arXiv subjects

Mohsen Annabestani

Publications and source records attributed to Mohsen Annabestani.

16 recordsLinked to original sources

arXiv2026

Enhanced Real-Time 6-DOF Extended Reality Catheter Tracking for Evaluating Potential Improvement in Efficiency, Precision, and Depth Perception for Cardiac Interventions

Despite advances in 3D ultrasound, most percutaneous cardiac interventions still rely on 2D visualization, limiting depth perception and spatial understanding. To address this challenge, we developed an Extended Reality (XR)-based platform that enables real-time six-degree-of-freedom (6-DOF) catheter tracking and visualization within a patient-specific 3D heart model. The system combines a custom machine-vision algorithm for 5-DOF catheter tracking with a 3D-printed electromechanical encoder that measures catheter roll, providing complete 6-DOF motion reconstruction. In a proof-of-concept study, 20 novice medical students navigated an intracardiac echocardiography (ICE) catheter to six anatomical targets using either immersive 3D visualization or a conventional 2D cathlab-style view. Participants in the 3D condition completed the task in 54.6 seconds and traveled 1,939 mm on average, compared with 267.5 seconds and 7,854 mm in the 2D condition. Therefore, the XR-based 3D system was more than 5x faster and required ~5x less catheter travel. The 3D mode also improved targeting precision and reduced performance variability. Participants consistently rated immersive visualization higher for accuracy, speed, usability, and clinical value. Kinematic analysis showed smoother depth-axis navigation in 3D, whereas 2D users relied on repeated corrective movements. These findings demonstrate that XR-based visualization can substantially improve procedural training efficiency, precision, and motor control.

cs.RO↗

arXiv2025

AI-Driven Acoustic Voice Biomarker-Based Hierarchical Classification of Benign Laryngeal Voice Disorders from Sustained Vowels

Benign laryngeal voice disorders affect nearly one in five individuals and often manifest as dysphonia, while also serving as non-invasive indicators of broader physiological dysfunction. We introduce a clinically inspired hierarchical machine learning framework for automated classification of eight benign voice disorders alongside healthy controls, using acoustic features extracted from short, sustained vowel phonations. Experiments utilized 15,132 recordings from 1,261 speakers in the Saarbruecken Voice Database, covering vowels /a/, /i/, and /u/ at neutral, high, low, and gliding pitches. Mirroring clinical triage workflows, the framework operates in three sequential stages: Stage 1 performs binary screening of pathological versus non-pathological voices by integrating convolutional neural network-derived mel-spectrogram features with 21 interpretable acoustic biomarkers; Stage 2 stratifies voices into Healthy, Functional or Psychogenic, and Structural or Inflammatory groups using a cubic support vector machine; Stage 3 achieves fine-grained classification by incorporating probabilistic outputs from prior stages, improving discrimination of structural and inflammatory disorders relative to functional conditions. The proposed system consistently outperformed flat multi-class classifiers and pre-trained self-supervised models, including META HuBERT and Google HeAR, whose generic objectives are not optimized for sustained clinical phonation. By combining deep spectral representations with interpretable acoustic features, the framework enhances transparency and clinical alignment. These results highlight the potential of quantitative voice biomarkers as scalable, non-invasive tools for early screening, diagnostic triage, and longitudinal monitoring of vocal health.

cs.SD↗

arXiv2024

Advanced XR-Based 6-DOF Catheter Tracking System for Immersive Cardiac Intervention Training

Extended Reality (XR) technologies are gaining traction as effective tools for medical training and procedural guidance, particularly in complex cardiac interventions. This paper presents a novel system for real-time 3D tracking and visualization of intracardiac echocardiography (ICE) catheters, with precise measurement of the roll angle. A custom 3D-printed setup, featuring orthogonal cameras, captures biplane video of the catheter, while a specialized computer vision algorithm reconstructs its 3D trajectory, localizing the tip with sub-millimeter accuracy and tracking the roll angle in real-time. The system's data is integrated into an interactive Unity-based environment, rendered through the Meta Quest 3 XR headset, combining a dynamically tracked catheter with a patient-specific 3D heart model. This immersive environment allows the testing of the importance of 3D depth perception, in comparison to 2D projections, as a form of visualization in XR. Our experimental study, conducted using the ICE catheter with six participants, suggests that 3D visualization is not necessarily beneficial over 2D views offered by the XR system; although all cardiologists saw its utility for pre-operative training, planning, and intra-operative guidance. The proposed system qualitatively shows great promise in transforming catheter-based interventions, particularly ICE procedures, by improving visualization, interactivity, and skill development.

eess.IV↗

arXiv2022

Warp and Weft Wiring method for rapid, modifiable, self-aligned, and bonding-free fabrication of multi electrodes microfluidic sensors

