Rami N. Khushaba
University of Technology, Sydney
Publications 70
#2Angkoon Phinyomark (U of C: University of Calgary)H-Index: 18
Last.Erik Scheme (UNB: University of New Brunswick)H-Index: 10
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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: 1
#2Emma Brunton (Newcastle University)H-Index: 4
Last.Kianoush Nazarpour (Newcastle University)H-Index: 16
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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 ...
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: 17
#2Agamemnon Krasoulis (Newcastle University)H-Index: 4
Last.Kianoush Nazarpour (Newcastle University)H-Index: 16
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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...
#1Angkoon PhinyomarkH-Index: 3
#2Angkoon PhinyomarkH-Index: 18
Last.Erik SchemeH-Index: 10
view all 4 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...
#1Angkoon Phinyomark (UNB: University of New Brunswick)H-Index: 3
#2Rami N. KhushabaH-Index: 17
Last.Giovanni Petri (Institute for Scientific Interchange)H-Index: 11
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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, leading to feature redundancy and the need for optimal feature set identification. A further complication is that, due to the inherent biological variability, even the same classification problem on different datasets can display variations in the respective optimal sets, casting doubts on the generaliza...
#1Rami N. Khushaba (Information Technology University)H-Index: 17
#2Ali H. Al-Timemy (UOB: University of Baghdad)H-Index: 7
Last.Adel Al-Jumaily (Information Technology University)H-Index: 15
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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...
Jul 1, 2017 in EMBC (International Conference of the IEEE Engineering in Medicine and Biology Society)
#1Rami N. Khushaba (AmeriCorps VISTA)H-Index: 17
#2Jeff Armitstead (AmeriCorps VISTA)H-Index: 3
Last.Klaus Schindhelm (AmeriCorps VISTA)H-Index: 22
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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...
#1Rami N. Khushaba (UTS: University of Technology, Sydney)H-Index: 17
#2Ahmed Al-Ani (UTS: University of Technology, Sydney)H-Index: 18
Last.Adel Al-Jumaily (UTS: University of Technology, Sydney)H-Index: 15
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This paper presents a new feature extraction algorithm for the challenging problem of the classification of myoelectric signals for prostheses control. The algorithm employs the orientation between a set of descriptors of muscular activities and a nonlinearly mapped version of them. It incorporates information about the Electromyogram (EMG) signal power spectrum characteristics derived from each analysis window while correlating that with the descriptors of previous windows for robust activity r...