4 citations · 8 across the 4 of their papers we have counts for
4 papers
Evaluating Performance of Machine Learning Models for Diabetic Sensorimotor Polyneuropathy Severity Classification using Biomechanical Signals during Gait
Fahmida Haque, Mamun Bin Ibne Reaz, Muhammad Enamul Hoque Chowdhury +10
Diabetic sensorimotor polyneuropathy (DSPN) is one of the prevalent forms of neuropathy affected by diabetic patients that involves alterations in biomechanical changes in human ga…
Motion Artifacts Correction from Single-Channel EEG and fNIRS Signals using Novel Wavelet Packet Decomposition in Combination with Canonical Correlation Analysis
Md Shafayet Hossain, Muhammad E. H. Chowdhury, Mamun Bin Ibne Reaz +7
The electroencephalogram (EEG) and functional near-infrared spectroscopy (fNIRS) signals, highly non-stationary in nature, greatly suffers from motion artifacts while recorded usin…
A machine learning-based severity prediction tool for diabetic sensorimotor polyneuropathy using Michigan neuropathy screening instrumentations
Fahmida Haque, Mamun B. I. Reaz, Muhammad E. H. Chowdhury +7
Background: Diabetic Sensorimotor polyneuropathy (DSPN) is a major long-term complication in diabetic patients associated with painful neuropathy, foot ulceration and amputation. T…
A Machine Learning Model for Early Detection of Diabetic Foot using Thermogram Images
Amith Khandakar, Muhammad E. H. Chowdhury, Mamun Bin Ibne Reaz +7
Diabetes foot ulceration (DFU) and amputation are a cause of significant morbidity. The prevention of DFU may be achieved by the identification of patients at risk of DFU and the i…