A Model for real time monitoring of epileptic patients

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dc.contributor.authorOnyango, Christine Apondi
dc.date.accessioned2018-07-23 13:41:19.539
dc.date.available2018-07-23 13:41:19.539
dc.date.issued2017
dc.descriptionThesis submitted in partial fulfillment of the requirements for the Degree of Master of Science in Information Technology (MSIT) at Strathmore Universityen_US
dc.description.abstractEffective treatment and therapy in epileptic patients require thorough monitoring of seizures. Medical care givers require information on number of seizure occurrences, duration of seizure and magnitude. People suffering from epilepsy face tremendous problems in regards to epileptic seizure monitoring. The typical way to diagnose and monitor epileptic patients is by use of electroencephalography (EEG) which requires monitoring within the confines of the hospital. EEG equipment is available in very few hospitals in Kenya and that is an impediment to proper therapy and treatment for epileptic patients. The challenges faced in using the existing methods include; lack of flexibility for the patient as there is need for long term monitoring in a hospital setup, financial burden on the patients when they are hospitalized and obtrusive nature of the EEG monitoring making it not suitable for monitoring outdoors. This study applies agile methodology to design, develop and test a model for real time monitoring of patients with tonic-clonic epileptic seizures. This model is hardware based, with the capability to send alerts to a family member in the event of a seizure. The patient can also view their seizure history from a mobile application installed on their smartphones. The device was created using Arduino Uno, a tri-axis accelerometer for motion detection and a Global system for Mobile Communication (GSM) module for communication. This model promotes long term, flexible and inexpensive mode of epileptic seizure monitoring therefore contributing to effective treatment of epileptic patients.en_US
dc.identifier.urihttp://hdl.handle.net/11071/5665
dc.language.isoenen_US
dc.publisherStrathmore Universityen_US
dc.subjectWearable devicesen_US
dc.subjectSmart phone cameraen_US
dc.subjectSeizure Monitoringen_US
dc.subjectElectroencephalographyen_US
dc.subjectEEGen_US
dc.titleA Model for real time monitoring of epileptic patientsen_US
dc.typeThesisen_US
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MSIT Theses and Dissertations (2017)