NeuroAiR: Deep Learning Framework for Airwriting Recognition from Scalp-recorded Neural Signals

A Tripathi, A Gupta, AP Prathosh… - IEEE Transactions …, 2024 - ieeexplore.ieee.org
Airwriting recognition is a task that involves identifying letters written in free space using
finger movement. It is a special case of gesture recognition, where gestures correspond to …

SurfMyoAiR: A surface electromyography-based framework for airwriting recognition

A Tripathi, AP Prathosh… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
Airwriting recognition is the task of identifying letters written in free space with finger
movement. It is a dynamic gesture recognition with the vocabulary of gestures …

TripCEAiR: A multi-loss minimization approach for surface EMG based airwriting recognition

A Tripathi, AP Prathosh, SP Muthukrishnan… - … Signal Processing and …, 2023 - Elsevier
Airwriting Recognition refers to the problem of identification of letters written in space with
movement of the finger. It can be seen as a special case of dynamic gesture recognition …

In-air handwriting system based on multi-scale channel attention network and monocular vision

X Qu, M Ye, W Zhao - Applied Soft Computing, 2024 - Elsevier
In-air handwriting based on a monocular camera is an innovative and promising modality for
human–computer interaction, offering a plethora of potential applications. However, existing …

Letter and Person Recognition in Freeform Air-Writing using Machine Learning Algorithms

H Kunt, Z Yetgin, F Gozukara, T Celik - IEEE Access, 2025 - ieeexplore.ieee.org
Air-writing is an emerging form of human-computer interaction that enables text entry
through hand movements in the air. This paper explores air-writing-based person …

Continuous Hand Gestures Detection and Recognition in Emergency Human-Robot Interaction Based on the Inertial Measurement Unit

S Wang, T Zhang, Y Li, P Li, H Wu… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Robots have become increasingly prevalent in various aspects of daily life. In an increasing
number of scenarios, particularly in social contexts, such as those involving delivery robots …

Deep Learning-based Classification of Dementia using Image Representation of Subcortical Signals

S Ranjan, A Tripathi, H Shende, R Badal… - arxiv preprint arxiv …, 2024 - arxiv.org
Dementia is a neurological syndrome marked by cognitive decline. Alzheimer's disease
(AD) and Frontotemporal dementia (FTD) are the common forms of dementia, each with …

Prism: Mining Task-aware Domains in Non-iid IMU Data for Flexible User Perception

Y Li, F Hu, H Zhu, Q Liu, X Zhao, J Shen… - arxiv preprint arxiv …, 2025 - arxiv.org
A wide range of user perception applications leverage inertial measurement unit (IMU) data
for online prediction. However, restricted by the non-iid nature of IMU data collected from …

Gesture Recognition Methods Using Sensors Integrated into Smartwatches: Results of a Systematic Literature Review

PRI Gomes, MS Castro, TH Nascimento - Proceedings of the XXII …, 2023 - dl.acm.org
This work addresses the importance of gesture recognition in smartwatches and aims to
conduct a systematic literature review to identify the most commonly used methods and …

Identification of Gas-Solid Two-Phase Flow Regimes Based on Electrostatic Sensor and CB-ResNext Network

J Lu, H Hu, H Cai, H Yang, H Zhang… - 2024 IEEE International …, 2024 - ieeexplore.ieee.org
Electrostatic sensors are commonly used to extract parameter information from gas-solid two-
phase flow in the energy and power industry, characterized by a simple structure and high …