...] Read more.
Robot-assisted surgery is of growing interest in the surgical and engineering communities. The use of robots allows surgery to be performed with precision using smaller instruments and incisions, resulting in shorter healing times. However, using current technology, an operator cannot directly feel the operation because the surgeon-instrument and instrument-tissue interaction force feedbacks are lost during needle insertion. Advancements in force feedback and control not only help reduce tissue deformation and needle deflection but also provide the surgeon with better control over the surgical instruments. The goal of this review is to summarize the key components surrounding the force feedback and control during robot-assisted needle insertion. The literature search was conducted during the middle months of 2017 using mainstream academic search engines with a combination of keywords relevant to the field. In total, 166 articles with valuable contents were analyzed and grouped into five related topics. This survey systemically summarizes the state-of-the-art force control technologies for robot-assisted needle insertion, such as force modeling, measurement, the factors that influence the interaction force, parameter identification, and force control algorithms. All studies show force control is still at its initial stage. The influence factors, needle deflection or planning remain open for investigation in future. Full article
(This article belongs to the Special Issue Force and Pressure Based Sensing Medical Application)
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15 pages, 2008 KiB  
Review
Intracranial Pressure Monitoring—Review and Avenues for Development
by Maya Harary, Rianne G. F. Dolmans and William B. Gormley
Sensors 2018, 18(2), 465; https://doi.org/10.3390/s18020465 - 05 Feb 2018
Cited by 105 | Viewed by 19060
Abstract
Intracranial pressure (ICP) monitoring is a staple of neurocritical care. The most commonly used current methods of monitoring in the acute setting include fluid-based systems, implantable transducers and Doppler ultrasonography. It is well established that management of elevated ICP is critical for clinical [...] Read more.
Intracranial pressure (ICP) monitoring is a staple of neurocritical care. The most commonly used current methods of monitoring in the acute setting include fluid-based systems, implantable transducers and Doppler ultrasonography. It is well established that management of elevated ICP is critical for clinical outcomes. However, numerous studies show that current methods of ICP monitoring cannot reliably define the limit of the brain’s intrinsic compensatory capacity to manage increases in pressure, which would allow for proactive ICP management. Current work in the field hopes to address this gap by harnessing live-streaming ICP pressure-wave data and a multimodal integration with other physiologic measures. Additionally, there is continued development of non-invasive ICP monitoring methods for use in specific clinical scenarios. Full article
(This article belongs to the Special Issue Force and Pressure Based Sensing Medical Application)
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Other

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2 pages, 714 KiB  
Erratum
Erratum: Mei, Y., et al. Mechanics Based Tomography: A Preliminary Feasibility Study. Sensors 2017, 17, 1075
by Yue Mei, Sicheng Wang, Xin Shen, Stephen Rabke and Sevan Goenezen
Sensors 2018, 18(2), 384; https://doi.org/10.3390/s18020384 - 29 Jan 2018
Cited by 2 | Viewed by 3078
Abstract
The authors wish to correct Figures 12 and 14 in their paper published in Sensors [1], doi:10.3390/s17051075, https://www.mdpi.com/1424-8220/17/5/1075[...] Full article
(This article belongs to the Special Issue Force and Pressure Based Sensing Medical Application)
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