Research and application of a teaching platform for combined spinal-epidural anesthesia based on virtual reality and haptic feedback technology.

BACKGROUND: Intraspinal anesthesia poses significant teaching challenges and inadequate teaching resources, which ultimately limit students' opportunities for practice. To address this issue, we aimed to develop a virtual platform for combined spinal-epidural anesthesia that merges virtual reality technology with haptic feedback technology, while assessing its educational impact and learning outcomes. METHODS: We utilized MIMICS, 3Ds MAX, and UNITY 3D software to perform 3D reconstruction based on lumbar CT/MRI data from a standard male volunteer. The haptic coefficients were configured on each layer by 20 experienced anesthesiologists in accordance with the Geomagic Touch X force feedback device. A total of 20 anesthesiology interns completed 30 virtual puncture training sessions. Two experienced anesthetists evaluated the efficacy of the platform and the level of mastery achieved using the Global Rating Scale (GRS) and a Checklist score, respectively. Finally, a questionnaire survey was conducted to gather feedback on the virtual platform. RESULTS: After the 10th session, the puncture time stabilized at 2.4 min. As the number of sessions increased, the Global Rating Scale (GRS) score stabilized by the 8th session, and the Checklist scores tended to stabilize by the 10th session. Results from questionnaires indicated that over half of the anesthesiology interns (70%) believed that the platform, which exhibited strong repeatability, improved their anatomical recognition and provided a strong sense of breakthrough in identifying the ligamentum flavum. The majority of them (80%) expressed satisfaction with the virtual platform. CONCLUSIONS: The platform effectively facilitated the acquisition of basic and accurate puncture skills on a virtual patient.

Large-area flexible MWCNT/PDMS pressure sensor for ergonomic design with aid of deep learning learning.

The achievement of well-performing pressure sensors with low pressure detection, high sensitivity, large-scale integration, and effective analysis of the subsequent data remains a major challenge in the development of flexible piezoresistive sensors. In this study, a simple and extendable sensor preparation strategy was proposed to fabricate flexible sensors on the basis of multiwalled carbon nanotube/polydimethylsiloxane (MWCNT/PDMS) composites. A dispersant of tetrahydrofuran (THF) was added to solve the agglomeration of MWCNTs in PDMS, and the resistance of the obtained MWCNT/PDMS conductive unit with 7.5 wt.% MWCNTs were as low as 180 Ω/hemisphere. Sensitivity (0.004 kPa-1), excellent response stability, fast response time (36 ms), and excellent electromechanical properties were demonstrated within the pressure range from 0 to 100 kPa. A large-area flexible sensor with 8 × 10 pixels was successfully adopted to detect the pressure distribution on the human back and to verify its applicability. Combining the sensor array with deep learning, inclination of human sitting was easily recognized with high accuracy, indicating that the combined technology can be used to guide ergonomic design.

Assessment of a 3D printed simulator of a lateral ventricular puncture in interns' surgical training.

PURPOSE: In this study, a simulator for training lateral ventricular puncture (LVP) was developed using three-dimensional (3D) printing technology, and its function of improving the skills of LVP in young interns was evaluated. METHODS: A virtual 3D craniocerebral simulator of a 51-year-old female patient with hydrocephalus was reconstructed with 3D printing technology. The anatomical and practical validity were assessed by all interns on a 13-item Likert scale. The usefulness of this simulator was evaluated once a week by two neurosurgeons, based on the performance of the interns, using the objective structured assessment of technical skills (OSATS) scale. RESULTS: The Likert scale showed that all participants agreed with the overall appearance of the simulator. Also, the authenticity of the skull was the best, followed by the lateral ventricles, analog generation system of intraventricular pressure, cerebrum, and the scalp. This simulator could help the participants' learning about the anatomy of the lateral ventricle, effective training, and repeating the steps of LVP. During training, the interns' ratio of success in LVP elevated gradually. At each evaluation stage, all mean performance scores for each measure based on the OSATS scale were higher than the previous. CONCLUSIONS: The 3D printed simulator for LVP training provided both anatomical and practical validity, and enabled young doctors to master the LVP procedures and skills.

Find Outliers of Image Edge Consistency by Weighted Local Linear Regression with Equality Constraints.

