Literature DB >> 27741462

Patient-centered design criteria for wearable seizure detection devices.

Anup D Patel1, Robert Moss, Steven W Rust2, Jeremy Patterson2, Robert Strouse2, Satyanarayana Gedela3, Jesse Haines2, Simon M Lin2.   

Abstract

INTRODUCTION: Epilepsy is a common neurological condition. Seizure diary reports and patient- or caregiver-reported seizure counts are often inaccurate and underestimated. Many caregivers express stress and anxiety about the patient with epilepsy having seizures when they are not present. Therefore, a need exists for the ability to recognize and/or detect a seizure in the home setting. However, few studies have inquired on detection device features that are important to patients and their caregivers.
METHODS: A survey instrument utilizing a population of patients and caregivers was created to obtain information on the design criteria most desired for patients with epilepsy in regard to wearable devices.
RESULTS: One thousand one hundred sixty-eight responses were collected. Respondents thought that sensors for muscle signal (61.4%) and heart rate (58.0%) would be most helpful followed by the O2 sensor (41.4%). There was more interest in these three sensor types than for an accelerometer (25.5%). There was very little interest in a microphone (8.9%), galvanic skin response sensor (8.0%), or a barometer (4.9%). Based on a rating scale of 1-5 with 5 being the most important, respondents felt that "detecting all seizures" (4.73) is the most important device feature followed by "text/email alerts" (4.53), "comfort" (4.46), and "battery life" (4.43) as an equally important group of features. Respondents felt that "not knowing device is for seizures" (2.60) and "multiple uses" (2.57) were equally the least important device features. Average ratings differed significantly across age groups for the following features: button, multiuse, not knowing device is for seizures, alarm, style, and text ability. The p-values were all<0.002. Eighty-two point five percent of respondents [95% confidence interval: 80.0%, 84.7%] were willing to pay more than $100 for a wearable seizure detection device, and 42.8% of respondents [95% confidence interval: 39.8%, 45.9%] were willing to pay more than $200.
CONCLUSIONS: Our survey results demonstrated that patients and caregivers have design features that are important to them in regard to a wearable seizure detection device. Overall, the ability to detect all seizures rated highest among respondents which continues to be an unmet need in the community with epilepsy in regard to seizure detection. Additional uses for a wearable were not as important. Based on our results, it is important that an alert (via test and/or email) for events be a portion of the system. A reasonable price point appears to be around $200 to $300. An accelerometer was less important to those surveyed when compared with the use of heart rate, oxygen saturation, or muscle twitches/signals. As further products become developed for use in other health arenas, it will be important to consider patient and caregiver desires in order to meet the need and address the gap in devices that currently exist.
Copyright © 2016 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Seizure detection; Survey

Mesh:

Year:  2016        PMID: 27741462     DOI: 10.1016/j.yebeh.2016.09.012

Source DB:  PubMed          Journal:  Epilepsy Behav        ISSN: 1525-5050            Impact factor:   2.937


  9 in total

Review 1.  Seizure detection: do current devices work? And when can they be useful?

Authors:  Xiuhe Zhao; Samden D Lhatoo
Journal:  Curr Neurol Neurosci Rep       Date:  2018-05-23       Impact factor: 5.081

Review 2.  [Mobile seizure monitoring in epilepsy patients].

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

3.  Automated real-time detection of tonic-clonic seizures using a wearable EMG device.

Authors:  Sándor Beniczky; Isa Conradsen; Oliver Henning; Martin Fabricius; Peter Wolf
Journal:  Neurology       Date:  2018-01-05       Impact factor: 9.910

4.  Owner's Perception of Seizure Detection Devices in Idiopathic Epileptic Dogs.

Authors:  Jos Bongers; Rodrigo Gutierrez-Quintana; Catherine Elizabeth Stalin
Journal:  Front Vet Sci       Date:  2021-12-09

5.  Ambulatory seizure forecasting with a wrist-worn device using long-short term memory deep learning.

Authors:  Mona Nasseri; Tal Pal Attia; Boney Joseph; Nicholas M Gregg; Ewan S Nurse; Pedro F Viana; Gregory Worrell; Matthias Dümpelmann; Mark P Richardson; Dean R Freestone; Benjamin H Brinkmann
Journal:  Sci Rep       Date:  2021-11-09       Impact factor: 4.379

6.  A Patient Perspective on Seizure Detection and Forecasting.

Authors:  Aria Moss; Evan Moss; Robert Moss; Lisa Moss; Sharon Chiang; Peter Crino
Journal:  Front Neurol       Date:  2022-02-11       Impact factor: 4.003

7.  Parental preferences for seizure detection devices: A discrete choice experiment.

Authors:  Anouk van Westrhenen; Ben F M Wijnen; Roland D Thijs
Journal:  Epilepsia       Date:  2022-03-04       Impact factor: 6.740

8.  Electrographic seizure monitoring with a novel, wireless, single-channel EEG sensor.

Authors:  Mitchell A Frankel; Mark J Lehmkuhle; Meagan Watson; Kirsten Fetrow; Lauren Frey; Cornelia Drees; Mark C Spitz
Journal:  Clin Neurophysiol Pract       Date:  2021-05-29

Review 9.  Seizure Diaries and Forecasting With Wearables: Epilepsy Monitoring Outside the Clinic.

Authors:  Benjamin H Brinkmann; Philippa J Karoly; Ewan S Nurse; Sonya B Dumanis; Mona Nasseri; Pedro F Viana; Andreas Schulze-Bonhage; Dean R Freestone; Greg Worrell; Mark P Richardson; Mark J Cook
Journal:  Front Neurol       Date:  2021-07-13       Impact factor: 4.003

  9 in total

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