Titulo Estágio
SMITH II - Smart MonITor Health system II
Áreas de especialidade
Sistemas Inteligentes
Sistemas Inteligentes
Local do Estágio
LARN - Laboratorio de Redes Neuronais
Enquadramento
Health Monitoring Systems have been evolving significantly over the last years, having the potential to change the way we perceive our health and, consequently, improving the actions towards a better life.
One proof of the development of such systems is the recent “boom” of wearables in the consumer market and the investment that some of the biggest companies in the world are making towards this area such as Apple, Google, Samsung or Nike. Looking into these systems one can easily see three main areas:
- Gathering: how the data is collected and stored (the “hands”)
- Analysis: how the data is analyzed and characterized (the “brains”)
- Reporting: how the data is shown to the user (the “eyes”)
We believe that the key to a major technological breakthrough resides in how the data is analyzed, classified and used towards each person, although there is a lot to be done in data gathering, through wearables, and data reporting, such as mobile apps.
Objetivo
Diabetes is a huge health problem that is affecting more and more people over the time and, since there is still no cure for this disease, a person who has been diagnosed with diabetes has to control his blood sugar level between some thresholds. This is extremely important as non-controlled level of glucose can lead the subject to severe health complications and compromise his lifestyle. Tools that forecast the subject's glucose level within a prediction horizon may let the individual take preemptive actions to avoid crossing the normal thresholds.
The main goal of this research project is to develop a framework that, having a set of healthcare key indicators, is able to analyze the data, classify it according with a set of anomalies and predict personal patterns that, typically, precede the anomalies.
Plano de Trabalhos - Semestre 1
- State of the Art Review (September 2015)
- Dataset Gathering & Model Definition for Anomalies Characterization (October 2015)
- Evaluation of Classification and Machine-Learning Methodologies (November-December 2015)
- Intermediate MSc Report (January 2016)
Plano de Trabalhos - Semestre 2
- System & Algorithm Implementations (February - May 2016)
- Testing & Results Evaluation (March - May 2016)
- MSc Dissertation (May - June 2016)
Condições
Depending on the work conducted by the student, there is the opportunity for a one year paid internship in the company after Master’s conclusion. Additionally, the student has the possibility to incorporate in the company for a few weeks during the second semester.
Profile
Student should have:
- Attitude is first on the list!!
- Tons of energy
Student should be:
- Confident
- Ambitious
- Self-motivated
- Highly Adaptable
- Self-starter
- Quick Learner
Student should have interest (or academic experience) in at least one of the following:
- Pattern Recognition
- Artificial Intelligence
- Computer Vision
Observações
EyeSee is a technological startup, funded by Olisipo, focusing on intelligent systems. As of today, EyeSee developed a novel digital advertising solution with unique insertion and interaction features, owning 5 patents in USPTO. Additionally, EyeSee team is working on a smart energy management product and on a smart health monitoring system. Olisipo is an IT outsourcing company with more than 20 years of experience in the Portuguese market and with more than 500 employees in some of the main Portuguese companies. Recently, Olisipo decided to make a very strong bet on innovation and entrepreneurship, creating “Olisipo ADN - Ambiente de Desenvolvimento de Negócios”. Olisipo ADN counts with 6 startups, namely EyeSee, and currently funds ten innovation projects. This bet on innovative products and solutions focus on 4 areas: Better Life, Digital Advertising, Smart Energy and Machine-to-Machine. This is a brilliant opportunity to gain exposure to a dynamic, fun and outstanding technology company.
Orientador
André Ribeiro Pimentel (andre.pimentel@eyesee.pt) e Prof Bernardete Ribeiro (bribeiro@dei.uc.pt)
andre.pimentel@eyesee.pt 📩