Presentation
Epilog: A Human Centered Design Proposal for Seizure Management
SessionPoster Session 2
DescriptionEpilepsy is a chronic neurological disorder affecting over 50 million individuals worldwide, that causes seizures which are difficult to manage and predict. The primary seizure management protocol depends on the person with epilepsy and their caregivers to track and report the epileptic events, medication, diet, exercise, and any other factors that could be contributing to the frequency of events. One of the major challenges that patients, caregivers, and healthcare providers face is the lack of commercially available and cost effective tools for reliably tracking their events and the other contributing factors. Patients experience frustration with this process and are further irritated by the lack of insights gleaned from the recorded data.
Currently, there are a few mobile applications available on the market for seizure tracking and management. A competitor analysis revealed a focus on self reporting to log seizures and medication schedules with some using biometric tracking for convulsive seizures. In the commercially available applications, there is a major gap in data synthesis, non-convulsive episode tracking, and personalization. Prior studies have demonstrated that wearable devices can detect convulsive seizure activity which can be helpful for automatic seizure tracking and event logging. However, these advancements in existing research fail to meet user needs of integrating and analyzing data in a meaningful way and providing actionable insights for preventative care. The outcome is that many users discontinue current tracking methods as the application doesn’t provide seizure management insights.
This study employed a mixed-methods design process, comprising literature reviews, competitor analysis, a survey with 21 participants, and three interviews with patients and caregivers. The main insights showed strong user demand for simple tracking, caregiver collaborations, and forecasting insights. Based on these findings, we developed EpiLog, a biometric-assisted mobile application that integrates wearable data, environmental triggers (i.e., noise and heat), and lifestyle tracking (i.e., sleep, period, medication, diet, and mood). EpiLog’s main contributions are voice-assisted logging to reduce cognitive burden, predictive text based on word frequency analysis, seizure risk forecasting, and real-time caregiver alerts. The results demonstrate that biometric integration and user-centered design can change seizure management from reactive tracking to proactive prevention, improving independence, safety, and quality of life for individuals with epilepsy.
Currently, there are a few mobile applications available on the market for seizure tracking and management. A competitor analysis revealed a focus on self reporting to log seizures and medication schedules with some using biometric tracking for convulsive seizures. In the commercially available applications, there is a major gap in data synthesis, non-convulsive episode tracking, and personalization. Prior studies have demonstrated that wearable devices can detect convulsive seizure activity which can be helpful for automatic seizure tracking and event logging. However, these advancements in existing research fail to meet user needs of integrating and analyzing data in a meaningful way and providing actionable insights for preventative care. The outcome is that many users discontinue current tracking methods as the application doesn’t provide seizure management insights.
This study employed a mixed-methods design process, comprising literature reviews, competitor analysis, a survey with 21 participants, and three interviews with patients and caregivers. The main insights showed strong user demand for simple tracking, caregiver collaborations, and forecasting insights. Based on these findings, we developed EpiLog, a biometric-assisted mobile application that integrates wearable data, environmental triggers (i.e., noise and heat), and lifestyle tracking (i.e., sleep, period, medication, diet, and mood). EpiLog’s main contributions are voice-assisted logging to reduce cognitive burden, predictive text based on word frequency analysis, seizure risk forecasting, and real-time caregiver alerts. The results demonstrate that biometric integration and user-centered design can change seizure management from reactive tracking to proactive prevention, improving independence, safety, and quality of life for individuals with epilepsy.
Event Type
Poster Presentation
TimeTuesday, March 244:45pm - 6:15pm EDT
LocationRhinelander Gallery
Digital Health