In this paper, we propose a general method to detect outliers from contaminated estimates of various image estimation applications. The method does not require any prior knowledge about the purpose, theory or hardware of the application but simply relies on the law of edge consistency between sources and estimates. The method is termed as ALRe (anchored linear residual) because it is based on the residual of weighted local linear regression with an equality constraint exerted on the measured pixel. Given a pair of source and contaminated estimate, ALRe offers per-pixel outlier likelihoods, which can be used to compose the data weights of post-refinement algorithms, improving the quality of refined estimate. ALRe has the features of asymmetry, no false positive and linear complexity. Its effectiveness is verified on four applications, four post-refinement algorithms and three datasets. It demonstrates that, with the help of ALRe, refined estimates are better in the aspects of both quality and edge consistency. The results are even comparable to model-based and hardware-based methods. Accuracy comparison on synthetic images shows that ALRe could detect outliers reliably. It is as effective as the mainstream weighted median filter at spike detection and is significantly better at bad region detection.

Enhancing the settling time estimation of fixed-time stability and applying it to the predefined-time synchronization of delayed memristive neural networks with external unknown disturbance.

This paper concentrates on the global predefined-time synchronization of delayed memristive neural networks with external unknown disturbance via an observer-based active control. First, a global predefined-time stability theorem based on a non-negative piecewise Lyapunov function is proposed, which can obtain more accurate upper bound of the settling time estimation. Subsequently, considering the delayed memristive neural networks with disturbance, a disturbance-observer is designed to approximate the external unknown disturbance in the response system with a Hurwitz theorem and then to eliminate the influence of the unknown disturbance. With the help of global predefined-time stability theorem, the predefined-time synchronization is achieved between two delayed memristive neural networks via an active control Lyapunov function design. Finally, two numerical simulations are performed, and the results are given to show the correctness and feasibility of the predefined-time stability theorem.

Finite element method analysis of the periodontal ligament in mandibular canine movement with transparent tooth correction treatment.

BACKGROUND: This study used the 3D finite element method to investigate canine's displacements and stresses in the canine's periodontal ligament (PDL) during canine's translation, inclination, and rotation with transparent tooth correction treatment. METHODS: Finite element models were developed to simulate dynamic orthodontic treatments of the translation, inclination, and rotation of the left mandibular canine with transparent tooth correction system. Piecewise static simulations were performed to replicate the dynamic process of orthodontic treatments. The distribution and change trends of canine's displacements and stresses in the canine's PDL during the three types of tooth movements were obtained. RESULTS: Maximum displacements were observed at the crown and middle part in the translation case, at the crown in the inclination case, and at the crown and root part in the rotation case. The relative maximum von Mises and principal stresses were mainly found at the cervix of the PDL in the translation and inclination cases. In the translation case, tensile stress was mainly observed on the mesial and distal surfaces near the lingual side and compressive stress was located at the bottom of the labial surface. In the inclination case, tensile stress was mainly observed at the labial cervix and lingual apex and compressive stress was located at the lingual cervix and labial apex. In the rotation case, von Mises stress was mainly located at the cervix and inside the lingual surface, tensile stress was located on the distal surface, and compressive stress was detected on the mesial surface. The stress and displacement value rapidly decreased in the first few steps and then reached a plateau. CONCLUSIONS: Canine's movement type significantly influences the distribution of canine's displacement and stresses in the canine's PDL. Changes in canine's displacement and stresses in the canine's PDL were exponential in transparent tooth correction treatment.

Influences of solvents and monomer concentrations on the electrochemical performance and structural properties of electrodeposited PEDOT films: a comparative study in water and acetonitrile.

Poly(3,4-ethylenedioxythiophene) (PEDOT) has emerged as a promising coating for neural electrodes especially through convenient electrodeposition methods. To investigate the influences of solvents and EDOT monomer concentrations on the electrochemical performance and structural characteristics of PEDOT, both aqueous and acetonitrile solutions were employed with varying monomer concentrations during deposition. The prepared PEDOT films were examined for the surface morphology, electrochemical performance, and chemical structures. The results showed that an increase in EDOT concentration in either solvent led to PEDOT films with improved charge storage capacity and reduced impedance magnitude. At equivalent monomer concentrations, PEDOT films generated in acetonitrile exhibited a rougher surface texture and better electrochemical performance. Notably, the growth rate of charge storage capacity of PEDOT prepared in acetonitrile relative to the deposited charge density was 2.5 times that of PEDOT prepared in water. These findings could help to the optimization of PEDOT coating preparation to enhance electrode performance.

