A wearable sensor based multi-criteria-decision-system for real-time seizure detection

This paper presents a wireless, low power and low cost two part wearable for real-time epileptic seizure detection. Using parameters of Electro-cardiograph (ECG), Electro-dermal Activity (EDA), body motion and breathing rate (BR), a novel multi-criteria-decision-system (MCDS) is proposed that reduce...

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Published in2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) Vol. 2017; pp. 2377 - 2380
Main Authors Ahmed, Abdullah, Ahmad, Waqas, Khan, Muhammad Jazib, Siddiqui, Shoaib Ahmed, Cheema, Hammad M.
Format Conference Proceeding Journal Article
LanguageEnglish
Published United States IEEE 01.07.2017
Subjects
Algorithms
Anomaly detection
Biomedical monitoring
Electrocardiography
Epilepsy
Humans
Monitoring, Physiologic
Real-time systems
Seizures
Sensors
Smartphone
Wearable Electronic Devices
Wrist
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Summary:This paper presents a wireless, low power and low cost two part wearable for real-time epileptic seizure detection. Using parameters of Electro-cardiograph (ECG), Electro-dermal Activity (EDA), body motion and breathing rate (BR), a novel multi-criteria-decision-system (MCDS) is proposed that reduces false alarms and true negatives. The combination of a chest and hand worn wearable continuously senses these parameters transmitting the data to a smart phone application via BLE 4.0 where long-short-term-memory (LSTM) based anomaly detection algorithms and logistic classifiers decide on the occurrence of the seizure in real time. A 96% precision and 90% recall is achieved through testing on synthetic data.
ISSN:1557-170X
DOI:10.1109/EMBC.2017.8037334