Probe Movement Research Articles

Optimizing the uncertainty of measurements on a coordinate measuring machine when controlling complex geometric surfaces

The object of this study is the process of optimizing measurement uncertainty on a coordinate measuring machine (CMM) when inspecting complex geometric surfaces. The problem addressed was insufficient accuracy and efficiency of measurements of complex parts on CMMs under production conditions. A method for optimizing measurement uncertainty has been devised, which includes a mathematical model of the measurement process and an adaptive algorithm for optimizing the control strategy, based on the Monte Carlo method. The model takes into account the geometry of surfaces and CMM characteristics, while the algorithm dynamically adjusts measurement parameters. The results demonstrate a reduction in measurement uncertainty by 15–20 % and a reduction in inspection time by 10–12 % compared to conventional methods. This is achieved by taking into account the specificity of complex surface geometry and an adaptive approach. The uniqueness of the developed method is the ability to automatically adapt to different types of CMMs and measured objects, optimizing the number and location of measurement points, the speed of probe movement, and its contact force with the surface. The method takes into account not only the geometric parameters of objects but also the characteristics of the CMM itself, which allows for high accuracy. The method is particularly effective for parts with complex geometry, in which conventional methods often lead to significant errors. Practical application is possible at machine-building enterprises for quality control of complex parts, especially in serial production. The implementation of the developed method allows for improving product quality and reducing production costs by 8–10 % due to optimization of the control process and reduction of defects

Selected Errors in Spatial Measurements of Surface Asperities.

This work presents issues related to selected errors accompanying spatial measurements of surface roughness using contact profilometry. The influence of internal heat sources, such as engines or control electronics, on the thermal expansion of the drive responsible for the measurement probe's movement in the X-axis direction was investigated. In terms of starting measurements on a thermally unstable device, the synchronization error of individual profile paths was 16.1 µm. Based on thermographic studies, the time required for full thermal stabilization of this drive was determined to be 6-12 h from when the device was turned on. It was demonstrated that thermal stabilization of the profilometer significantly reduced positioning errors of the measurement probe on the X-axis. Thermal stabilization time should be determined individually for a specific device variant. This research also determined how changes in the center of gravity caused by the measurement probe's movement affected the overall rigidity of the profilometer structure and the leveling of the tested surface. Laser interferometry was used for this purpose. The determined vulnerability of the profilometer structure was 0.8 µm for a measurement section of 25 mm. Understanding the described relationships will reduce errors associated with conducting measurements and preparing equipment for tests. Additionally, it will enable the correct evaluation of surface geometry.

Freehand 3D Ultrasound Imaging Based on Probe-mounted Vision and IMU System

ObjectivesFreehand three-dimensional (3D) ultrasound (US) is of great significance for clinical diagnosis and treatment, it is often achieved with the aid of external devices (optical and/or electromagnetic, etc.) that monitor the location and orientation of the US probe. However, this external monitoring is often impacted by imaging environment such as optical occlusions and/or electromagnetic (EM) interference. MethodsTo address the above issues, we integrated a binocular camera and an inertial measurement unit (IMU) on a US probe. Subsequently, we built a tight coupling model utilizing the unscented Kalman algorithm based on Lie groups (UKF-LG), combining vision and inertial information to infer the probe's movement, through which the position and orientation of the US image frame are calculated. Finally, the volume data was reconstructed with the voxel-based hole-filling method. ResultsThe experiments including calibration experiments, tracking performance evaluation, phantom scans, and real scenarios scans have been conducted. The results show that the proposed system achieved the accumulated frame position error of 3.78 mm and the orientation error of 0.36° and reconstructed 3D US images with high quality in both phantom and real scenarios. ConclusionsThe proposed method has been demonstrated to enhance the robustness and effectiveness of freehand 3D US. Follow-up research will focus on improving the accuracy and stability of multi-sensor fusion to make the system more practical in clinical environments.