Preparation, identification and molecular docking of two novel anti-aging peptides from perilla seed.

Perilla seed meal is an important agricultural by-product of perilla oil extraction. The antioxidant and anti-aging activities of perilla seed meal protein hydrolysate were investigated, and the bioactive peptides were identified to maximize the utilization of perilla seed meal resources. Anti-aging peptides were identified using a combination of peptidomics and in silico bioinformatics. Furthermore, the potential molecular mechanism of these peptides was explored through molecular docking and RT-PCR. The results showed a significant anti-aging properties of F2 (MW 3 kDa ∼5 kDa) by inhibition of reactive oxygen species (ROS) production and ß-galactosidase activity. Nine novel peptides were identified from F2 and subsequently synthesized to explore their bioactivities. The two peptides, NFF and PMR, were found to promote the proliferation of keratinocytes (HaCaT cells) and suppress the level of ROS and the activity of ß-galactosidase. Both peptides exhibited a strong binding affinity with the Keap1 protein. Additionally, NFF and PMR downregulated the expression of matrix metalloproteinases (MMPs) and the degradation of collagens (COLs). The potential molecular mechanism underlying the anti-aging properties of perilla seed meal peptides might involve the competitive binding of Keap1 to facilitate the release of Nrf2 and activation of NF-κB signal pathway. This study provides a theoretical basis for the application of perilla seed meal peptides in functional cosmetics and presents a novel perspective for the investigation of additional food-derived peptides.

Efficient intraoral photogrammetry using self-identifying projective invariant marker.

PURPOSE: The re-measurement of full-arch implant digital impressions is an important step in denture restoration. This paper provides an efficient oral photogrammetry technology using projective invariant marker, applied in the re-measurement of full-arch implant digital impressions. METHODS: We have developed a self-recognizing marker with projection invariance, along with its detection code. The marker is installed on the scanning body and used for photogrammetric measurements. Triangulation is utilized to determine the 3D coordinates of the marker, followed by a series of post-processing steps to obtain more accurate 3D coordinates. RESULTS: The experimental data indicate that the optimal working distance is between 200 and 250 mm, with a minimum measurement error of less than 0.05 mm and an average measurement error of 0.10 mm. The measurement time is less than 2 min. CONCLUSIONS: The experimental results show that the photogrammetric system can obtain reliable positions of full-arch implants with efficient photogrammetry, without the need to enter the patient's oral cavity, and has potential clinical application value.

Distributed visual positioning for surgical instrument tracking.

In clinical operations, it is crucial for surgeons to know the location of the surgical instrument. Traditional positioning systems have difficulty dealing with camera occlusion, marker occlusion, and environmental interference. To address these issues, we propose a distributed visual positioning system for surgical instrument tracking in surgery. First, we design the marker pattern with a black and white triangular grid and dot that can be adapted to various instrument surfaces and improve the marker location accuracy of the feature. The cross-points in the marker are the features that each feature has a unique ID. Furthermore, we proposed detection and identification for the position-sensing marker to realize the accurate location and identification of features. Second, we introduce multi Perspective-n-Point (mPnP) method, which fuses feature coordinates from all cameras to deduce the final result directly by the intrinsic and extrinsic parameters. This method provides a reliable initial value for the Bundle Adjustment algorithms. During instrument tracking, we assess the motion state of the instrument and select either dynamic or static Kalman filtering to mitigate any jitter in the instrument's movement. The core algorithms comparison experiment indicates our positioning algorithm has a lower reprojection error comparison to the mainstream algorithms. A series of quantitative experiments showed that the proposed system positioning error is below 0.207 mm, and the run time is below 118.842 ms. The results demonstrate the tremendous clinical application potential of our system providing accurate positioning of instruments promoting the efficiency and safety of clinical surgery.

Hemodynamic characteristics and mechanism for intracranial aneurysms initiation with the circle of Willis anomaly.

