3D printing technology has breakthrough many long pending medical challenges. In this study the researchers are addressing epilepsy, a disability that limits mobility freedom, that can appear at any age but usually start in childhood or people over 60 years old. Diagnosing epilepsy quickly can be challenging due to the fact other conditions such as migraines, panic attacks and fainting possess similar symptoms. Regularly, it cannot be confirmed until seizure is detected. Electroencephalogram (EEG) is the most common test used to diagnose epilepsy. Epileptiform brain activity presence is used as a change seen on an EEG recording among epilepsy patients. The availability of EEG device for epilepsy diagnosis is currently limited to clinical settings which restricts the treatment process. The objective of this study is to offer an option for personalized home-based EEG device for epilepsy diagnosis and monitoring. A customized 3D printed EEG headset with 8 channel dry electrodes device is assembled and configured. The customization is managed by offering three different printable headset sizes with material selection options. The device is supported with an OpenBCI application connected through Bluetooth for recording and further processing options. The proposed device has potential to address number of limitations including the recent pandemic’s challenge where hospitalization option is restricted. The outcome of the research is expected to bring a new breakthrough in brain activity related research and clinical diagnosis in patient monitoring. The customization option of this device is also expected to offer a new trend in managing treatment compliance and adherence in clinical practice.
Ambulatory EEGs began emerging in the healthcare industry over the years, setting a new norm for long-term monitoring services. The present devices in the market are neither meant for remote monitoring due to their technical complexity nor for meeting clinical setting needs in epilepsy patient monitoring. In this paper, we propose an ambulatory EEG device, OptiEEG, that has low setup complexity, for the remote EEG monitoring of epilepsy patients. OptiEEG’s signal quality was compared with a gold standard clinical device, Natus. The experiment between OptiEEG and Natus included three different tests: eye open/close (EOC); hyperventilation (HV); and photic stimulation (PS). Statistical and wavelet analysis of retrieved data were presented when evaluating the performance of OptiEEG. The SNR and PSNR of OptiEEG were slightly lower than Natus, but within an acceptable bound. The standard deviations of MSE for both devices were almost in a similar range for the three tests. The frequency band energy analysis is consistent between the two devices. A rhythmic slowdown of theta and delta was observed in HV, whereas photic driving was observed during PS in both devices. The results validated the performance of OptiEEG as an acceptable EEG device for remote monitoring away from clinical environments.
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