RL-TEE: Autonomous Probe Guidance for Transesophageal Echocardiography Based on Attention-Augmented Deep Reinforcement Learning

Ultrasound image acquisition in conventional transesophageal echocardiography (TEE) requires complex manual operation of the probe in the esophagus based on the interpretation of ultrasound images and in-depth knowledge of the cardiac anatomy. In this work, we formulate the TEE probe guidance task as a reinforcement learning (RL) problem, and present the first learning-based solution to 3-DOF control of a TEE probe based on the ultrasound image feedback, named RL-TEE, in order to mimic the visual search and navigation strategies of expert echocardiographers. The probe-tissue interaction in TEE is carefully modeled in our framework by considering both the requirements for navigation towards the standard views and compliance in the esophageal environment. Furthermore, we propose a hybrid deep Q-network model that augments a convolutional neural network backbone with self-attention mechanisms to better capture spatial information in ultrasound images to guide navigation decisions. The presented methods are preliminarily validated in a TEE simulation environment built with data from 25 subjects to acquire four standard views of the heart. Our results show that the proposed method can effectively learn to accurately and compliantly guide the probe movement for TEE standard view acquisition tasks and has a good generalization ability to unseen patient data. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —The motivation of this paper is to realize 3-DOF movement guidance of a TEE probe to acquire the standard views of the heart based on the real-time images, which can be applied to existing robotic control systems or used to assist novice echocardiographers in TEE examination, thereby relieving operator workload and improving ease of use. This paper suggests a novel approach that uses the deep RL technique to achieve automatic interpretation of TEE images and intelligent guidance of the probe movement. The RL framework is designed to take into account both the navigation efficiency and compliance with the esophageal environment for the targeted intracorporeal application. A hybrid deep Q-network model that augments a convolutional neural network with attention mechanisms is designed to better capture spatial information from ultrasound images to predict the probe movement. The effectiveness of the framework is preliminarily validated in extensive experiments in a simulation environment built with real patient data. The proposed method can be applied in clinical use to provide real-time TEE probe guidance for novice echocardiographers, and can be integrated with a robotic system to fully automate the TEE acquisition, thereby relieving the doctors from tedious manual operation to focus on the diagnosis and treatment.

Change in economy of ultrasound probe motion among general medicine trainees

ObjectivesTo observe change in economy of 9 ultrasound probe movement metrics among internal medicine trainees during a 5-day training course in cardiac point of care ultrasound (POCUS).MethodsWe used a novel probe tracking device to record nine features of ultrasound probe movement, while trainees and experts optimized ultrasound clips on the same volunteer patients. These features included translational movements, gyroscopic movements (titling, rocking, and rotation), smoothness, total path length, and scanning time. We determined the adjusted difference between each trainee’s movements and the mean value of the experts’ movements for each patient. We then used a mixed effects model to trend average the adjusted differences between trainees and experts throughout the 5 days of the course.ResultsFifteen trainees were enrolled. Three echocardiographer technicians and the course director served as experts. Across 16 unique patients, 294 ultrasound clips were acquired. For all 9 movements, the adjusted difference between trainees and experts narrowed day-to-day (p value < 0.05), suggesting ongoing improvement during training. By the last day of the course, there were no statistically significant differences between trainees and experts in translational movement, gyroscopic movement, smoothness, or total path length; yet on average trainees took 28 s (95% CI [14.7–40.3] seconds) more to acquire a clip.ConclusionsWe detected improved ultrasound probe motion economy among internal medicine trainees during a 5-day training course in cardiac POCUS using an inexpensive probe tracking device. Objectively quantifying probe motion economy may help assess a trainee’s level of proficiency in this skill and individualize their POCUS training.

Adaptive Ultrasonic Full Matrix Capture Process for the Global Imaging of Complex Components with Curved Surfaces.