Clinically, circle of Willis (CoW) is prone to anomaly and is also the predominant incidence site of intracranial aneurysms (IAs). This study aims to investigate the hemodynamic characteristics of CoW anomaly, and ascertain the mechanism of IAs initiation from the perspective of hemodynamics. Thus, the flow of IAs and pre-IAs were analyzed for one type of cerebral artery anomaly, that is, anterior cerebral artery A1 segment (ACA-A1) unilateral absence. Three patient geometrical models with IAs were selected from Emory University Open Source Data Center. IAs were virtually removed from the geometrical models to simulate the pre-IAs geometry. For calculation methods, a one-dimensional (1-D) solver and a three-dimensional (3-D) solver were combined to obtain the hemodynamic characteristics. The numerical simulation revealed that the average flow of Anterior Communicating Artery (ACoA) is almost zero when CoW is complete. In contrast, ACoA flow increases significantly in the case of ACA-A1 unilateral absence. For per-IAs geometry, the jet flow is found at the bifurcation between contralateral ACA-A1 and ACoA, which exhibits characteristics of high Wall Shear Stress (WSS) and high wall pressure in the impact region. It triggers the initiation of IAs from the perspective of hemodynamics. The vascular anomaly that leads to jet flow should be considered as a risk factor for IAs initiation.

Quantitative Evaluation of Hemodynamic Changes After Multiple Intracranial Aneurysms Occlusion Using Computational Fluid Dynamics.

OBJECTIVE: Multiple intracranial aneurysms (MIA) are prevalent. This study conducted hemodynamic calculations on MIA to analyze the effects of occlusion of the internal carotid artery (ICA) and middle cerebral artery (MCA) aneurysms on the hemodynamics of other arteries, as well as the issue of the treatment order for these aneurysms. METHODS: The models of 9 patients with MIA were selected for the study. A computational fluid dynamics model combining 1-dimension and 3-dimension was used to obtain the vascular flow pattern and wall pressure. RESULTS: There was increased pressure at the MCA and anterior cerebral artery (ACA) after occlusion of the aneurysm at the ICA. However, the pressure at the ICA has hardly changed after the aneurysm occlusion at the MCA. Occlusion of the aneurysm of different sizes at the MCA had almost no impact on the pressure at the ICA and ACA. For small aneurysm, the pressure of the ACA and MCA increases with decreasing size of the aneurysm at the ICA. After occlusion of a large aneurysm at the ICA, the impact on the pressure of the ACA and MCA is almost the same as after occlusion of a medium-sized aneurysm. CONCLUSIONS: If the treatment order of ICA and MCA aneurysms cannot be determined based on patient factors and aneurysm characteristics, the MCA aneurysm should be treated as a priority.

A Self-Developed Mobility Augmented Reality System Versus Conventional X-rays for Spine Positioning in Intraspinal Tumor Surgery: A Case-Control Study.

OBJECTIVE: To evaluate the efficacy of a self-developed mobile augmented reality navigation system (MARNS) in guiding spinal level positioning during intraspinal tumor surgery based on a dual-error theory. METHODS: This retrospective study enrolled patients diagnosed with intraspinal tumors admitted to Fujian Provincial Hospital between May and November 2023. The participants were divided into conventional x-rays and self-developed MARNS groups according to the localization methods they received. Position time, length of intraoperative incision variation, and location accuracy were systematically compared. RESULTS: A total of 41 patients (19 males) with intraspinal tumors were included, and MARNS was applied to 21 patients. MARNS achieved successful lesion localization in all patients with an error of 0.38±0.12 cm. Compared to x-rays, MARNS significantly reduced positioning time (129.00±13.03 seconds vs. 365.00±60.43 seconds, p<0.001) and length of intraoperative incision variation (0.14 cm vs. 0.67 cm, p=0.009). CONCLUSION: The self-developed MARNS, based on augmented reality technology for lesion visualization and perpendicular projection, offers a radiation-free complement to conventional x-rays.

Role of peptide-cell surface interactions in cosmetic peptide application.

