EMG-Based Seizure Detection System


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Membership level
2013-2014 Team
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Team Name
Project Title
EMG-Based Seizure Detection System
Design Challenge
We are developing a seizure monitoring device which incorporates an electromyography sensor. The sensor should be designed so that it can be attached to the arms or upper torso of a patient's body. The EMG sensor shall detect muscle activity that is typical of the physiological response resulting from a convulsive epileptic seizure. The system shall be able to differentiate normal activity from activity resulting from seizures.
Design Summary
Design Goals:
• Noticeable difference in different muscle activities: resting, voluntary contraction, maximum contraction

• Time between contraction onset and algorithm detection (≤ 5 seconds)

• Prompt caretaker notification (≤ 5 seconds)

• Reliable fault detection for device detachment (≤ 5 seconds)

• Battery life of > 12 hours

• Less than $300

We have four subsystems: the selected muscle group, an electrode patch, a sensor unit, and a detection algorithm. The muscle group is the lateral deltoid. The electrode patch will be disposable and houses two Easytrode electrodes (Prometheus Group, Dover, NH) and a 3V coin cell battery. The patch attaches to the sensor unit that performs signal processing. Finally, our detection algorithm is embedded in an Arduino that is connected to the sensor unit. It analyzes processed EMG data in real time and detects seizures and electrode detachment.

Current Status:
Currently, we have developed a prototype that consists of a patch, printed circuit board, Arduino, and Bluetooth Low Energy transceiver. It is able to collect and filter EMG data from the lateral deltoid in real time. Additionally, we have implemented an algorithm to detect maximum deltoid contractions that are similar to seizure contractions and electrode detachment. The results are sent over Bluetooth Low Energy to a receiver.

Last Updated May 3, 2014.
Sponsor Logo
  • Bioengineering
Faculty Advisor 1 - Name
Dr. Gary L. Woods
Faculty Advisor 1 - Department
  • ECE
Faculty Advisor 2 - Name
Dr. Eric Richardson
Faculty Advisor 2 - Department
  • BIOE

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