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Rami N. Khushaba
University of Technology, Sydney
Machine learningPattern recognitionComputer scienceFeature extractionDimensionality reduction
71Publications
19H-index
1,519Citations
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Publications 69
Newest
Jul 1, 2019 in EMBC (International Conference of the IEEE Engineering in Medicine and Biology Society)
#2Rami N. KhushabaH-Index: 19
Last. Adel Al-JumailyH-Index: 16
view all 3 authors...
Surface Electromyogram (EMG) pattern recognition has long been utilized for controlling multifunctional myoelectric prostheses. In such an application, a number of EMG channels are usually utilized to acquire more information about the underlying activity of the remaining muscles in the amputee stump. However, despite the multichannel nature of this application, the extracted features are usually acquired from each channel individually, without consideration for the interaction between the diffe...
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#1Evan Campbell (UNB: University of New Brunswick)H-Index: 1
#2Angkoon Phinyomark (UNB: University of New Brunswick)H-Index: 4
Last. Erik Scheme (UNB: University of New Brunswick)H-Index: 10
view all 6 authors...
Difficulties accessing amputee populations has resulted in the widespread adoption of able-bodied subjects in virtual environments for the development of myoelectric prostheses. Factors such as scar tissue, different physiologies or surgical outcomes, and reduced visual and proprioceptive feedback, however, may contribute to differences in electromyogram (EMG) patterns between these groups. As such, studies have consistently found worse results when comparing the performance of amputee subjects ...
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Jul 1, 2018 in EMBC (International Conference of the IEEE Engineering in Medicine and Biology Society)
#1Carolina Silveira (Newcastle University)H-Index: 2
#2Emma Brunton (Newcastle University)H-Index: 5
Last. Kianoush Nazarpour (Newcastle University)H-Index: 18
view all 4 authors...
In the development of closed-loop prostheses that record from the patient’s own nerves to provide sensory feedback, it is first necessary to determine the features of sensory signals that may help to identify different sensations. The aim of this work was to investigate different time-domain features for separation of sensory electroneurographic signals. To do this, sensory signals were elicited in response to mechanical stimulation of the rat hindpaw and these signals were recorded from a cuff ...
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Jul 1, 2018 in EMBC (International Conference of the IEEE Engineering in Medicine and Biology Society)
#1Rami N. Khushaba (UTS: University of Technology, Sydney)H-Index: 19
#2Agamemnon Krasoulis (Newcastle University)H-Index: 4
Last. Kianoush Nazarpour (Newcastle University)H-Index: 18
view all 4 authors...
Recent studies indicate the limited clinical acceptance of myoelectric prostheses, as upper extremity amputees need improved functionality and more intuitive, effective, and coordinated control of their artificial limbs. Rather than exclusively classifying the electromyogram (EMG) signals, it has been shown that inertial measurements (IMs) can form an excellent complementary signal to the EMG signals to improve the prosthetic control robustness. We present an investigation into the possibility o...
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#1Angkoon PhinyomarkH-Index: 20
#2Rami N. KhushabaH-Index: 19
Last. Erik SchemeH-Index: 10
view all 3 authors...
Specialized myoelectric sensors have been used in prosthetics for decades, but, with recent advancements in wearable sensors, wireless communication and embedded technologies, wearable electromyographic (EMG) armbands are now commercially available for the general public. Due to physical, processing, and cost constraints, however, these armbands typically sample EMG signals at a lower frequency (e.g., 200 Hz for the Myo armband) than their clinical counterparts. It remains unclear whether existi...
22 CitationsSource
#1Angkoon Phinyomark (UNB: University of New Brunswick)H-Index: 4
#2Rami N. Khushaba (UTS: University of Technology, Sydney)H-Index: 19
Last. Giovanni Petri (Institute for Scientific Interchange)H-Index: 14
view all 6 authors...
The success of biological signal pattern recognition depends crucially on the selection of relevant features. Across signal and imaging modalities, a large number of features have been proposed, le...
12 CitationsSource
#1Angkoon PhinyomarkH-Index: 4
#2Rami N. KhushabaH-Index: 19
Last. Giovanni PetriH-Index: 14
view all 6 authors...
Source
#1Rami N. Khushaba (Information Technology University)H-Index: 19
#2Ali H. Al-Timemy (UOB: University of Baghdad)H-Index: 7
Last. Adel Al-Jumaily (Information Technology University)H-Index: 16
view all 4 authors...
The extraction of the accurate and efficient descriptors of muscular activity plays an important role in tackling the challenging problem of myoelectric control of powered prostheses. In this paper, we present a new feature extraction framework that aims to give an enhanced representation of muscular activities through increasing the amount of information that can be extracted from individual and combined electromyogram (EMG) channels. We propose to use time-domain descriptors (TDDs) in estimati...
16 CitationsSource
Jul 1, 2017 in EMBC (International Conference of the IEEE Engineering in Medicine and Biology Society)
#1Rami N. Khushaba (AmeriCorps VISTA)H-Index: 19
#2Jeff Armitstead (AmeriCorps VISTA)H-Index: 3
Last. Klaus Schindhelm (AmeriCorps VISTA)H-Index: 23
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Monitoring of respiration patterns allows the early detection of various breathing disorders and may better identify those at risk for adverse acute outcomes in a variety of clinical settings. In this paper, we report on the use of SleepMinder (SM), a bedside non-contact Doppler-based biomotion recording sensor, to monitor remotely the nocturnal respiration patterns of 50 patients with systolic Heart failure (HF) while undergoing a lab based Polysomnography (PSG) test. A new respiration rate (RR...
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#1Kenneth McDonald (UCD: University College Dublin)H-Index: 36
#2Rory O'Hanlon (UCD: University College Dublin)H-Index: 18
Last. Martin R. Cowie (Imperial College London)H-Index: 59
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5 CitationsSource
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