| Grant number: | 19/06551-5 |
| Support Opportunities: | Scholarships abroad - Research Internship - Doctorate |
| Start date: | September 01, 2019 |
| End date: | August 31, 2020 |
| Field of knowledge: | Physical Sciences and Mathematics - Computer Science - Computer Systems |
| Principal Investigator: | Alexandre Cláudio Botazzo Delbem |
| Grantee: | Caio Benatti Moretti |
| Supervisor: | Hermano Igo Krebs |
| Host Institution: | Instituto de Ciências Matemáticas e de Computação (ICMC). Universidade de São Paulo (USP). São Carlos , SP, Brazil |
| Institution abroad: | Massachusetts Institute of Technology (MIT), United States |
| Associated to the scholarship: | 18/26493-7 - Progress assessment of stroke patients in robotic rehabilitation treatments, BP.DR |
Abstract Coupled with sensors, robotic devices for Stroke rehabilitation describe the motor behavior of patients as kinematic and dynamic data, which are underexplored in the machine learning context, due to the time-consuming task of pursuing enough data volume. Moreover, the establishment of means for a quantitative assessment of patient progress, as well as whether data volume is large enough for solid learning guarantees remain unclear. Pondered by premises from Statistical Learning Theory, this research project proposes the definition of machine-learning-based biomarkers for assessing the patient progress during the treatment. The pathology severity, interpreted as the uncertainty in binary classification between left and right hemiparesis are to be exploited towards grounds for the assumption that pathological features, in data, attenuate over time, as an evidence of patient recovery. | |
| News published in Agência FAPESP Newsletter about the scholarship: | |
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