This work proposes a new global FD-RTM method to solve the problem of ultrasonic inspection of parts with complex geometric shapes. With this method, the frequency domain reverse time migration (FD-RTM) algorithm is used to adapt to the complex refraction of ultrasonic waves by the surface, while an interface solution algorithm based on tangent fitting is used to solve the interface position with high precision through the full matrix reception data. Based on high-precision interface information, a hybrid extrapolation algorithm and a situation-specific probe movement strategy are used to enable the probe to find the next sampling point according to the direction of the workpiece surface, allowing complex surface topography features to be identified without relying on the workpiece CAD drawing. This makes it possible to achieve the automated inspection of workpieces. To verify the proposed method's effectiveness, an aluminum alloy model with side-drilled holes (SDH) is used. The geometry of the model consists of multiple convex and concave surfaces. By comparing the local FD-RTM imaging with images synthesized using the entire scan path, it is shown that gFD-RTM improved the imaging performance. Compared with FD-RTM, the average signal-to-noise ratio of gFD-RTM was increased by 20%, and the array performance index (API) was reduced by 70%, indicating effective detection coverage.

Criteria for choosing the energy of micropulse transscleral cyclophotocoagulation

For a long time, the main parameter of micropulse cyclophotocoagulation (mTS-CPC) operation planning has been the calculated total energy. However, this indicator alone is not enough to determine more accurate correlations between exposure parameters and treatment outcomes.Purpose: to determine the criteria for choosing energy parameters to be used in mTS-CPC in refractory glaucoma patients.Material and methods. We propose a more reliable indicator of mTS-CPC clinical results, the energy flow, which is calculated from the speed of the probe movement. We developed and used a new strategy for conducting mTS-CPC: dividing the hemispheres of the ocular surface into 4 quadrants for a better control of the light guide movement while maintaining the selected speed. The standardized protocol for conducting the procedure has been modified so that the calculated energy flow is 121.8 J/cm2.Results. The evaluation of the treatment results of 140 patients according to the Kaplan Meier criteria showed the success of the treatment. IOP fell by 30 %, as compared with the baseline in the advanced stage, and by 20 % in the terminal stage, causing no complications. 12 months after the follow-up start, IOP compensation was noted in 81.3 % of cases.Conclusion. The presented modification of mTS-CPC using the energy flow parameters makes it possible to unify the technology of laser treatment, and the results obtained demonstrate a good and uncomplicated hypotensive effect. The availability of standardized energy indicators allows for a selective treatment tactics, depending on the individual characteristics of glaucomatous patients.

Deep Learning Image Recognition-Assisted Atomic Force Microscopy for Single-Cell Efficient Mechanics in Co-culture Environments.

Atomic force microscopy (AFM)-based force spectroscopy assay has become an important method for characterizing the mechanical properties of single living cells under aqueous conditions, but a disadvantage is its reliance on manual operation and experience as well as the resulting low throughput. Particularly, providing a capacity to accurately identify the type of the cell grown in co-culture environments without the need of fluorescent labeling will further facilitate the applications of AFM in life sciences. Here, we present a study of deep learning image recognition-assisted AFM, which not only enables fluorescence-independent recognition of the identity of single co-cultured cells but also allows efficient downstream AFM force measurements of the identified cells. With the use of the deep learning-based image recognition model, the viability and type of individual cells grown in co-culture environments were identified directly from the optical bright-field images, which were confirmed by the following cell growth and fluorescent labeling results. Based on the image recognition results, the positional relationship between the AFM probe and the targeted cell was automatically determined, allowing the precise movement of the AFM probe to the target cell to perform force measurements. The experimental results show that the presented method was applicable not only to the conventional (microsphere-modified) AFM probe used in AFM indentation assay for measuring the Young's modulus of single co-cultured cells but also to the single-cell probe used in AFM-based single-cell force spectroscopy (SCFS) assay for measuring the adhesion forces of single co-cultured cells. The study illustrates deep learning imaging recognition-assisted AFM as a promising approach for label-free and high-throughput detection of single-cell mechanics under co-culture conditions, which will facilitate unraveling the mechanical cues involved in cell-cell interactions in their native states at the single-cell level and will benefit the field of mechanobiology.

