Abhinav V Kurada1, Tarun Srinivasan2, Sarah Hammond3, Adriana Ulate-Campos4, Jonathan Bidwell5. 1. Department of Biomedical Engineering, Columbia University School of Engineering and Applied Science, New York, NY, USA. Electronic address: abhinav.kurada@columbia.edu. 2. Department of Biochemistry, Columbia University, New York, NY, USA. 3. Division of Epilepsy and Clinical Neurophysiology, Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA. 4. Department of Neurology, National Children's Hospital "Dr. Carlos Saenz Herrera", San José, Costa Rica. 5. Division of Epilepsy and Clinical Neurophysiology, Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; School of Interactive Computing, Georgia Institute of Technology, 85 Fifth Street NW, Atlanta, GA, USA.
Abstract
OBJECTIVE: This study characterizes the current capabilities of seizure detection device (SDD) technology and evaluates the fitness of these devices for use in anti-seizure medication (ASM) clinical trials. METHODS: Through a systematic literature review, 36 wireless SDDs featured in published device validation studies were identified. Each device's seizure detection capabilities that addressed ASM clinical trial primary endpoint measurement needs were cataloged. RESULTS: The two most common types of seizures targeted by ASMs in clinical trials are generalized tonic-clonic (GTC) seizures and focal with impaired awareness (FIA) seizures. The Brain Sentinel SPEAC achieved the highest performance for the detection of GTC seizures (F1-score = 0.95). A non-commercial wireless EEG device achieved the highest performance for the detection of FIA seizures (F1-score = 0.88). DISCUSSION: A preliminary assessment of device capabilities for measuring selected ASM clinical trial secondary endpoints was performed. The need to address key limitations in validation studies is highlighted in order to support future assessments of SDD fitness for ASM clinical trial use. In tandem, a stepwise framework to streamline device testing is put forth. These suggestions provide a starting point for establishing SDD reporting requirements before device integration into ASM clinical trials.
OBJECTIVE: This study characterizes the current capabilities of seizure detection device (SDD) technology and evaluates the fitness of these devices for use in anti-seizure medication (ASM) clinical trials. METHODS: Through a systematic literature review, 36 wireless SDDs featured in published device validation studies were identified. Each device's seizure detection capabilities that addressed ASM clinical trial primary endpoint measurement needs were cataloged. RESULTS: The two most common types of seizures targeted by ASMs in clinical trials are generalized tonic-clonic (GTC) seizures and focal with impaired awareness (FIA) seizures. The Brain Sentinel SPEAC achieved the highest performance for the detection of GTC seizures (F1-score = 0.95). A non-commercial wireless EEG device achieved the highest performance for the detection of FIA seizures (F1-score = 0.88). DISCUSSION: A preliminary assessment of device capabilities for measuring selected ASM clinical trial secondary endpoints was performed. The need to address key limitations in validation studies is highlighted in order to support future assessments of SDD fitness for ASM clinical trial use. In tandem, a stepwise framework to streamline device testing is put forth. These suggestions provide a starting point for establishing SDD reporting requirements before device integration into ASM clinical trials.
Authors: Jennifer Shum; Adam Fogarty; Patricia Dugan; Manisha G Holmes; Beth A Leeman-Markowski; Anli A Liu; Robert S Fisher; Daniel Friedman Journal: Seizure Date: 2020-03-18 Impact factor: 3.184
Authors: A Schulze-Bonhage; S Böttcher; M Glasstetter; N Epitashvili; E Bruno; M Richardson; K V Laerhoven; M Dümpelmann Journal: Nervenarzt Date: 2019-12 Impact factor: 1.214
Authors: Anouk van Westrhenen; George Petkov; Stiliyan N Kalitzin; Richard H C Lazeron; Roland D Thijs Journal: Epilepsia Date: 2020-05-07 Impact factor: 5.864
Authors: Amirhossein Jahanbekam; Jan Baumann; Robert D Nass; Christian Bauckhage; Holger Hill; Christian E Elger; Rainer Surges Journal: Epilepsia Open Date: 2021-07-20