UC Berkeley

Topics in Computer Systems CS262a Fall’13

Orianna DeMasi Jordan Kellerstrass

http://github.com/odemasi/OpenEmo

The open source system for EEG data collection

Solution OpenEmo is an open source adapter which makes commodity EEG devices mobile and thus available to take emerging medical research into practice. The OpenEmo system enables data collection for large scale studies and opens the possibility for current research to be utilized in areas with community health workers (CHW).

Problem Behavioral clues are the current means of diagnosis for many neuropsychological disorders. Research shows that EEG scans could be used for diagnosis*, but current EEG devices are not mobile enough to be used outside of clinics. In addition, the compute infrastructure is not in place to do large scale studies and implement diagnostic methods in resource poor areas with community healthcare models

OpenEmo is a mobile health device.

It reads data from an EEG headset dongle, decodes it and sends it wirelessly to an Android device.

Data is sent from the phone into the cloud for evaluation and research.

Caption here. Hooray! I am a caption, and I am happy to be a caption.

This diagram shows the flow of data

Implementation Community health clinic

Our product can be easily integrated into a community healthcare model. It is inexpensive and low power enough to be made available to community health workers. These workers visit people in their homes to provide basic care and connect them with further resources when necessary.

* “EEG as a Biomarker for Autism Spectrum Disorder Risk” Bosl et al. BMC Medicine 2011

OpenEmo’s user interface makes it easy to understand and use.

Design Considerations Data flow Energy Medical data integrity Time & Money

Implementation OpenEmo reads data from dongle supported EEG devices, decodes it, and sends it, through a mobile phone, into the cloud for evaluation. OpenEmo is currently compatible with the popular Emotiv EPOC headset and Android. OpenEmo can be made compatible with any dongle supported EEG device. OpenEmo is prototyped with a Raspberry Pi and Bluetooth 3.0+HS. It uses DropBox to transfer data from mobile phones and tablets to research servers.

Energy Considerations OpenEmo reads EEG data from dongle supported devices and sends it, through a mobile phone, into the cloud for evaluation. OpenEmo is currently compatible with the popular Epoc headset, but can be made Costsupported EEG device.

Hospitals & Researchers

OpenEmo

Evaluation

Data flow model

Project Scale

# CHW in Kenya 15000 patients/CHW 50-500 CHW visits/day 15 EEG file size 860KB - 7.7MB sample frequency 128 - 250 Hz number of channels 14 - 64

Project Cost System

Component Price OpenEmo Part Price

Dropbox 2/50/100GB $0/99/199 Battery $19.96

OpenEmo $64.72 Raspberry Pi $35.00

Nexus 5 $349.00 Bluetooth 3.0 $8.76

Nexus 7 (donated) $229.00 LED's $1.00

EPOC (donated) $299.00 Total $64.72

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startup sampling EPOC

sending bluetooth

shutdown idle/sec

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Energy Breakdown OpenEmo

Encrypted

Solution Research shows some neuropsychological disorders (e.g. autism) can be identified via electroencephalography (EEG) scans years before behavioral signs*. OpenEmo is an adapter that makes commodity EEG devices available to take this research into practice.

Final Prototype For less than $65 OpenEmo can make an EEG device compatible with an Android phone and thus available to a community health worker and an entire community. OpenEmo is low power – it currently will last up to a week without recharging. The headset will last for 16 days without recharging. OpenEmo is currently compatible with the popular EPOC headset. Future generations will be compatible with more headsets and contain predictive features in the app.

Design Considerations OpenEmo’s goal is to make EEG technology, such as the Emotiv EPOC, accessible. The most important design features are that the entire system be mobile, low cost, and low energy.

Future Work Future generations will be compatible with more dongle supported devices and will have predictive features in the app. Dynamic plotting and machine learning on the server will also be implemented. Multiple levels of encryption between devices will be considered for patient data safety and data quality will be improved.

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OpenEmo Nexus phone Nexus tablet EPOC headset

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EEG Samples per Charge (system runs for 3.8 visit-days)

Energy estimates assume 3 minute EEG samples (based on previous research*). A visit-days consists of 15 samples.