Characterization of food emulsions and dispersions based on nonlinear friction dynamics

AbstractMany foods are emulsions or dispersions containing lipids. The friction properties of foods are evaluated because they affect food texture and processability. Here, we evaluated the friction characteristics of 55 liquid or semisolid foods using a sinusoidal motion friction evaluation system to classify them based on friction dynamics. The contact surface was made to resemble a biological surface using agar gel, which exhibited a fractal structure, and the movement of the contact probe mimicked living movement by sinusoidal motion. The change in average friction coefficient (Δμ), static friction coefficient (Δμs) in a round trip, delay time (Δδ), and friction profile depended on the condition and rheological properties. Principal component analysis showed that all the friction parameters of Δμ, Δμs, Δδ, and the appearance ratio of the profile were involved in the principal components, Z1 and Z2 which are composite variables obtained by the contraction of many friction parameters in a principal component analysis. In addition, the foods were classified into three groups by cluster analysis using Z1 and Z2. The condition of the foods, rheological properties, and the presence or absence of lipids was the factors that defined each group.

Teaching point-of-care ultrasound using a serious game: a randomized controlled trial

BackgroundPoint-of-care ultrasound (POCUS) is an important diagnostic tool for internists. However, there are important barriers in learning POCUS, including lack of practice time and lack of experts for supervision. Alternative learning tools may assist in overcoming these barriers. A serious game is being developed specifically for teaching ultrasound. In this study, we assessed the use of a serious game in learning POCUS.MethodsUltrasound-native medical students were randomly assigned to the intervention group (N = 27) or the control group (N = 26). Both groups performed a real ultrasound on a volunteer after a brief introduction, but the intervention group played a serious game in advance. The endpoints were the assessments of the videos by experts (scoring quality of the probe movements) and the research team (counting probe movements), and probe movements measured with an accelerometer.ResultsThe intervention group completed the exam faster (247 s vs. 347 s, p = 0.006 (95% CI: [30.20;168.80]) and lifted the probe less frequently from the model (0.54 vs. 3.79, p = 0.001 (95% CI: [1.39;5.11]). Also, we found an in-game learning effect between levels, showing a 48% decrease in total playing time (p < 0.001), 36% reduction in attempts per coin (p = 0.007), a 33% reduction in total probe distance (p = 0.002), and a 61% decrease in contact moments (p < 0.001). However, there was no significant difference in expert score between the two groups.ConclusionThe serious game ‘Underwater’ is a fun and useful addition to traditional bedside ultrasound learning, which also may overcome one of the most important barriers in learning ultrasound: lack of supervised practice time. We show that the game improves real-practice probe handling with faster and more goal-oriented probe movements.

Patent umbilical artery in medial umbilical fold: Cadaveric study and clinical implications

Minimally invasive surgery has become one of the most accepted surgical options across the globe. In most laparoscopic surgeries, medial umbilical fold (MUF) containing the umbilical artery (UA) serves as an important landmark for creation of peritoneal flap. 50% of gynaecological laparoscopic injuries occur at the time of entry into the anterior abdominal wall, as it involves blind insertion of the trochar or veress needle in the peritoneal cavity. Any variation in the structures of the anterior abdominal wall may affect the placement location of the trocar, which is a crucial aspect to ease the surgeon’s ability to manoeuvre the abdominal cavity. The presence of cords and/or dense ligamentous structures in the anterior abdominal wall may complicate trocar insertion and restrict the probe movement during laparoscopic procedures. Hence, the aim of the present study was to classify and observe the variations in the MUF in the anterior abdominal wall.The cadavers in the study were formalin fixed through femoral artery perfusion method. Out of the 35 (23 males; 12 female) cadavers (70 MUF), studied, 34 cadavers (69 MUF) followed the pattern of the existing classification proposed by Tokar and Yucel, (2009). However, the right MUF of one male cadaver presented, patent umbilical artery (PUA) associated with a long mesentery. Based on safe presentations for laparoscopic exploration, MUF was given grades. Grades 0 and 1 were categorised as safe as compared to grade 2 and the novel variant observed, based on the morphology of MUF. No significant difference was noted in the occurrence of safe presentations of MUF amongst males and females.MUF with a patent vessel and a mesentery may cause technical difficulties to the surgeon by decreasing the laparoscopic port work space and obscuring the view of lateral pelvic wall during surgeries. Furthermore, persistent UA can compress the ureter and vas deferens resulting in myriad of symptoms ranging from unexplainable flank pain, hydronephrosis to male infertility. Awareness of such variants is of relevance to urologists in determining the cause of these unexplained symptoms and to surgeons in determining the site of safe trocar insertion. The findings also, highlight the fact that anterior abdominal wall anatomy is not mirror image on both the sides.

