Drug-resistance is a prevalent condition in children and adult patients with epilepsy. The quality of life of these patients is profoundly affected by the unpredictability of seizure ccurrence. Some of these patients are capable of reporting self-prediction of their seizures by observing their affectivity. Some patients report no signs of feeling premonitory symptoms, prodromes, or aura. In this paper, we propose a concept study that will provide objective information to self-predict seizures for both the patient groups. We will develop a model using digital phenotyping which takes both ecological momentary assessment and data from sensor technology into consideration. This method will be able to provide a feedback of their premonitory symptoms so that a pre-emptive therapy can be associated to reduce seizure frequency or eliminate seizure occurrence.
Objectives and Research Question
Within this research framework, the main objective is to quantify prodromes and premonitory symptoms in the pre-ictal and the interictal state of the brain consecutively, which leads to the following research questions:
- Which affective states are responsible for preceding seizures in the pre-ictal and inter-ictal phase? Is it possible to extract more reliable and conclusive outcomes on affective states preceding seizures compared to the state-of-art discussed?
- Is it possible to demonstrate the patient-reported feelings of prodromes or premonitory symptoms of seizure self-prediction by physiological measures?
- To improve the QoL, is it possible to provide objective information of prodromes or premonitory symptoms from physiological measures to PWE who can not self-predict seizure?
- Sensitivity: what percentage of seizures which are preceded by prodromes or premonitory symptoms can be detected using the proposed system? What are the correct PPV and correct NPV of seizures? Does it comprehend the state of the art findings?
- False prediction rate: what percentage of specificity can be achieved?
At the beginning of our study, we will choose a set of patients according to the criterion mentioned above and monitor them for two weeks as a baseline study. As depicted in figure 1, the PWE will be divided into two groups: group 1: who are capable of reporting premonitory symptoms and/or prodromes and group 2: who do not report of premonitory symptoms and/or prodromes. Both the groups will answer questions from the Beck Depression Inventory-II (BDI), Generalized Anxiety Disorder–7 (GAD), State-Trait Anxiety Inventory (STAI), Self-Efficacy Scale, and Positive and Negative Affect Schedule (PANAS) screening tools. The scores from these screening tools will be essential to do the psychometric evaluation of depression, anxiety, stress, and affectivity, which will be used as ground truth for PWE. Along with that, each PWE will be given a smartphone with E-diary App developed in . In this App, they will log their seizures, premonitory symptoms, sleep hours, medication adherence, menstrual cycle, current illness once in a day at a randomly prompted time. The PWE also has to complete multiple mood items adapted from the circumplex models of affect using a visual analog scale. The PWE will be prompted to fill in this mood model and will be asked by the application to mention their contextual information at randomly sampled intervals daily. To measure the physiological signals such as HRV, EDA, unobtrusively, the PWE will be asked to wear smart wearable devices containing multiple sensors. These physiological signals will provide objective information about their affectivity. For group 1, we will try to recognize patient-reported premonitory symptoms preceding seizures with the physiological signals measured. For group 2, we will try to find abnormalities in the physiological signals that might have led to a seizure.
In the next two weeks, we would monitor the PWE in the hospital and observe them with video-EEG. These patients will have minimum movement restrictions to make the data more realistic to real life. To compare the emotional intensity with the previous baseline study for each patient, the emotional regulations will be evaluated by presenting five films inducing emotional responses discussed in . The skin conductance will be monitored while performing the attention task and suppression task. Apart from that, the PWE will be asked to perform simple cognitive task by solving arithmetic problems with the App used in . The physiological signals will be monitored for the whole period of study. Before leaving the hospital, the PWE will be asked to fill up the set of questions in the inventory mentioned earlier. After this hospital settings, the patients will be monitored for two more weeks in an uncontrolled environment. At that time, the physiological signals, the questionnaires from the inventory and E-diary will be monitored again. This data will be used for a comparison study with the baseline and the hospital study. The processing of the collected data will be used to set up a model explained in the next section and the timeline of the research is summarized in table 1.