Multimodal wearable EEG, EMG and accelerometry measurements improve the accuracy of tonic-clonic seizure detection.

Objective. This paper aims to investigate the possibility of detecting tonic-clonic seizures (TCSs) with behind-the-ear, two-channel wearable electroencephalography (EEG), and to evaluate its added value to non-EEG modalities in TCS detection.Methods. We included 27 participants with a total of 44 TCSs from the European multicenter study SeizeIT2. The wearable Sensor Dot (Byteflies) was used to measure behind-the-ear EEG, electromyography (EMG), electrocardiography, accelerometry (ACC) and gyroscope. We evaluated automatic unimodal detection of TCSs, using sensitivity, precision, false positive rate (FPR) and F1-score. Subsequently, we fused the different modalities and again assessed performance. Algorithm-labeled segments were then provided to two experts, who annotated true positive TCSs, and discarded false positives.Results. Wearable EEG outperformed the other single modalities with a sensitivity of 100% and a FPR of 10.3/24 h. The combination of wearable EEG and EMG proved most clinically useful, delivering a sensitivity of 97.7%, an FPR of 0.4/24 h, a precision of 43%, and an F1-score of 59.7%. The highest overall performance was achieved through the fusion of wearable EEG, EMG, and ACC, yielding a sensitivity of 90.9%, an FPR of 0.1/24 h, a precision of 75.5%, and an F1-score of 82.5%.Conclusions. In TCS detection with a wearable device, combining EEG with EMG, ACC or both resulted in a remarkable reduction of FPR, while retaining a high sensitivity.Significance. Adding wearable EEG could further improve TCS detection, relative to extracerebral-based systems.

Risk for injuries and accidents in epilepsy: A prospective population-based cohort study.

OBJECTIVE: To study the risk for injuries/accidents in people with newly diagnosed epileptic seizures in relation to comorbidities. METHODS: Between September 1, 2001, and August 31, 2008, individuals in northern Stockholm with incident unprovoked seizures (epilepsy; n = 2,130) were included in a registry. For every epilepsy patient, 8 individuals matched for sex and inclusion year (n = 16,992) were randomly selected as references from the population of the catchment area. Occurrence of injuries/accidents was monitored through the national patient and cause of death registers until December 31, 2013. These registers also provided information on comorbidities (e.g., brain tumor, stroke, psychiatric disease, diabetes mellitus). RESULTS: Injury/accident was demonstrated in 1,033 epilepsy cases and 6,202 references (hazard ratio [HR] 1.71, 95% confidence interval 1.60-1.83). The excess risk was seen mainly during the first 2 years after diagnosis. Sex and educational status had no significant effect on HR. The risk was normal in children but increased in adults. Highest HR was seen for drowning, poisoning, adverse effect of medication, and severe traumatic brain injury. Compared to references without comorbidities, HR was 1.17 (1.07-1.28) in epilepsy without comorbidities, 4.52 (4.18-4.88) in references with comorbidities, and 7.15 (6.49-7.87) in epilepsy with comorbidities. CONCLUSION: Presence of comorbidities should be considered when counseling patients with newly diagnosed epilepsy concerning risk for injuries/accidents. Early information is important, as the risk is highest during the first 2 years following seizure onset.

Unprovoked seizures after traumatic brain injury: A population-based case-control study.

OBJECTIVE: To quantify the risk of unprovoked seizures after traumatic brain injury (TBI) METHODS: We used the Stockholm Incidence Registry on Epilepsy to carry out a population-based case-control study, including 1,885 cases with incident unprovoked seizures from September 1, 2000 through August 31, 2008, together with 15,080 matched controls. Information of prior hospitalizations for TBI was obtained through record linkage with the Swedish National Inpatient Registry for the period 1980-2008. Relative risks (RRs) for unprovoked seizures were estimated after various TBI diagnoses, and influences of TBI severity and time since trauma were studied in detail. RESULTS: After hospitalization for mild TBI, the RR was 2.0 (95% confidence interval [CI] 1.5-2.7). The RR was higher after brain contusion (5.9, 95% CI 2.4-15.0) or intracranial hemorrhage (ICH) (4.5, 95% CI 2.2-9.0), whereas a combination of both diagnoses led to a further sevenfold increase in RR (42.6, 95% CI 12.2-148.5). The risk was greatest during the first 6 months after severe TBI (RR 48.9, 95% CI 10.9-218.9) or mild TBI (RR 8.1, 95% CI 3.1-21.7), but was still elevated >10 years after any TBI. SIGNIFICANCE: Herein we present a large population-based case-control study on TBI as a risk factor for unprovoked epileptic seizures, including cases of all ages with individually validated seizure diagnoses. The risk for epileptic seizures was substantially increased after TBI, especially during the first 6 months after the injury and in patients with a combination of ICH and brain contusion.