Gaze-probe joint guidance with multi-task learning in obstetric ultrasound scanning

In this work, we exploit multi-task learning to jointly predict the two decision-making processes of gaze movement and probe manipulation that an experienced sonographer would perform in routine obstetric scanning. A multimodal guidance framework, Multimodal-GuideNet, is proposed to detect the causal relationship between a real-world ultrasound video signal, synchronized gaze, and probe motion. The association between the multi-modality inputs is learned and shared through a modality-aware spatial graph that leverages useful cross-modal dependencies. By estimating the probability distribution of probe and gaze movements in real scans, the predicted guidance signals also allow inter- and intra-sonographer variations and avoid a fixed scanning path. We validate the new multi-modality approach on three types of obstetric scanning examinations, and the result consistently outperforms single-task learning under various guidance policies. To simulate sonographer’s attention on multi-structure images, we also explore multi-step estimation in gaze guidance, and its visual results show that the prediction allows multiple gaze centers that are substantially aligned with underlying anatomical structures.

An AI-powered navigation framework to achieve an automated acquisition of cardiac ultrasound images

Echocardiography is an effective tool for diagnosing cardiovascular disease. However, numerous challenges affect its accessibility, including skill requirements, workforce shortage, and sonographer strain. We introduce a navigation framework for the automated acquisition of echocardiography images, consisting of 3 modules: perception, intelligence, and control. The perception module contains an ultrasound probe, a probe actuator, and a locator camera. Information from this module is sent to the intelligence module, which grades the quality of an ultrasound image for different echocardiography views. The window search algorithm in the control module governs the decision-making process in probe movement, finding the best location based on known probe traversal positions and image quality. We conducted a series of simulations using the HeartWorks simulator to assess the proposed framework. This study achieved an accuracy of 99% for the image quality model, 96% for the probe locator model, and 99% for the view classification model, trained on an 80/20 training and testing split. We found that the best search area corresponds with general guidelines: at the anatomical left of the sternum between the 2nd and 5th intercostal space. Additionally, the likelihood of successful acquisition is also driven by how long it stores past coordinates and how much it corrects itself. Results suggest that achieving an automated echocardiography system is feasible using the proposed framework. The long-term vision is of a widely accessible and accurate heart imaging capability within hospitals and community-based settings that enables timely diagnosis of early-stage heart disease.

Inertial Measurement Unit-Assisted Ultrasonic Tracking System for Ultrasound Probe Localization.

Ultrasonic tracking is a promising technique in indoor object localization. However, limited success has been reported in dynamic orientational and positional ultrasonic tracking for ultrasound (US) probes due to its instability and relatively low accuracy. This article aims at developing an inertial measurement unit (IMU)-assisted ultrasonic tracking system that enables a high accuracy positional and orientational localization. The system was designed with the acoustic pressure field simulation of the transmitter, receiver configuration, position-variant error simulation, and sensor fusion. The prototype was tested in a tracking volume required in typical obstetric sonography within the typical operation speed ranges (slow mode and fast mode) of US probe movement. The performance in two different speed ranges was evaluated against a commercial optical tracking device. The results show that the proposed IMU-assisted US tracking system achieved centimeter-level positional tracking accuracy with the mean absolute error (MAE) of 12 mm and the MAE of orientational tracking was less than 1°. The results indicate the possibility of implementing the IMU-assisted ultrasonic tracking system in US probe localization.