Cosmetic peptides have gained popularity in a wide range of skincare products due to their good biocompatibility, effective anti-oxidative properties, and anti-aging effects. However, low binding between peptides and the cell surface limits the efficacy of functional peptides. In this study, we designed two novel targeting peptide motifs to enhance the interaction between cosmetic peptides and the cell surface, thereby improving their performance for skin health. To achieve this, we optimized the well-known peptide tripeptide-1 (GHK) by separately grafting the integrin αvß3-binding motif RGD and the chondroitin sulfate (CS)-binding motif sOtx2 onto it, forming two chimeric targeting peptides, RGD-GHK and sOtx2-GHK. Comparative analysis showed that both RGD-GHK and sOtx2-GHK exhibited superior anti-oxidative and anti-apoptotic effects compared to the non-targeting peptide, GHK. Furthermore, RGD-GHK demonstrated exceptional anti-aging activity, and its potential for promoting wound healing and repairing the skin barrier was evaluated in vitro using cells and skin models. In vitro permeation and in vivo adsorption testing confirmed that RGD-GHK achieved a high local concentration in the skin layer, initiating peptide effects and facilitating in vivo wound healing, while maintaining excellent biocompatibility. The enhancement of signaling cosmetic peptides can be attributed to the specific interaction between the binding motif and cell surface components. Consequently, this targeting peptide holds promising potential as a novel functional peptide for application in cosmetics.

Image-guided navigation system for minimally invasive total hip arthroplasty (MITHA) using an improved position-sensing marker.

PURPOSE: Minimally invasive total hip arthroplasty (MITHA) is a treatment for hip arthritis, and it causes less tissue trauma, blood loss, and recovery time. However, the limited incision makes it difficult for surgeons to perceive the instruments' location and orientation. Computer-assisted navigation systems can help improve the medical outcome of MITHA. Directly applying existing navigation systems for MITHA, however, suffers from problems of bulky fiducial marker, severe feature-loss, multiple instruments tracking confusion, and radiation exposure. To tackle these problems, we propose an image-guided navigation system for MITHA using a novel position-sensing marker. METHODS: A position-sensing marker is proposed to serve as the fiducial marker with high-density and multi-fold ID tags. It results in less feature span and enables the use of ID for each feature, overcoming the problem of bulky fiducial markers and multiple instruments tracking confusion. And the marker can be recognized even when a large part of locating features is obscured. As for the elimination of intraoperative radiation exposure, we propose a point-based method to achieve patient-image registration based on anatomical landmarks. RESULTS: Quantitative experiments are conducted to evaluate the feasibility of our system. The accuracy of instrument positioning is achieved at 0.33 ± 0.18 mm, and that of patient-image registration is achieved at 0.79 ± 0.15 mm. And qualitative experiments are also performed, verifying that our system can be used in compact surgical spatial volume and can address severe feature-loss and tracking confusion problems. In addition, our system does not require any intraoperative medical scans. CONCLUSION: Experimental results indicate that our proposed system can assist surgeons without larger space occupations, radiation exposure, and extra incision, showing its potential application value in MITHA.

Gesture Classification in Electromyography Signals for Real-Time Prosthetic Hand Control Using a Convolutional Neural Network-Enhanced Channel Attention Model.

Accurate and real-time gesture recognition is required for the autonomous operation of prosthetic hand devices. This study employs a convolutional neural network-enhanced channel attention (CNN-ECA) model to provide a unique approach for surface electromyography (sEMG) gesture recognition. The introduction of the ECA module improves the model's capacity to extract features and focus on critical information in the sEMG data, thus simultaneously equipping the sEMG-controlled prosthetic hand systems with the characteristics of accurate gesture detection and real-time control. Furthermore, we suggest a preprocessing strategy for extracting envelope signals that incorporates Butterworth low-pass filtering and the fast Hilbert transform (FHT), which can successfully reduce noise interference and capture essential physiological information. Finally, the majority voting window technique is adopted to enhance the prediction results, further improving the accuracy and stability of the model. Overall, our multi-layered convolutional neural network model, in conjunction with envelope signal extraction and attention mechanisms, offers a promising and innovative approach for real-time control systems in prosthetic hands, allowing for precise fine motor actions.

HydraMarker: Efficient, Flexible, and Multifold Marker Field Generation.