The need for rapid fabrication of microfluidic devices has become increasingly critical as microfluidics become part of biomedical sensors. Using Warp and Weft Wiring (WWW) of copper wires, this paper presents a novel low-cost method for rapid, self-aligned, bonding-free, and modifiable fabrication of multi-electrodes microfluidic sensors. All the proposed features are promising and highly recommended for the development of Point-of-Care Tests (POCTs), while most of the conventional methods have low chances of coming out of the research labs and play no role in POCTs development. To have an experimental proof of concept, the proposed chip was fabricated and then tested with two sets of experiments that showed the potential applications of water quality management, hygiene, biomedical impedance measurement, cell analysis, flow cytometry, etc.

q-bio.QM↗

arXiv2022

A Plant-Inspired Multifunctional, Two Way, and Fiberless Soft Gripper with Sensorized Kinaesthesia

This work presents a new fiberless soft pneumatic actuator that can work multifunctional and bidirectional, and its embedded sensors give it a self-proprioception ability. This actuator works based on the idea of employing helical pressure channels. Applying the controlled input pressures into these two channels causes a variety of deformations and actuation. In particular, single pressure, imbalanced pressures, and balanced pressures applied in the channels cause bidirectional coilings, opposite bendings, and elongation, respectively, in a single unit actuator. Also, two U-shaped microchannels are created, and by injecting a gel-based conductive material, the actuator is equipped with resistive sensors which are responsive to a vast dynamic range from a small oscillation to a large elongation. This actuator has so many promising features as a multifunctional soft gripper, and its embedded soft sensors enable it to have better controllability in real problems. The multifunctionality of this actuator has been validated with several experimental tests, and also we have shown it has excellent potential in gripping a variety of objects. Finally, the embedded sensors can discriminate the main functions of actuators, and also they can play the role of independent sensors as well like a stretch, pressure, or bending sensors.

cs.RO↗

arXiv2022

Physics-Data Driven Machine Learning Based Model: A Hybrid Way for Nonlinear, Dynamic, and Open-loop Identification of IPMC Soft Artificial Muscles

Ionic Polymer Metal Composites (IPMCs) are one of the most preferred choices among biocompatible materials for industrial and biomedical applications. Despite their advantages, some of their drawbacks include non-linear and hysteretic behavior, which complicates the modeling process. In previous works, usually autoregressive models were used to predict the behavior of an IPMC actuator. The main drawback of using an autoregressive model is that it cannot be used in mobile and real-time applications. In this study, we proposed a hybrid analytical intelligent model for an IPMC actuator. The most outstanding feature of this model is its non-autoregressive structure. The hybrid concept proposed in this study can be generalized to various problems other than IPMCs. The structure used in this work comprises an analytical model and a deep neural network, providing a non-linear, dynamic, and non-autoregressive model for the IPMC actuator. Lastly, the average NMSE achieved using the proposed hybrid model is 9.5781e-04 showing a significant drop in the error rate compared to other non-autoregressive structures.

cs.LG↗

arXiv2021

A novel fully 3D, microfluidic-oriented, gel-based and low cost stretchable soft sensor

In this paper, a novel fully 3D, microfluidic-oriented, gel-based, and low-cost highly stretchable resistive sensors have been presented. By the proposed method we are able to measure and discriminate all of the stretch, twist, and pressure features by a single sensor which is the potential that we have obtained from the fully 3D structure of our sensor. Against previous sensors which all have used EGaIn as the conductive material of their sensor, we have used low-cost, safe, and ubiquitous glycol-based gel instead. To show the functionality of the proposed sensor some FEM simulations, a set of the designed experimental tests were done which showed the linear, accurate, and durable operation of the proposed sensor. Finally, the sensor was put through its paces on the knee, elbow, and wrist of a female test subject. Also, to evaluate the pressure functionality of the sensor, a fully 3D active foot insole was developed, fabricated, and evaluated. All of the results show promising features for the proposed sensor to be used in real-world applications like rehabilitation, wearable devices, soft robotics, smart clothing, gait analysis, AR/VR, etc.

q-bio.QM↗

arXiv2021

A new soft computing method for integration of expert's knowledge in reinforcement learn-ing problems

This paper proposes a novel fuzzy action selection method to leverage human knowledge in reinforcement learning problems. Based on the estimates of the most current action-state values, the proposed fuzzy nonlinear mapping as-signs each member of the action set to its probability of being chosen in the next step. A user tunable parameter is introduced to control the action selection policy, which determines the agent's greedy behavior throughout the learning process. This parameter resembles the role of the temperature parameter in the softmax action selection policy, but its tuning process can be more knowledge-oriented since this parameter reflects the human knowledge into the learning agent by making modifications in the fuzzy rule base. Simulation results indicate that including fuzzy logic within the reinforcement learning in the proposed manner improves the learning algorithm's convergence rate, and provides superior performance.

