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

4 citations · 8 across the 4 of their papers we have counts for

collaborators

4 papers

cs.HC2024★ 1 cited

Impact of Electrode Position on Forearm Orientation Invariant Hand Gesture Recognition

Md. Johirul Islam, Umme Rumman, Arifa Ferdousi +10

Objective: Variation of forearm orientation is one of the crucial factors that drastically degrades the forearm orientation invariant hand gesture recognition performance or the de…

cs.LG2022★ 4 cited

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…

cs.LG2022★ 1 cited

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…

eess.SP2022★ 2 cited

Myoelectric Pattern Recognition Performance Enhancement Using Nonlinear Features

Md. Johirul Islam, Shamim Ahmad, Fahmida Haque +3

The multichannel electrode array used for electromyogram (EMG) pattern recognition provides good performance, but it has a high cost, is computationally expensive, and is inconveni…