Výsledky vyhledávání - "A. Bakar, A. Ashrif"

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Design and Implementation of a Complete Wearable Smart Insole Solution to Measure Plantar Pressure and Temperature

Autor: Khandakar, Amith, Mahmud, Sakib, Chowdhury, Muhammad E. H., Reaz, Mamun Bin Ibne, Kiranyaz, Serkan, Mahbub, Zaid Bin, Ali, Sawal Hamid Md, Bakar, Ahmad Ashrif A, Alhatou, Mohammed, AbdulMoniem, Mohammed

A complete smart insole solution that continuously monitors the foot plantar pressure and temperature can detect foot complications early and that too from the convenience of the user home. Widespread health complications such as Diabetic Mellitus ne

Externí odkaz: http://arxiv.org/abs/2206.07779

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Evaluating Performance of Machine Learning Models for Diabetic Sensorimotor Polyneuropathy Severity Classification using Biomechanical Signals during Gait

Autor: Haque, Fahmida, Reaz, Mamun Bin Ibne, Chowdhury, Muhammad Enamul Hoque, Kiranyaz, Serkan, Abdelmoniem, Mohamed, Hussein, Emadeddin, Shaat, Mohammed, Ali, Sawal Hamid Md, Bakar, Ahmad Ashrif A, Srivastava, Geetika, Bhuiyan, Mohammad Arif Sobhan, Mokhtar, Mohd Hadri Hafiz, Kurniawan, Edi

Diabetic sensorimotor polyneuropathy (DSPN) is one of the prevalent forms of neuropathy affected by diabetic patients that involves alterations in biomechanical changes in human gait. In literature, for the last 50 years, researchers are trying to ob

Externí odkaz: http://arxiv.org/abs/2205.10581

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Akademický článek

Single-Walled Carbon Nanotube (SWCNT) thin films via automatic spray coating and nitric acid vapor treatment

Autor: Kunaraj, Arulampalam ^{a, c}, Chelvanathan, P. ^b, A Bakar, Ahmad Ashrif ^a, Yahya, Iskandar ^{a, ⁎}

Publikováno v: In Journal of Engineering Research December 2024 12(4):825-831

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Motion Artifacts Correction from Single-Channel EEG and fNIRS Signals using Novel Wavelet Packet Decomposition in Combination with Canonical Correlation Analysis

Autor: Hossain, Md Shafayet, Chowdhury, Muhammad E. H., Reaz, Mamun Bin Ibne, Ali, Sawal H. M., Bakar, Ahmad Ashrif A., Kiranyaz, Serkan, Khandakar, Amith, Alhatou, Mohammed, Habib, Rumana, Hossain, Muhammad Maqsud

The electroencephalogram (EEG) and functional near-infrared spectroscopy (fNIRS) signals, highly non-stationary in nature, greatly suffers from motion artifacts while recorded using wearable sensors. This paper proposes two robust methods: i) Wavelet

Externí odkaz: http://arxiv.org/abs/2204.04533

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