An Ultra-Low Power Smart Headband for Real-Time Epileptic Seizure Detection

Abstract

In this paper, the design of a smart headband for epileptic seizure detection is presented. The proposed headband consists of four key components: 1) an analog front-end circuitry; 2) an epileptic seizure detection tag (ESDT); 3) a Bluetooth low-power chip; and 4) customized electrodes. All the above components are integrated into a fabric headband with only 50.3 g. The smart headband system dissipates 55.89 mW. The epileptic seizure detection algorithm inside ESDT is validated by using Boston Children’s Hospital’s CHB-MIT scalp EEG clinical database with the detection rate of 92.68% and the false alarm of 0.527/h. We develop a service APP connected to the cloud so that the patients’ health condition can be recorded and then referenced by doctors for further diagnosis or research.

Prospecção tecnológica de internet das coisas no contexto dos hospitais inteligentes

“…No gerenciamento hospitalar, estudos de tecnologias baseadas na IoT tem investigado novas soluções aos registros eletrônicos do paciente, fazendo integração em nuvem (Riad, Hanza & Yan, 2019). Outras pesquisas têm procurado modernizar o cuidado com o paciente como dispositivos para prever e/ou alertar quedas (Liu et al, 2018), uma preocupação pertinente em hospitais; camas de hospitais acionadas sob o comando de voz (Kajol et al, 2019); tecnologias para monitoramento das funções cardíacas para prevenção de ataques cardíacos (Majumder et al, 2016); e tecnologias de previsão de crises epiléticas (Lin et al, 2018).…”

Ambulatory EEG: Crossing the divide during a pandemic

“…Some algorithms also contain alarms that sound when EEG seizures are detected. 94 The utility resides in permitting on- or off-site staff to apply and record EEG quickly with subsequent web access that allows rapid interpretation of the results. During COVID-19, rapid EEG devices may demonstrate utility in critically ill patients when access to EEG is personnel is limited and on-site ability to provide rapid feedback exists.…”

Epilepsy Seizure Detection and Prediction Based on DeviceHive

“…[6] Seizure monitoring and notification proof-of-concept wearable prototype that can detect specific seizure activity, namely generalized tonic-clonic seizures and designing a robust and computationally low intensive real-time seizure detection algorithm, and utilization of a scalable cloud-based data management system to record, analyze, and visualize the received seizure data. [7] The service APP connected to the cloud so that the patients' health condition can be recorded and then referenced by doctors for further diagnosis or research process. The only channel FP2-F8 for seizure detection to avoid using conductive adhesive.…”