38 citations · 122 across the 25 of their papers we have counts for
26 papers
Encoding Biomechanical Energy Margin into Passivity-based Synchronization for Networked Telerobotic Systems
Xingyuan Zhou, Peter Paik, S. Farokh Atashzar
Maintaining system stability and accurate position tracking is imperative in networked robotic systems, particularly for haptics-enabled human-robot interaction. Recent literature…
Tunable Passivity Control for Centralized Multiport Networked Systems
Xingyuan Zhou, Peter Paik, S. Farokh Atashzar
Centralized Multiport Networked Dynamic (CMND) systems have emerged as a key architecture with applications in several complex network systems, such as multilateral telerobotics an…
A Systematic Review of EEG-based Machine Intelligence Algorithms for Depression Diagnosis, and Monitoring
Amir Nassibi, Christos Papavassiliou, Ildar Rakhmatulin +2
Depression disorder is a serious health condition that has affected the lives of millions of people around the world. Diagnosis of depression is a challenging practice that relies…
PREPARE: PREdicting PAndemic's REcurring Waves Amidst Mutations, Vaccination, and Lockdowns
Narges M. Shahtori, S. Farokh Atashzar
This study releases an adaptable framework that can provide insights to policymakers to predict the complex recurring waves of the pandemic in the medium postemergence of the virus…
The Role of Functional Muscle Networks in Improving Hand Gesture Perception for Human-Machine Interfaces
Costanza Armanini, Tuka Alhanai, Farah E. Shamout +1
Developing accurate hand gesture perception models is critical for various robotic applications, enabling effective communication between humans and machines and directly impacting…
An LSTM Feature Imitation Network for Hand Movement Recognition from sEMG Signals
Chuheng Wu, S. Farokh Atashzar, Mohammad M. Ghassemi +1
Surface Electromyography (sEMG) is a non-invasive signal that is used in the recognition of hand movement patterns, the diagnosis of diseases, and the robust control of prostheses.…
A Deep Learning Sequential Decoder for Transient High-Density Electromyography in Hand Gesture Recognition Using Subject-Embedded Transfer Learning
Golara Ahmadi Azar, Qin Hu, Melika Emami +3
Hand gesture recognition (HGR) has gained significant attention due to the increasing use of AI-powered human-computer interfaces that can interpret the deep spatiotemporal dynamic…
ViT-MDHGR: Cross-day Reliability and Agility in Dynamic Hand Gesture Prediction via HD-sEMG Signal Decoding
Qin Hu, Golara Ahmadi Azar, Alyson Fletcher +2
Surface electromyography (sEMG) and high-density sEMG (HD-sEMG) biosignals have been extensively investigated for myoelectric control of prosthetic devices, neurorobotics, and more…
From Unstable Contacts to Stable Control: A Deep Learning Paradigm for HD-sEMG in Neurorobotics
Eion Tyacke, Kunal Gupta, Jay Patel +2
In the past decade, there has been significant advancement in designing wearable neural interfaces for controlling neurorobotic systems, particularly bionic limbs. These interfaces…
A Smart Handheld Edge Device for On-Site Diagnosis and Classification of Texture and Stiffness of Excised Colorectal Cancer Polyps
Ozdemir Can Kara, Jiaqi Xue, Nethra Venkatayogi +5
This paper proposes a smart handheld textural sensing medical device with complementary Machine Learning (ML) algorithms to enable on-site Colorectal Cancer (CRC) polyp diagnosis a…
How Does the Inner Geometry of Soft Actuators Modulate the Dynamic and Hysteretic Response?
Jacqueline Libby, Aniket A. Somwanshi, Federico Stancati +4
This paper investigates the influence of the internal geometrical structure of soft pneu-nets on the dynamic response and hysteresis of the actuators. The research findings indicat…
FiMReSt: Finite Mixture of Multivariate Regulated Skew-t Kernels -- A Flexible Probabilistic Model for Multi-Clustered Data with Asymmetrically-Scattered Non-Gaussian Kernels
Sarmad Mehrdad, S. Farokh Atashzar
Recently skew-t mixture models have been introduced as a flexible probabilistic modeling technique taking into account both skewness in data clusters and the statistical degree of…
Upper-limb Geometric MyoPassivity Map for Physical Human-Robot Interaction
Xingyuan Zhou, Peter Paik, S. Farokh Atashzar
The intrinsic biomechanical characteristic of the human upper limb plays a central role in absorbing the interactive energy during physical human-robot interaction (pHRI). We have…
What Happens When Pneu-Net Soft Robotic Actuators Get Fatigued?
