Camila Acevedo Carrillo

MIT Department: Media Arts and Sciences
Faculty Mentor: Prof. Pattie Maes
Undergraduate Institution: University of Central Florida
Website: LinkedIn
Research Poster

Biography

I am a rising senior at the University of Central Florida, majoring in Computer Science. I am originally from sunny Guayama, Puerto Rico. I have had diverse research experiences in the following fields: micro-mobility, city science, photonics, natural language processing, and youth online safety. I am committed to learning how to use computer science, in combination with other fields, to improve the lives of underserved individuals and communities. When I am not focusing on academia, I like to split my time between volunteering for O.U.R. and for Every.Last.One. Overall, I am passionate about applying science, art, and technology to create a safer, more equitable, creative, prosperous, and sustainable world. My favorite things to do during my free time are learning about filmmaking and all things Old Hollywood-related, vegan baking, and dissecting reality television.

 

2021 Abstract

Brain Switch: Enhancing the Communication for People with ALS

Camila Acevedo Carrillo1, Guillaume Hessel2, Nataliya Kosmyna3,
and Pattie Maes3
1Department of Computer Science, University of Central Florida
2MIASHS Technology and Disability, University Paris 8
3Department of Media Arts and Sciences, Fluid Interfaces,
Massachusetts Institute of Technology

The Brain Switch system is an innovative brain computer interaction (BCI) tool which helps patients with Amyotrophic Lateral Sclerosis (ALS) and other motor function disabilities to communicate more effectively with their caretakers. However, there is a need for a system in which caretakers and family members of the patient can communicate with in case of any problems or doubts pertaining to the tool and its accompanying mobile application. The goal of this project is to develop and test an easily scalable and deployable chatbot to help improve communication between multiple caregivers, patients with ALS, and the Brain Switch research team and to share their experiences and difficulties with the Brain Switch system. The main priorities in selecting the correct stack for the chatbot implementation is to keep the patient’s information private, to make it easy and hassle free to install for the users, it should be able to send and receive diverse media files, and it should communicate in multiple languages. The resulting chatbot system—which was developed using Landbot Chatbot Builder—corresponds to all of the aforementioned requirements. Moreover, the system is connected to a secure, online database which stores the daily survey and customer support participation data submitted daily by caretakers and family members. The chatbot is also very simple and accessible to deploy for users via a URL link which can be accessed and filled via multiple devices.