Md. Rabiul Islam, Mohammad Ali Moni, Md. Milon Islam, Md. Rashed-Al-Mahfuz et al.
Recently, electroencephalogram-based emotion recognition has become crucial in enabling the Human-Computer Interaction (HCI) system to become more intelligent. Due to the outstanding applications of emotion recognition, e.g., person-based decision making, mind-machine interfacing, cognitive interact...
Muiz Ahmed Khan, Pias Paul, Mahmudur Rashid, Mainul Hossain et al.
Blindness prevents a person from gaining knowledge of the surrounding environment and makes unassisted navigation, object recognition, obstacle avoidance, and reading tasks a major challenge. In this work, we propose a novel visual aid system for the completely blind. Because of its low cost, compac...
Khondoker Murad Hossain, Md. Ariful Islam, Shahera Hossain, Anton Nijholt et al.
In the previous decade, breakthroughs in the central nervous system bioinformatics and computational innovation have prompted significant developments in brain-computer interface (BCI), elevating it to the forefront of applied science and research. BCI revitalization enables neurorehabilitation stra...
Anindya Das Antar, Masud Ahmed, Md Atiqur Rahman Ahad
Human Activity Recognition using embedded sensors has lately made renowned development and is drawing growing attention in numerous application domains including machine learning, pattern recognition, context awareness, and human-centric sensing. Due to the lacking of a prominent analysis of this to...
Md. Zasim Uddin, Md Shahriar, Md. Nadim Mahamood, Fady Alnajjar et al.
Md Atiqur Rahman Ahad, Masud Ahmed, Anindya Das Antar, Yasushi Makihara et al.
Action recognition is a very widely explored research area in computer vision and related fields. We propose Kinematics Posture Feature (KPF) extraction from 3D joint positions based on skeleton data for improving the performance of action recognition. In this approach, we consider the skeleton 3D j...
Md Atiqur Rahman Ahad, Trung Thanh Ngo, Anindya Das Antar, Masud Ahmed et al.
Wearable sensor-based systems and devices have been expanded in different application domains, especially in the healthcare arena. Automatic age and gender estimation has several important applications. Gait has been demonstrated as a profound motion cue for various applications. A gait-based age an...
Upal Mahbub, Hafiz Imtiaz, Tonmoy Roy, Md. Shafiur Rahman et al.
Md. Ahasan Atick Faisal, Farhan Fuad Abir, Mosabber Uddin Ahmed, Md Atiqur Rahman Ahad
Hand gesture recognition is one of the most widely explored areas under the human-computer interaction domain. Although various modalities of hand gesture recognition have been explored in the last three decades, in recent years, due to the availability of hardware and deep learning algorithms, hand...
Tahera Hossain, Md Atiqur Rahman Ahad, Sozo Inoue
Sensor-based human activity recognition has various applications in the arena of healthcare, elderly smart-home, sports, etc. There are numerous works in this field—to recognize various human activities from sensor data. However, those works are based on data patterns that are clean data and have al...
Valentina Emilia Bălaş, Vijender Kumar Solanki, Raghvendra Kumar, Md Atiqur Rahman Ahad
Md. Moin Uddin Atique, Md. Rafiqul Islam Sarker, Md Atiqur Rahman Ahad
Quadruped robots can mimic animal walking gait and they have certain advantages like walking on terrain and extremely rough surfaces. Obstacles can impede the movement of wheeled vehicles, where a quadruped can adapt to avoid obstacles by adjusting its height. A quadruped robot is designed and devel...
Fahad Parvez Mahdi, Md. Mahmudul Habib, Md Atiqur Rahman Ahad, Susan McKeever et al.
The ability to automatically recognize human faces based on dynamic facial images is important in security, surveillance and the health/independent living domains. Specific applications include access control to secure environments, identification of individuals at a particular place and intruder d ...
Tahera Hossain, Md Shafiqul Islam, Md Atiqur Rahman Ahad, Sozo Inoue
Wearable sensors are monumental for human activity recognition. Researchers are continuously inventing new technology to detect human activity properly. Earable opens up interesting possibilities of monitoring personal scale behavioral activities. In this paper, we explore earables device 'eSense' m...
Md Atiqur Rahman Ahad, Anindya Das Antar, Omar Shahid