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

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4 papers

cs.HC20241 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.LG20224 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.LG20221 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.SP20222 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…