CITRIS Big Ideas Winners for 2014

CITRIS held its poster and judging session on April 21st, 2014 for the annual Big Ideas competition, with eight innovative projects competing for $22.5K in prizes. Congratulations to this year’s winners!

  • 1st place: Glucose Enose
  • Co-2nd place: Remote Cleft
  • Co-2nd place: Dropsense
  • 3rd place: Sahay
  • Hon. Mention: SignUp
  • Hon. Mention: Aeolus

The contest concludes with two public events, the Grand Prize Pitch Day on May 5th and the Big Ideas Awards Celebration and Poster Session on May 8th.  For more information on these events, or any questions about the contest, please contact

(1st place) Glucose ENOSE

Team Members: Patrick Lyon, Benson Fan, Yayun Chen, Ray Chiu, UC Berkeley

In 2011, the CDC reported diabetes afflicted 25.8 million people in the United States. This disease can be controlled by strict blood serum glucose level monitoring, but the gold standard fingerstick test is painful and must be done multiple times every day. The team is developing a colorimetric sensor that could provide an inexpensive, non-invasive test for determining the level of glucose in the patient’s blood, providing a painless alternative to the fingerstick testing method. By developing a novel phage matrix material and smartphone sensor analyzer, the team hopes to create a non-invasive point-of-care sensor that can identify the concentration of these compounds on the patient’s breath and accurately report the patient’s blood glucose levels.

(co-2nd place) Dropsense

Team Members: Jeremy Fiance, Steve Yadlowsky, Vikram Iyer, UC Berkeley

Dropsense is developing a convenient, affordable hypoglycemia alert system to help diabetics better monitor their glucose levels. The technology comprises a sensor patch, mobile application, and machine learning analytics platform. The non-invasive Dropsense sensor sends data wirelessly to a smartphone, where a mobile app continuously processes the data with the machine learning algorithm to accurately identify hypoglycemic events. The app alerts users with an alarm or emergency phone call upon detecting low glucose levels so it can be treated before it becomes dangerous.

(co-2nd place) Remote Cleft Therapy for Young Children through a Mobile Game

Team Members: Zak Rubin, UC Santa Cruz

Speech therapy is not fun for children. It consists of frequent doctor visits and boring repetitive homework. Outside of the office, the therapist has no idea if the child performs the exercises correctly or at all. Modern speech recognition is capable of accurately detecting speech impediments, and the speed of current mobile devices makes it possible to use this in a game that reacts and responds to speech in real time. A tool like this on a mobile device will motivate children to practice their therapy exercises while also providing critical feedback and information to the therapist about how the child progresses outside of the office. This tool enables speech therapists to continue aiding children remotely, providing better care and enabling organizations to make an even bigger impact in a child’s life.

(3rd place) Sahay

Team Members: Priya Iyer, Seema Puthyapurayil, Eric Zan, Timothy Meyers, Ajeeta Dhole, UC Berkeley

Sahay is an Information and Communication Technology (ICT) platform connecting workers in the household informal sector (e.g. domestic help, cooks, drivers, security guards, etc.) in India with employment opportunities. Using the web page, Short Message Service (SMS) system, or Interactive Voice Response (IVR) interface, rural and migrant workers can search for jobs posted on Sahay’s platform by urban households. The solution will allow workers to search for jobs beyond their geographically restricted network. The platform will support technically literate job posters through a web interface, and will support workers in the informal sector through a mobile interface and IVR system.

(Honorable mention) Aeolus: Detecting Narcotics-Induced Respiratory Depression

Team Members: Vinayak Viswanadham, Brian Dick, Yumi Suh, Adrian Tabula, UC Berkeley

In order to sleep comfortably while recovering from surgery, hospital patients are often given narcotics for pain relief. However, this can cause respiratory depression, where the patients’ ability to breathe is hindered. This can lead to apnea (blockage of airways), respiratory and cardiac arrest, and death. Current approaches to early detection of NIRD chiefly involve detecting the blood saturation of oxygen and carbon dioxide. These strategies, however, provide imprecise information on patient respiration and often run into logistical difficulties. This project uses a detection system that employs visual, infrared, and ultrasonic surveillance of patient breathing, bodily changes, and positioning within the room. Software will also be built to integrate multiple sensory channels to construct a holistic portrait of patient respiratory status and NIRD risk levels over an extended period of time. This solution will hopefully changehow medical staff intervene in cases of NIRD and also shift the paradigm of monitoring unpredictable and lethal postoperative situations.

(Honorable mention) Sign UP

Team Members: Thibault Duchemin, Achal Pandey, Pieter Doevendans, Justin Harnoss, UC Berkeley

Today, a deaf person cannot reliably connect with 99% of the people around him or her. The few interactions between deaf and hearing people are usually limited by the difficulty for the deaf person to understand the hearing person and to talk in an intelligible way. Sign UP wants to break this barrier of communication that stands between deaf people and the rest of the world. Sign language is the natural way of communication for most deaf people and a fundamental part of their culture. The solution is two smart gloves that will translate Sign Language in real time and enable deaf people to interact freely and seamlessly with the rest of the world. The S-Gloves will also provide speech-to-text support to facilitate a proper conversation.

More information about our poster contest can be found here: