Zobrazeno 1 - 10
of 197
pro vyhledávání: '"Atashzar, S. Farokh"'
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 spread, a phase marked by rapidly changing factors like virus mutatio
Externí odkaz:
http://arxiv.org/abs/2410.00921
Developing accurate hand gesture perception models is critical for various robotic applications, enabling effective communication between humans and machines and directly impacting neurorobotics and interactive robots. Recently, surface electromyogra
Externí odkaz:
http://arxiv.org/abs/2408.02547
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. Despite the remarkable success of recent end-to-end Deep Learning app
Externí odkaz:
http://arxiv.org/abs/2405.19356
Autor:
Azar, Golara Ahmadi, Hu, Qin, Emami, Melika, Fletcher, Alyson, Rangan, Sundeep, Atashzar, S. Farokh
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 dynamics of biosignals from the peripheral nervous system, such as surface el
Externí odkaz:
http://arxiv.org/abs/2310.03752
Surface electromyography (sEMG) and high-density sEMG (HD-sEMG) biosignals have been extensively investigated for myoelectric control of prosthetic devices, neurorobotics, and more recently human-computer interfaces because of their capability for ha
Externí odkaz:
http://arxiv.org/abs/2309.12602
In the past decade, there has been significant advancement in designing wearable neural interfaces for controlling neurorobotic systems, particularly bionic limbs. These interfaces function by decoding signals captured non-invasively from the skin's
Externí odkaz:
http://arxiv.org/abs/2309.11086
Autor:
Kara, Ozdemir Can, Xue, Jiaqi, Venkatayogi, Nethra, Mohanraj, Tarunraj G., Hirata, Yuki, Ikoma, Naruhiko, Atashzar, S. Farokh, Alambeigi, Farshid
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 and pathology of excised tumors. The proposed unique handheld edge devi
Externí odkaz:
http://arxiv.org/abs/2309.09642
Autor:
Libby, Jacqueline, Somwanshi, Aniket A., Stancati, Federico, Tyagi, Gayatri, Mehrdad, Sarmad, Rizzo, JohnRoss, Atashzar, S. Farokh
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 indicate that by strategically manipulating the stress distribution within so
Externí odkaz:
http://arxiv.org/abs/2308.04722
Autor:
Mehrdad, Sarmad, Atashzar, S. Farokh
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 freedom (S-DoF) to improve modeling generalizability, and robustness t
Externí odkaz:
http://arxiv.org/abs/2305.09071
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 recently shown that based on the concept of ``Excess of Passivity (EoP
Externí odkaz:
http://arxiv.org/abs/2302.00495