cs.AI↗

arXiv2021

Toward a High Performance IPMC Soft Actuator using A disturbance-aided method

Besides the advantages of Ionic polymer-metal composites (IPMCs) for biomedical applications, there are some drawbacks in their performance, which can be enhanced. One of those critical drawbacks is "back relaxation" (BR). If we apply a step voltage to IPMC, it will bend in the anode direction. Afterward, there is an unwanted and relatively slow counter-bending toward the cathode side. There are some disadvantages in the current BR control methods of IPMC actuators that prevent them from being used in real applications. This paper presents a new non-feedback method for eliminating the BR effect of non-patterned IPMCs by using a relatively high-frequency disturbance and proving it by theoretical and experimental explanations. The results show that the proposed method, needless to have any pattern on the electrodes of the IPMCs, can significantly eliminate the BR effect. Unlike the patterned IPMCs, no reduction will occur in the bending amplitude of IPMC, and even we can see the increased bending amplitude.

cond-mat.soft↗

arXiv2019

Continuous Emotion Recognition during Music Listening Using EEG Signals: A Fuzzy Parallel Cascades Model

A controversial issue in artificial intelligence is human emotion recognition. This paper presents a fuzzy parallel cascades (FPC) model for predicting the continuous subjective appraisal of the emotional content of music by time-varying spectral content of EEG signals. The EEG, along with an emotional appraisal of 15 subjects, was recorded during listening to seven musical excerpts. The emotional appraisement was recorded along the valence and arousal emotional axes as a continuous signal. The FPC model was composed of parallel cascades with each cascade containing a fuzzy logic-based system. The FPC model performance was evaluated by comparing with linear regression (LR), support vector regression (SVR) and Long Short Term Memory recurrent neural network (LSTM RNN) models. The RMSE of the FPC was lower than other models for the estimation of both valence and arousal of all musical excerpts. The lowest RMSE was 0.089 which was obtained in estimation of the valence of MS4 by the FPC model. The analysis of MI of frontal EEG with the valence confirms the role of frontal channels in theta frequency band in emotion recognition. Considering the dynamic variations of musical features during songs, employing a modeling approach to predict dynamic variations of the emotional appraisal can be a plausible substitute for the classification of musical excerpts into predefined labels.

cs.HC↗

arXiv2019

Full Analytical 3D Ion Transport Model for Large Deformable IPMC Soft Actuator

Ionic Polymer Metal Composite is a well-known soft electroactive polymer composite that it's promising features tell us that it has adequate potential to be a utilizable and applicative soft actuator in the practical applications, especially in the small size applications. But this smart material is still immature, and one of the reasons that lead to its immaturity is lack of a valid and proper physics-based model for large deformation situations. In practical online and large deformation applications, the inverse non-autoregressive identification based models are the proper choices but if we want to know how IPMC works and what is the physics of its behavior in the large deformation situation the inverse identification based models are deeply blind, and we have to use physical and multi-physical approaches. It is our main aim in this paper, and for the first time, we want to present a fully analytical and physics-based ion transport 3D and non-Linear model for large deformable IPMC. In this direction, based on three dimensional Nernst-Plank PDE we will find a well-defined and valid relationship between input voltage and output tip displacement of IPMC for large deformation situation and with four provable pieces of evidence it will be proven that proposed model has chosen a proper way and it is more complete than previous benchmark and well-known physics-based models for IPMC, and also it is valid and accurate enough for large deformation modeling of IPMC.

physics.app-ph↗

arXiv2019

Multiphysics analysis and practical implementation of an ionic soft actuator-based microfluidic device toward the design of a POCT compatible active micromixer

Electroactive-Polymers (EAPs) are one of the best soft materials with great applications in active microfluidics. Ionic ones (i-EAPs) have more promising features for being appropriate candidates to use in active microfluidic devices. Here, as a case study, we have designed and fabricated a microfluidic micromixer using an i-EAP named Ionic Polymer-Metal Composite (IPMC). In microfluidics, active devices have more functionality but due to their required facilities are less effective for Point of Care Tests (POCTs). In the direction of solving this paradox, we should use some active components that they need minimum facilities. IPMC can be one of these components, hence by integrating the IPMC actuator into a microfluidic channel, a micromixer chip was designed and put to the simulation and experimental tests. The result showed that the proposed micromixer is able to mix the micro fluids properly and IPMC actuator has adequate potential to be an active component for POCT-based microfluidic chips.

