S
Shitanshu Kusmakar
Researcher at University of Melbourne
Publications - 16
Citations - 237
Shitanshu Kusmakar is an academic researcher from University of Melbourne. The author has contributed to research in topics: Epilepsy & Psychogenic non-epileptic seizures. The author has an hindex of 7, co-authored 15 publications receiving 144 citations. Previous affiliations of Shitanshu Kusmakar include Deakin University & Indian Institute of Technology Madras.
Papers
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Journal ArticleDOI
Automated Detection of Convulsive Seizures Using a Wearable Accelerometer Device
Shitanshu Kusmakar,Chandan Karmakar,Bernard Yan,Terence J. O'Brien,Ramanathan Muthuganapathy,Marimuthu Palaniswami +5 more
TL;DR: The proposed algorithm showed a comparable performance with respect to existing unimodal and multi-modal methods for GTCS detection and shows the potential to build an ambulatory monitoring convulsive seizure detection system.
Journal ArticleDOI
Technical Validation of ARTSENS–An Image Free Device for Evaluation of Vascular Stiffness
Jayaraj Joseph,Ravikumar Radhakrishnan,Shitanshu Kusmakar,Arya Sree Thrivikraman,Mohanasankar Sivaprakasam +4 more
TL;DR: The feasibility of the novel ARTSENS device in performing accurate in vivo measurements of arterial stiffness is verified, a device for image free, noninvasive, automated evaluation of vascular stiffness amenable for field use.
Journal ArticleDOI
Automatic Detection and Classification of Convulsive Psychogenic Nonepileptic Seizures Using a Wearable Device
Jayavardhana Gubbi,Shitanshu Kusmakar,Aravinda S. Rao,Bernard Yan,Terence J. O'Brien,Marimuthu Palaniswami +5 more
TL;DR: The seizure detection algorithm and PNES classification algorithm are developed and a very high seizure detection rate is achieved with 100% sensitivity and few false alarms, demonstrating the usefulness of wearable device in the diagnosis of PNES.
Proceedings ArticleDOI
Detection of generalized tonic-clonic seizures using short length accelerometry signal
Shitanshu Kusmakar,Chandan Karmakar,Bernard Yan,Terence J. O'Brien,Ramanathan Muthuganapathy,Marimuthu Palaniswami +5 more
TL;DR: A system based on single wrist-worn accelerometer sensor capable of detecting seizures with short duration (≥ 10s) and employing machine learning approach such as kernelized support vector data description (SVDD) is proposed.
Journal ArticleDOI
The utility of an automated and ambulatory device for detecting and differentiating epileptic and psychogenic non-epileptic seizures
Vaidehi D Naganur,Shitanshu Kusmakar,Zhibin Chen,Marimuthu Palaniswami,Patrick Kwan,Patrick Kwan,Terence J. O'Brien,Terence J. O'Brien +7 more
TL;DR: Using a seizure detection and classification algorithm, this work sought to examine the diagnostic utility of an automated analysis with an ambulatory accelerometer of seizures between ES and PNES.