Visual Perception and Convolutional Neural Network-Based Robotic Autonomous Lung Ultrasound Scanning Localization System.

Under the situation of severe COVID-19 epidemic, lung ultrasound (LUS) has been proved to be an effective and convenient method to diagnose and evaluate the extent of respiratory disease. However, the traditional clinical ultrasound (US) scanning requires doctors not only to be in close contact with patients but also to have rich experience. In order to alleviate the shortage of medical resources and reduce the work stress and risk of infection for doctors, we propose a visual perception and convolutional neural network (CNN)-based robotic autonomous LUS scanning localization system to realize scanned target recognition, probe pose solution and movement, and the acquisition of US images. The LUS scanned targets are identified through the target segmentation and localization algorithm based on the improved CNN, which is using the depth camera to collect the image information; furthermore, the method based on multiscale compensation normal vector is used to solve the attitude of the probe; finally, a position control strategy based on force feedback is designed to optimize the position and attitude of the probe, which can not only obtain high-quality US images but also ensure the safety of patients and the system. The results of human LUS scanning experiment verify the accuracy and feasibility of the system. The positioning accuracy of the scanned targets is 15.63 ± 0.18 mm, and the distance accuracy and rotation angle accuracy of the probe position calculation are 6.38 ± 0.25 mm and 8.60° ±2.29° , respectively. More importantly, the obtained high-quality US images can clearly capture the main pathological features of the lung. The system is expected to be applied in clinical practice.

Effects of standardized language on remote ultrasound-guided percutaneous nephrolithotomy training: A mixed-methods explorative pilot study

BackgroundRemote teaching of procedural skills has demonstrated equivalence in knowledge acquisition compared to in-person teaching. Variations in terminology for probe and needle movements may serve as a barrier in remote training of ultrasound (US)-guided renal access for percutaneous nephrolithotomy (PCNL). This pilot study investigated the utility of standardized terminology in remote training of US-guided renal access for PCNL. HypothesisStandardization of verbal terminology to describe US probe and needle movement instruction improves remote teaching of US-guided renal access. MethodsFifteen urology residents (PGY1-6) were stratified by year and randomized into two groups. We provided participants with images illustrating US probe and needle movements labeled with predetermined standardized terminology for the intervention group and images without labels for the control group. Both groups were asked to perform US-guided renal access on a training mannequin with a remote faculty educator with (intervention) or without (control) use of standardized movement instructions. Quantitative outcomes included number of attempts and time to achieve access. All trainees completed pre- and post-session surveys and participated in focus groups; authors conducted thematic analysis of focus group transcripts. ResultsDifferences in primary outcomes between groups, including number of attempts and time to achieve access of the renal pole, were not statistically significant. Analysis of focus group interviews revealed that the use of standardized terminology in the setting of remote training can reduce trainee confusion by clarifying ambiguity in educator feedback. DiscussionUse of standardized terminology during remote surgical skills training allows for more effective feedback to trainees.

Ultrasound Probe Movement Analysis Using Depth Camera with Compact Handle Design for Probe Contact Force Measurement.

The real-time information of the ultrasound probe movement and contact force during scanning is helpful for improving skill of medical professionals. This paper presents an affordable technique using an RGB-depth camera with the MediaPipe Hands framework for capturing the hand gesture to estimate the position and orientation of the ultrasound probe. The method does not require any additional marker which can interfere the motion and the feeling of handheld operation. The tracking accuracies of position and orientation were evaluated experimentally at different camera angles. The 3D printed handle was inserted into the grids of the XYZ plate and the tilt plate. Although the camera angle and the spatial position affect the accuracies, the maximum errors are always less than 7.5 mm and 10 degrees. The custom designed handle consisting of the inner and outer shells allows installation of the small three-axis force sensor for probe contact force measurement while scanning. The design is easy to assemble with an ultrasound probe without requiring any modification. The results of this work can be applied as a guideline for monitoring ultrasound training.

