For Doctors Interested in Using BrightLight

You can create an account by using the Sign Up button above and provide your unique access code to your patients.

For Patients Interested in Using BrightLight

Download the app by clicking here and create an account!

You do not need to have an access code when signing up, you can add that later in your settings.

Mission Statement

At BrightLight, our mission is to revolutionize mental health care by leveraging the power of machine learning to create more efficient and personalized therapy sessions. Through innovative technology, we empower patients to express their emotions through journal entries , which are analyzed by our advanced machine learning model to detect emotional "hotspots."

These insights help psychiatrists better understand and address patients' needs, enabling more tailored and effective appointments. BrightLight aims to bridge the gap between emotional expression and professional care, fostering a more connected and responsive mental health experience.

Visit our GitHub Repo

Frequently Asked Questions

Why BrightLight?

BrightLight is an innovative tool in the mental health field which will allow appointments to be more streamlined through the use of machine learning.

What can BrightLight be used for?

BrightLight can be used by patients to write journal entries which will be analyzed by our machine learning model to find "hotspot" emotions. These hotspots will be highlighted on the psychiatrists' side and enable them to tailor appointments accordingly.

How does the AI functionality work?

BrightLight's machine learning model detects words with certain emotional connotations within journal entries and highlights them for the psychiatrist to take note of for future appointments.

Video Demo of BrightLight

Watch this video to learn more about how BrightLight can be used to revolutionalize mental health appointments for both patients and doctors.

Doctor Features

Patient Features

Dashboard Screen

This is the first screen you will see after creating your account as a doctor. You will be able to view all of your patients and their general account information. Clicking on a patient will take you to their entries.

View Patient's Entries Screen

You can view a selected patient's entries which are sorted in reverse chronological order. Clicking on a journal entry will let you to view the AI analysis of the entry.

View AI Analysis Screen

You can get a bar graph of the emotions noted in a selected journal entry and if you click on an emotion in the bar graph, you will get an array of sentences that were noted to match the emotion selected.

Settings Screen

You can view your account information in the Settings screen and change your password and email, and remove a patient's access code through the Manage Patients section.

Home Screen

This is the first screen you will see after creating your account as a patient. You will be able to view your doctor and well as access the three most recent entries you made. Pressing on any of these entries will take you to the View Entry Screen so that you can edit or delete the selected entry.

View Journal Screen

You can view all of the journal entries you made and access the View Entry screen to edit or delete your entry by pressing it.

Create Journal Screen

You can create a new journal entry and submit it to be scored by our AI model, or come back to it later so long as you are still logged in to your account.

View Entry Screen

You can edit and delete any entries you make here by pressing an entry from the Home screen or View Journal screen.

Settings Screen

You can view your account information in the Settings screen and change your password, email, and access code if you switch to a new doctor. You can also delete your account if you decide to no longer use BrightLight.

About the Developers

Marshall Kuriakose

Marshall implemented the frontend for the website and mobile app as well as helped to implement the backend functionality with the frontend.

Chris Taks

Chris worked on the backend and deployment for website/mobile app, database management, and HTTPS server communication.

Justin Siegfried

Justin worked on authentication, aided in backend development, and completed unit testing.

Jordan duBarry

Jordan worked on the machine learning components and behavioral testing.

Nolan Jones

Nolan developed Python-based microservices for the machine learning components and worked on general backend architecture for the project.