Jacqueline Libby, Aniket A. Somwanshi, Federico Stancati +5
Soft actuators have attracted a great deal of interest in the context of rehabilitative and assistive robots for increasing safety and lowering costs as compared to rigid-body robo…
Transformer-based Hand Gesture Recognition via High-Density EMG Signals: From Instantaneous Recognition to Fusion of Motor Unit Spike Trains
Mansooreh Montazerin, Elahe Rahimian, Farnoosh Naderkhani +3
Designing efficient and labor-saving prosthetic hands requires powerful hand gesture recognition algorithms that can achieve high accuracy with limited complexity and latency. In t…
Pit-Pattern Classification of Colorectal Cancer Polyps Using a Hyper Sensitive Vision-Based Tactile Sensor and Dilated Residual Networks
Nethra Venkatayogi, Qin Hu, Ozdemir Can Kara +3
In this study, with the goal of reducing the early detection miss rate of colorectal cancer (CRC) polyps, we propose utilizing a novel hyper-sensitive vision-based tactile sensor c…
HYDRA-HGR: A Hybrid Transformer-based Architecture for Fusion of Macroscopic and Microscopic Neural Drive Information
Mansooreh Montazerin, Elahe Rahimian, Farnoosh Naderkhani +3
Development of advance surface Electromyogram (sEMG)-based Human-Machine Interface (HMI) systems is of paramount importance to pave the way towards emergence of futuristic Cyber-Ph…
Design and Modeling of a Smart Torque-Adjustable Rotary Electroadhesive Clutch for Application in Human-Robot Interaction
Navid Feizi, S. Farokh Atashzar, Mehrdad R. Kermani +1
The increasing need for sharing workspace and interactive physical tasks between robots and humans has raised concerns regarding safety of such operations. In this regard, controll…
Deterioration Prediction using Time-Series of Three Vital Signs and Current Clinical Features Amongst COVID-19 Patients
Sarmad Mehrdad, Farah E. Shamout, Yao Wang +1
Unrecognized patient deterioration can lead to high morbidity and mortality. Most existing deterioration prediction models require a large number of clinical information, typically…
Force-Aware Interface via Electromyography for Natural VR/AR Interaction
Yunxiang Zhang, Benjamin Liang, Boyuan Chen +4
While tremendous advances in visual and auditory realism have been made for virtual and augmented reality (VR/AR), introducing a plausible sense of physicality into the virtual wor…
Hand Gesture Recognition Using Temporal Convolutions and Attention Mechanism
Elahe Rahimian, Soheil Zabihi, Amir Asif +3
Advances in biosignal signal processing and machine learning, in particular Deep Neural Networks (DNNs), have paved the way for the development of innovative Human-Machine Interfac…
TEMGNet: Deep Transformer-based Decoding of Upperlimb sEMG for Hand Gestures Recognition
Elahe Rahimian, Soheil Zabihi, Amir Asif +3
There has been a surge of recent interest in Machine Learning (ML), particularly Deep Neural Network (DNN)-based models, to decode muscle activities from surface Electromyography (…
FS-HGR: Few-shot Learning for Hand Gesture Recognition via ElectroMyography
Elahe Rahimian, Soheil Zabihi, Amir Asif +3
This work is motivated by the recent advances in Deep Neural Networks (DNNs) and their widespread applications in human-machine interfaces. DNNs have been recently used for detecti…
COVID-FACT: A Fully-Automated Capsule Network-based Framework for Identification of COVID-19 Cases from Chest CT scans
Shahin Heidarian, Parnian Afshar, Nastaran Enshaei +8
The newly discovered Corona virus Disease 2019 (COVID-19) has been globally spreading and causing hundreds of thousands of deaths around the world as of its first emergence in late…