Contact Us

Use the form on the right to contact us.

You can edit the text in this area, and change where the contact form on the right submits to, by entering edit mode using the modes on the bottom right. 

Name *
Name
         

123 Street Avenue, City Town, 99999

(123) 555-6789

email@address.com

 

You can set your address, phone number, email and site description in the settings tab.
Link to read me page with more information.

2015

List of projects undertaken in the year 2015. This includes volunteer, capstone, and class projects

Filtering by Tag: Capstone

Memory-Assistive Glasses

Enabling Engineering

The Need

Memory loss is a serious issue for both the affected individual and those who surround them. Today, an estimated 5.2 million Americans have some stage of Alzheimer’s, a disease that attacks the brain and causes memory loss and dementia. People with Alzheimer’s or other forms of memory loss often struggle with recognizing faces and remembering how to perform basic tasks. These individuals are often required to be aided by family members, nurses, and are sometimes forced to live in assisted living residences. According to the Alzheimer’s Association, “in 2013, 15.5 million caregivers provided more than 17.5 billion hours of unpaid care valued at over $220 billion”.!

The Project

Our goal was to help memory-impaired individuals, such as early stage Alzheimer’s patients, by identifying people they come in contact with, identifying objects, and displaying step-by-step instructions for simple tasks. Our design uses Google Glass to interface with the user, which includes a small display, a 5MP camera, a bone-conduction speaker, and a touchpad. Using Google Glass and an Android application, the user takes a picture of people they would like to recognize and adds the picture to a database.
When the user would like to identify someone, they take a picture of the person and Google Glass displays the matched person’s name and relationship on Glass’s display. If that person is not found in the database, the user must add the person to the database via our Android application. Memory-impaired individuals also have difficulty remembering steps for simple tasks, such as where to put the dishes after unloading the dishwasher. Using our application, the user scans the QR code and the corresponding steps are displayed to the user on the Glass’s display .

Current status

This project is complete and won third prize in the NU Capstone Design Competition.

Neurodot Interface

Enabling Engineering

Background

The Neurodot, developed by Professors Sridhar and Chowdhury at Northeastern University, is a compact Electroencephalography (EEG) device. The Neurodot is a smaller EEG device that eliminates the need for several reference sensors placed across the face due to its tactical placement in the center of a patients scalp which is used as a reference ground. The device allows for a real-time, non-invasive monitoring of brain activity and is associated with a higher performance and sensitivity as compared to conventional sensors The Neurodot can be used to connect allow an individual who cannot communicate to use brain signals to control devices in their environment.

The Need

To make the Neurodot a more viable solution, Bluetooth communication between the Neurodot and a computer is needed to enable wireless communication, and computationally quick transforms are needed to eliminate signal noise.

The Project

Built a working prototype of a real-time Bluetooth connection from a computer running MATLAB to the onboard receiver
on the NeuroDot. Demonstrated wireless transmission of the full 8 channel data spectrum in intervals of 1 second at 250Hz, with no packet loss or significant delay. This addition could prove to be extremely useful as the NeuroDot can now send data as it records it, and will be processed on a receiving laptop simultaneously with no post collection processing needed.

Current Status

This project is complete.

Help Me Get There

Enabling Engineering

The Need

37 million people in the U.S. are blind or have a visual impairment. For these individuals, travel within a busy city can be dangerous. The urban infrastructure often fails to convey the information necessary for the visually impaired to travel safely. The goal is to make crossing the street safer.

The Project

The Help Get Me There application identifies a user’s location with RFID tags located at both ends of crosswalks communicating with an RFID reader and Bluetooth transmitter located on the user. The RFID reader located on the user’s guide dog forwards this information to the smartphone allowing the application to pull up information about the intersection. The application then gives audio prompts that explain how the intersection can be crossed safely. The app features a gesture-based user interface complete with audible user feedback, providing concise and immediate information to the user. A database of information about 16 intersections near Northeastern’s campus was created.

Current status

The project is complete! It won a second prize in the ECE Department’s design competition.