Evaluation and recommendations for effective data visualization for seizure forecasting algorithms.
Sharon Chiang,Robert Moss,Angela P Black,Michele Jackson,Chuck Moss,Jonathan Bidwell,Christian Meisel,Tobias Loddenkemper +7 more
- 01 Mar 2021
- Vol. 4, Iss: 1
TL;DR: In this paper, the authors developed front-end data visualizations as part of a Seizure Forecast Visualization Toolkit and surveyed 627 people living with epilepsy and caregivers, and 28 epilepsy healthcare providers.
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Abstract: Objective Seizure forecasting algorithms have become increasingly accurate and may reduce the morbidity and mortality caused by seizure unpredictability. Translating these benefits into meaningful health outcomes for people with epilepsy requires effective data visualization of algorithm outputs. To date, no studies have investigated patient and physician perspectives on effective translation of algorithm outputs into data visualizations through health information technology. Materials and methods We developed front-end data visualizations as part of a Seizure Forecast Visualization Toolkit. We surveyed 627 people living with epilepsy and caregivers, and 28 epilepsy healthcare providers. Respondents scored each visualization in terms of international standardized software quality criteria for functionality, appropriateness, and usability. Results People with epilepsy and caregivers ranked hourly radar charts highest for protecting against errors in interpreting forecasts, reducing anxiety from seizure unpredictability, and understanding seizure patterns. Accuracy in interpreting visuals, such as a risk gauge, was dependent on seizure frequency. Visuals showing hourly/daily forecasts were more useful for patients who experienced seizure cycling than those who did not. Hourly line graphs and monthly heat maps were rated highest among clinicians for ease of understanding, anticipated integration into clinical practice, and the likelihood of clinical usage. Epilepsy providers indicated that daily heat maps, daily line graphs, and hourly line graphs were most useful for interpreting seizure diary patterns, assessing therapy impact, and counseling on seizure safety. Discussion The choice of data visualization impacts the effective translation of seizure forecast algorithms into meaningful health outcomes. Conclusion This effort underlines the importance of incorporating standardized, quantitative methods for assessing the effectiveness of data visualization to translate seizure forecast algorithms into clinical practice.
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Citations
Seizure diaries and forecasting with wearables: epilepsy monitoring outside the clinic
Benjamin H. Brinkmann,Philippa J. Karoly,Ewan S. Nurse,Sonya B. Dumanis,Mona Nasseri,Mona Nasseri,Pedro Viana,Pedro Viana,Andreas Schulze-Bonhage,Dean R. Freestone,Greg Worrell,Mark P. Richardson,Mark J. Cook +12 more
TL;DR: In this article, a review of the current evidence and challenges in the use of minimally and non-invasive devices for long-term epilepsy monitoring, the essential components in remote monitoring systems, and explores the feasibility to detect and forecast impending seizures via longterm use of these systems.
Seizure forecasting: bifurcations in the long and winding road.
Maxime O. Baud,Timothée Proix,Nicholas M. Gregg,Benjamin H. Brinkmann,Ewan S. Nurse,Mark J. Cook,Philippa J. Karoly +6 more
TL;DR: This review covers the most recent scientific, technical and medical developments, discusses methodology in detail and sets a number of goals for future studies.
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The Challenging Path to Developing a Mobile Health Device for Epilepsy: The Current Landscape and Where We Go From Here.
TL;DR: In this paper, the authors provide an overview of the challenges and current technological landscape of wearable devices and mobile health devices for seizure detection, and provide insight into current clinical practice guidelines, main outcomes of clinical validation studies, and discuss how to evaluate device performance at point of care facilities.
Systemic inflammation as a biomarker of seizure propensity and a target for treatment to reduce seizure propensity
TL;DR: In this article , the authors present a closed-loop device where release of a fast-acting therapy is governed by sensors that quantify the magnitude of systemic inflammation, and then consider the options of what might be incorporated into a responsive anti-seizure system.
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User experience of a seizure risk forecasting app: A mixed methods investigation
Rachel E Stirling,Ewan S. Nurse,Daniel E. Payne,J. Naim-Feil,Honor Coleman,Dean R. Freestone,Mark P. Richarson,Benjamin H. Brinkmann,Wendyl D'Souza,David B. Grayden,Mark J. Cook,Philippa J. Karoly +11 more
Abstract: OBJECTIVE
Over recent years, there has been a growing interest in exploring the utility of seizure risk forecasting, particularly how it could improve quality of life for people living with epilepsy. This study reports on user experiences and perspectives of a seizure risk forecaster app, as well as the potential impact on mood and adjustment to epilepsy.
METHODS
Active app users were asked to complete a survey (baseline and 3-month follow-up) to assess perspectives on the forecast feature as well as mood and adjustment. Post-hoc, nine neutral forecast users (neither agreed nor disagreed it was useful) completed semi-structured interviews, to gain further insight into their perspectives of epilepsy management and seizure forecasting. Non-parametric statistical tests and inductive thematic analyses were used to analyse the quantitative and qualitative data, respectively.
RESULTS
Surveys were completed by 111 users. Responders consisted of "app users" (n = 58), and "app and forecast users" (n = 53). Of the "app and forecast users", 40 % believed the forecast was accurate enough to be useful in monitoring for seizure risk, and 60 % adopted it for purposes like scheduling activities and helping mental state. Feeling more in control was the most common response to both high and low risk forecasted states. In-depth interviews revealed five broad themes, of which 'frustrations with lack of direction' (regarding their current epilepsy management approach), 'benefits of increased self-knowledge' and 'current and anticipated usefulness of forecasting' were the most common.
SIGNIFICANCE
Preliminary results suggest that seizure risk forecasting can be a useful tool for people with epilepsy to make lifestyle changes, such as scheduling daily events, and experience greater feelings of control. These improvements may be attributed, at least partly, to the improvements in self-knowledge experienced through forecast use.
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