Shitanshu Kusmakar1, Chandan Karmakar1,2, Bernard Yan3, Ramanathan Muthuganapathy4, Patrick Kwan3,5,6, Terence J O'Brien3,5,6, Marimuthu Swami Palaniswami1. 1. Department of Electrical and Electronic Engineering, The University of Melbourne, Melbourne, Victoria, Australia. 2. School of Information Technology, Deakin University, Geelong, Victoria, Australia. 3. Melbourne Brain Centre, Department of Medicine, The Royal Melbourne Hospital, University of Melbourne, Melbourne, Victoria, Australia. 4. Department of Engineering Design, Indian Institute of Technology Madras, Chennai, India. 5. Department of Neurosciences and Neurology, The Central Clinical School, Alfred Hospital, Monash University, Melbourne, Victoria, Australia. 6. Department of Medicine and Neurology, The Royal Melbourne Hospital, The University of Melbourne, Melbourne, Victoria, Australia.
Abstract
OBJECTIVE: To investigate the characteristics of motor manifestation during convulsive epileptic and psychogenic nonepileptic seizures (PNES), captured using a wrist-worn accelerometer (ACM) device. The main goal was to find quantitative ACM features that can differentiate between convulsive epileptic and convulsive PNES. METHODS: In this study, motor data were recorded using wrist-worn ACM-based devices. A total of 83 clinical events were recorded: 39 generalized tonic-clonic seizures (GTCS) from 12 patients with epilepsy, and 44 convulsive PNES from 7 patients (one patient had both GTCS and PNES). The temporal variations in the ACM traces corresponding to 39 GTCS and 44 convulsive PNES events were extracted using Poincaré maps. Two new indices-tonic index (TI) and dispersion decay index (DDI)-were used to quantify the Poincaré-derived temporal variations for every GTCS and convulsive PNES event. RESULTS: The TI and DDI of Poincaré-derived temporal variations for GTCS events were higher in comparison to convulsive PNES events (P < 0.001). The onset and the subsiding patterns captured by TI and DDI differentiated between epileptic and convulsive nonepileptic seizures. An automated classifier built using TI and DDI of Poincaré-derived temporal variations could correctly differentiate 42 (sensitivity: 95.45%) of 44 convulsive PNES events and 37 (specificity: 94.87%) of 39 GTCS events. A blinded review of the Poincaré-derived temporal variations in GTCS and convulsive PNES by epileptologists differentiated 26 (sensitivity: 70.27%) of 44 PNES events and 33 (specificity: 86.84%) of 39 GTCS events correctly. SIGNIFICANCE: In addition to quantifying the motor manifestation mechanism of GTCS and convulsive PNES, the proposed approach also has diagnostic significance. The new ACM features incorporate clinical characteristics of GTCS and PNES, thus providing an accurate, low-cost, and practical alternative to differential diagnosis of PNES. Wiley Periodicals, Inc.
OBJECTIVE: To investigate the characteristics of motor manifestation during convulsive epileptic and psychogenic nonepileptic seizures (PNES), captured using a wrist-worn accelerometer (ACM) device. The main goal was to find quantitative ACM features that can differentiate between convulsive epileptic and convulsive PNES. METHODS: In this study, motor data were recorded using wrist-worn ACM-based devices. A total of 83 clinical events were recorded: 39 generalized tonic-clonic seizures (GTCS) from 12 patients with epilepsy, and 44 convulsive PNES from 7 patients (one patient had both GTCS and PNES). The temporal variations in the ACM traces corresponding to 39 GTCS and 44 convulsive PNES events were extracted using Poincaré maps. Two new indices-tonic index (TI) and dispersion decay index (DDI)-were used to quantify the Poincaré-derived temporal variations for every GTCS and convulsive PNES event. RESULTS: The TI and DDI of Poincaré-derived temporal variations for GTCS events were higher in comparison to convulsive PNES events (P < 0.001). The onset and the subsiding patterns captured by TI and DDI differentiated between epileptic and convulsive nonepileptic seizures. An automated classifier built using TI and DDI of Poincaré-derived temporal variations could correctly differentiate 42 (sensitivity: 95.45%) of 44 convulsive PNES events and 37 (specificity: 94.87%) of 39 GTCS events. A blinded review of the Poincaré-derived temporal variations in GTCS and convulsive PNES by epileptologists differentiated 26 (sensitivity: 70.27%) of 44 PNES events and 33 (specificity: 86.84%) of 39 GTCS events correctly. SIGNIFICANCE: In addition to quantifying the motor manifestation mechanism of GTCS and convulsive PNES, the proposed approach also has diagnostic significance. The new ACM features incorporate clinical characteristics of GTCS and PNES, thus providing an accurate, low-cost, and practical alternative to differential diagnosis of PNES. Wiley Periodicals, Inc.
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Authors: A Zsom; S Tsekhan; T Hamid; J Levin; W Truccolo; W C LaFrance; A S Blum; P Li; L A Wahed; M A Shaikh; G Sharma; R Ranieri; L Zhang Journal: Annu Int Conf IEEE Eng Med Biol Soc Date: 2019-07
Authors: Wesley T Kerr; Xingruo Zhang; Emily A Janio; Amir H Karimi; Corinne H Allas; Ishita Dubey; Siddhika S Sreenivasan; Janar Bauirjan; Shannon R D'Ambrosio; Mona Al Banna; Andrew Y Cho; Jerome Engel; Mark S Cohen; Jamie D Feusner; John M Stern Journal: Epilepsy Behav Date: 2021-01-01 Impact factor: 2.937