Evaluation of Different Registration Algorithms to Reduce Motion Artifacts in CT-Thermography (CTT).

Computed tomography (CT)-based Thermography (CTT) is currently being investigated as a non-invasive temperature monitoring method during ablation procedures. Since multiple CT scans with defined time intervals were acquired during this procedure, interscan motion artifacts can occur between the images, so registration is required. The aim of this study was to investigate different registration algorithms and their combinations for minimizing inter-scan motion artifacts during thermal ablation. Four CTT datasets were acquired using microwave ablation (MWA) of normal liver tissue performed in an in vivo porcine model. During each ablation, spectral CT volume scans were sequentially acquired. Based on initial reconstructions, rigid or elastic registration, or a combination of these, were carried out and rated by 15 radiologists. Friedman's test was used to compare rating results in reader assessments and revealed significant differences for the ablation probe movement rating only (p = 0.006; range, 5.3-6.6 points). Regarding this parameter, readers assessed rigid registration as inferior to other registrations. Quantitative analysis of ablation probe movement yielded a significantly decreased distance for combined registration as compared with unregistered data. In this study, registration was found to have the greatest influence on ablation probe movement, with connected registration being superior to only one registration process.

Chemical Reactions-Based Detection Mechanism for Molecular Communications

In molecular communications, the direct detection of signaling molecules may be challenging due to a lack of suitable sensors and interference from co-existing substances in the environment. Motivated by research in molecular biology, we investigate an indirect detection mechanism using chemical reactions between the signaling molecules and a molecular probe to produce an easy-to-measure product at the receiver. We consider two implementations of the proposed detection mechanism, i.e., unrestricted probe movement and probes restricted to a volume around the receiver. In general, the resulting reaction-diffusion equations that describe the concentrations of the reactant and product molecules in the system are non-linear and coupled, and cannot be solved in closed form. To evaluate these molecule concentrations, we develop an efficient iterative algorithm by discretizing the time variable and solving for the space variables of the concentration equations in each time step. In the special case when the concentration of the unrestricted probes is high and not significantly changed by the chemical reaction, we obtain insightful closed-form solutions. Our results show that the concentrations of the product molecules and the signalling molecules have a similar characteristic over time, i.e., a single peak and a long tail. We highlight that by carefully choosing the molecular probe and optimizing the decision threshold, the BER can be improved significantly such that a direct detection system is outperformed. Moreover, when the molecular probes are kept in a small volume around the receiver, fewer resources are needed to achieve a lower BER and/or a higher data rate compared to the case of unrestricted molecular probes.

Reliability and validity of ultrasonographic automated length measurement system for assessing talofibular anterior instability in acute lateral ankle sprain

Ankle joint instability after acute lateral ankle sprain (LAS) is an important factor for deciding treatment strategies. Nevertheless, the degree of ankle joint mechanical instability as a criterion for making clinical decisions is unclear. This study examined the reliability and validity of an Automated Length Measurement System (ALMS) in ultrasonography for assessing real-time anterior talofibular distance. Using a phantom model, we tested whether ALMS could detect two points within a landmark following movement of the ultrasonographic probe. Furthermore, we examined whether ALMS was comparable with the manual measurement method for 21 patients with an acute LAS (42 ankles) during the reverse anterior drawer test. Using the phantom model, ALMS measurements showed excellent reliability, with errors below 0.4 mm and with a small variance. The ALMS measurement was comparable to manually measured values (ICC = 0.53–0.71, p < 0.001) and detected differences in talofibular joint distances between unaffected and affected ankles of 1.41 mm (p < 0.001). ALMS shortened the measurement time by one-thirteenth for one sample compared to the manual measurement (p < 0.001). ALMS could be used to standardize and simplify ultrasonographic measurement methods for dynamic joint movements without human error in clinical applications.