15 citations · 22 across the 18 of their papers we have counts for
20 papers
A Multi-Objective Optimisation Framework for Corticomuscular EEG-EMG Pair Selection in Hybrid BCI
Dekka Muni Kumar, Yogesh Kumar Meena
Hybrid brain-computer interface (BCI) systems that integrate electroencephalography (EEG) and electromyography (EMG) signals have shown significant potential in improving the relia…
A Hybrid Gaze-Motor Imagery BCI Framework for Effective Decision Communication
Gowtham Reddy N, KongFatt Wong-Lin, Yogesh Kumar Meena
Non-invasive brain-computer interfaces (BCIs) and eye-tracking technologies offer promising communication pathways; however, motor imagery (MI)-based BCIs often suffer from low dis…
Towards simultaneous decoding of kinetic and kinematic movement parameters during grasp and lift task by noninvasive brain imaging
Parth G. Dangi, Yogesh Kumar Meena
Brain-machine interfaces (BMIs) can assist individuals with limited mobility, such as stroke survivors or amputees. One of the key challenges in developing BMIs is expanding their…
From Dyad to Triad: Eliciting XAI Requirements in Stroke Rehabilitation
Param Rajpura, Yogesh Kumar Meena
Eliciting explainable AI (XAI) requirements from stroke survivors presents a methodological challenge with direct implications for the design of trustworthy brain-computer interfac…
EEGForceFusion: Joint Tokenised-Continuous Representation Learning for Subject-Independent Grasp Force Decoding
Sankalp Sunil Turankar, Yogesh Kumar Meena
Brain-machine interfaces provide a link between neural activity and external devices, enabling restoration of motor function and advancing human-machine interaction using non-invas…
SwitchBraidNet: Quantisation-Aware Lightweight Architecture for Hybrid Brain-Computer Interface
Gourav Siddhad, Yogesh Kumar Meena
Hybrid brain-computer interfaces (BCIs) that integrate motor imagery (MI) and steady-state visual evoked potentials (SSVEP) provide high-dimensional neural decoding but typically e…
RL-ACRGNet: Reinforcement Learning-Based Chest Radiology Report Generation Network
Yogesh Kumar Meena, Saurabh Agarwal, K. V. Arya
Medical imaging interpretation is a foundational pillar of modern clinical diagnostics, yet the manual generation of radiology reports remains a time-consuming process prone to int…
A Domain-Informed Multi-Objective Framework for EEG Channel Selection in Motor Imagery BCIs
Dekka Muni Kumar, Dhruba Jyoti Kalita, Yogesh Kumar Meena
Motor imagery (MI) classification using electroencephalography (EEG) signals is essential for advancing brain-computer interfaces (BCIs). Traditional EEG channel selection methods…
Dac-Fake: A Divide and Conquer Framework for Detecting Fake News on Social Media
Mayank Kumar Jain, Dinesh Gopalani, Yogesh Kumar Meena +1
With the rapid evolution of technology and the Internet, the proliferation of fake news on social media has become a critical issue, leading to widespread misinformation that can c…
SkeySpot: Automating Service Key Detection for Digital Electrical Layout Plans in the Construction Industry
Dhruv Dosi, Rohit Meena, Param Rajpura +1
Legacy floor plans, often preserved only as scanned documents, remain essential resources for architecture, urban planning, and facility management in the construction industry. Ho…
Multimodal Appearance based Gaze-Controlled Virtual Keyboard with Synchronous Asynchronous Interaction for Low-Resource Settings
Yogesh Kumar Meena, Manish Salvi
Over the past decade, the demand for communication devices has increased among individuals with mobility and speech impairments. Eye-gaze tracking has emerged as a promising soluti…
Improving Continuous Grasp Force Decoding from EEG with Time-Frequency Regressors and Premotor-Parietal Network Integration
Parth G. Dangi, Yogesh Kumar Meena
Brain-machine interfaces (BMIs) have significantly advanced neuro-rehabilitation by enhancing motor control. However, accurately decoding continuous grasp force remains a challenge…
Can EEG resting state data benefit data-driven approaches for motor-imagery decoding?
Rishan Mehta, Param Rajpura, Yogesh Kumar Meena
Resting-state EEG data in neuroscience research serve as reliable markers for user identification and reveal individual-specific traits. Despite this, the use of resting-state data…
Predictive Tree-based Virtual Keyboard for Improved Gaze Typing
Hrushikesh Etikikota, Yogesh Kumar Meena
On-screen keyboard eye-typing systems are limited due to the lack of predictive text and user-centred approaches, resulting in low text entry rates and frequent recalibration. This…
Towards Effective Deep Neural Network Approach for Multi-Trial P300-based Character Recognition in Brain-Computer Interfaces
Praveen Kumar Shukla, Hubert Cecotti, Yogesh Kumar Meena
Brain-computer interfaces (BCIs) enable direct interaction between users and computers by decoding brain signals. This study addresses the challenges of detecting P300 event-relate…
Post-Training Quantization in Brain-Computer Interfaces based on Event-Related Potential Detection
Hubert Cecotti, Dalvir Dhaliwal, Hardip Singh +1
Post-training quantization (PTQ) is a technique used to optimize and reduce the memory footprint and computational requirements of machine learning models. It has been used primari…
Quantifying Spatial Domain Explanations in BCI using Earth Mover's Distance
Param Rajpura, Hubert Cecotti, Yogesh Kumar Meena
Brain-computer interface (BCI) systems facilitate unique communication between humans and computers, benefiting severely disabled individuals. Despite decades of research, BCIs are…
Towards Optimising EEG Decoding using Post-hoc Explanations and Domain Knowledge
Param Rajpura, Yogesh Kumar Meena
Decoding EEG during motor imagery is pivotal for the Brain-Computer Interface (BCI) system, influencing its overall performance significantly. As end-to-end data-driven learning me…
MultiFusionNet: Multilayer Multimodal Fusion of Deep Neural Networks for Chest X-Ray Image Classification
Saurabh Agarwal, K. V. Arya, Yogesh Kumar Meena
Chest X-ray imaging is a critical diagnostic tool for identifying pulmonary diseases. However, manual interpretation of these images is time-consuming and error-prone. Automated sy…
Explainable artificial intelligence approaches for brain-computer interfaces: a review and design space
Param Rajpura, Hubert Cecotti, Yogesh Kumar Meena
This review paper provides an integrated perspective of Explainable Artificial Intelligence techniques applied to Brain-Computer Interfaces. BCIs use predictive models to interpret…