An n-order marker field is a special binary matrix whose n×n subregions are all distinct from each other in four orientations. It is commonly used to guide the composing process of position-sensing markers, which can be detected and identified in a camera image with very limited scope or severe visibility problems. Despite the advantages, position-sensing markers are rare and overlooked because generating marker fields is difficult. In this article, we broaden the definition of marker field, making it more powerful and flexible. Then, we propose bWFC (binary wave function collapse) and its high-speed version, fast-bWFC, to solve the generation problem. The methods are packaged into an open-sourced toolkit named HydraMarker, with which, users not only can generate marker fields on laptops within a short period of time, but also can highly customize them: preset values; fields and subregions in any shape; multifold local uniqueness. Comparative results indicate that the proposed method has superior efficiency, quality, and capability. It makes marker field generation accessible to common marker designers, opening up more possibilities for fiducial markers.

Numerical Analysis of Stress Force on Vessel Walls in Atherosclerotic Plaque Removal through Coronary Rotational Atherectomy.

Coronary rotational atherectomy is an effective technique for treating cardiovascular disease by removing calcified tissue using small rotary grinding tools. However, it is difficult to analyze the stress force on vessel walls using experiments directly. Using computational fluid dynamics is a better way to study the stress force characteristics of the burr grinding procedure from a fluid dynamics perspective. For this purpose, physical and simulation models of atherosclerotic plaque removal were constructed in this study. The simulation results show that smaller ratios between the burr and arterial diameter (B/A = 0.5) result in a more stable flow field domain. Additionally, the pressure and stress force generated by the 4.5 mm diameter grinding tool reach 92.77 kPa and 10.36 kPa, surpassing those of the 2.5 mm and 3.5 mm grinding tools. The study has demonstrated the use of computational fluid dynamics to investigate wall shear stress characteristics in medical procedures, providing valuable guidance for optimizing the procedure and minimizing complications.

A Low-Cost Mobile-Based Augmented Reality Neuronavigation System for Retrosigmoid Craniotomy.

BACKGROUND AND OBJECTIVES: The correct positioning of the transverse-sigmoid sinus junction (TSSJ) during retrosigmoid craniotomy (RC) is crucial for enhancing surgical efficiency and preventing complications. An augmented reality technology may provide low-cost guidance for the TSSJ position. The authors aimed to investigate the clinical application of a self-developed mobile augmented reality navigation system (MARNS) for TSSJ positioning during RC and present their findings. METHODS: This observational research enrolled patients who underwent RC at Fujian Provincial Hospital from May 2023 to June 2023. All patients had their TSSJs located by MARNS. The surgical incision and skull "keyhole" for drilling were determined separately based on the projections of TSSJ on the 3-dimensional model displayed by MARNS. This method was assessed using matching error, positioning time, integrity of the bone flap, incidence of transversal sigmoid sinus injury, and other complications. RESULTS: Seven patients diagnosed with acoustic neuroma, trigeminal neuralgia, and hemifacial spasm were enrolled in this study. The MARNS system exhibited a matching error with an average magnitude of 2.88 ± 0.69 mm. The positioning procedure necessitated an average duration of 279.71 ± 27.29 seconds. In every instance, the inner edge of the TSSJ was precisely identified and exposed while the bone flap was successfully formed and maintained an average integrity of 86.7%. CONCLUSION: This study demonstrated the efficacy of MARNS in the precise placement of the TSSJ during RC procedures. It offers advantages for convenience, cost-effectiveness, and reliability for neurosurgical navigation.

Application of an effective marker-less augmented reality image guidance method in dental implant surgery.

BACKGROUND: The existing augmented reality (AR) dental implant surgery navigation system usually uses markers to complete image guidance. However, markers often affect dentists' operations and make patients uncomfortable. METHODS: To solve the problems caused by markers, this paper proposes an effective marker-less image guidance method. After initialisation is completed by contour matching, the corresponding relationship is obtained by matching the feature points between the current frame and the preloaded initial frame. The camera pose is estimated by solving the Perspective-n-Point problem. RESULTS: The registration error of AR images is 0.731 ± 0.144 mm. The planting errors are 1.174 ± 0.241 mm at the neck, 1.433 ± 0.389 mm at the apex and 5.566 ± 2.102° for the angle. The maximum error and standard deviation meet the clinical requirements. CONCLUSIONS: We demonstrate that the proposed method can accurately guide dentists to perform dental implant surgery.