q-bio.QM↗

arXiv2019

Descriptive evaluation of students using fuzzy approximate reasoning

In recent years, descriptive evaluation has been introduced as a new model for educational evaluation of Iranian students. The current descriptive evaluation method is based on four-valued logic. Assessing all students with only four values is led to a lack of relative justice and the creation of unrealistic equality. Also, the complexity of the evaluation process in the current method increases teacher errors likelihood. As a suitable solution, in this paper, a fuzzy descriptive evaluation system has been proposed. The proposed method is based on fuzzy logic, which is an infinite-valued logic and it can perform approximate reasoning on natural language propositions. By the proposed fuzzy system, student assessment is performed over the school year with infinite values instead of four values. But to eliminate the diversity of assigned values to students, at the end of the school year, the calculated values for each student will be rounded to the nearest value of the four standard values of the current descriptive evaluation system. It can be implemented easily in an appropriate smartphone app, which makes it much easier for the teachers to evaluate the evaluation process. In this paper, the evaluation process of the elementary third-grade mathematics course in Iran during the period from the beginning of the MEHR (The Seventh month of Iran) to the end of BAHMAN (The Eleventh Month of Iran) is examined by the proposed system. To evaluate the validity of this system, the proposed method has been simulated in MATLAB software.

cs.AI↗

arXiv2019

An Algebraic Approach to Fast Estimation of the Threshold Voltage of Junctionless Double Gate MOSFETs Using the Gram Schmidt Method

The effect of decreasing Drain-Induced Barrier Lowering (DIBL) is one of the non-desirable short-channel effects in the MOSFETs family, which causes the threshold voltage of the transistor to be reduced by increasing the voltage of the drain. This effect makes it impossible for circuit designers to consider VT as a constant value, and hence, it is necessary to calculate VT as a function of the drain voltage. Therefore, to consider the effect of DIBL in the design of integrated circuits, a large computational burden is imposed on the system, which slows down the simulation process in circuit-level simulators, particularly when a large number of transistors are to be simulated. Accordingly, in this paper, a multiple input single output (MISO) Nonlinear Autoregressive (N-AR) model using the Gram-Schmidt orthogonalization approach is proposed, that calculates the threshold voltage of the new generation of MOSFETs, i.e., Junctionless Double-Gate MOSFETs (JL-DG-MOSFETs), with a high precision and a significant speed-up in the computational procedure of the model. It is shown that, on average, the proposed numerical method is 313 times faster than the state-of-the-art analytical model. The calculated percentage of normalized mean square error between the proposed model and analytical one is 0.435% on average, showing that the proposed approach can be a fast and accurate candidate for replacing the analytical modeling.

cs.DC↗

arXiv2019

A knowledge-based intelligent system for control of dirt recognition process in the smart washing machines

In this paper, we propose an intelligence approach based on fuzzy logic to modeling human intelligence in washing clothes. At first, an intelligent feedback loop is designed for perception-based sensing of dirt inspired by human color understanding. Then, when color stains leak out of some colored clothes the human probabilistic decision making is computationally modeled to detect this stain leakage and thus the problem of recognizing dirt from stain can be considered in the washing process. Finally, we discuss the fuzzy control of washing clothes and design and simulate a smart controller based on the fuzzy intelligence feedback loop.

cs.AI↗

arXiv2019

Ionic Electro active Polymer-Based Soft Actuators and Their Applications in Microfluidic Micropumps, Microvalves, and Micromixers: A Review

This paper provides a detailed review on applications of ionic electroactive polymer (i-EAP) soft actuators as active elements of microfluidic micropumps, microvalves, and micromixers. The related works that have so far been presented by various research groups in the field have been collected in this review, which in the presented comparative procedure here shows the progress of this field during the time. Microfluidic technology as a pioneer field in bioengineering needs to have some active components likes pumps, valves, and mixers to obtain efficient functionality. Most of the conventional microfluidic active components are challenging to assemble and control outside the laboratory since they need some special facilities, which is not cost-effective. This is while some of the main targets of the microfluidic devices are for the development of point of care (POC) diagnostic systems, home usability, ubiquitousness, and low-cost ability. To solve these problems, i-EAPs have shown promising features to be the proper candidates as active elements of the microfluidic devices. Ionic polymer-metal composites (IPMCs), Conducting polymer actuators (CPAs), and Ionic carbon nanotube-based actuators (i-CNTAs) are three main types of the i-EAPs. In this paper, the working principles, fabrication, and microfluidic-based applications of these three categories are described in details. To have a proper comparison between all the reported i-EAP based microfluidic devices, several important features, i.e., applied voltage/frequency, device materials, electrode material, membrane material, and the main measured index of each device, have been reviewed.

physics.app-ph↗