Angelo Maria Sabatini

Curriculum
ANGELO MARIA SABATINI

DOB: 29 september 1960
Current position: Associate Professor in Biomedical Engineering (ING-INF/06)
Current affiliation: The BioRobotics Institute, Scuola Superiore Sant'Anna (SSSA), Viale Rinaldo Piaggio, 34, 56025 Pontedera, Pisa, Italy

EDUCATION

1992: Ph.D. thesis: "Metodi e tecniche per la realizzazione di dispositivo sensoriali esterocettivi" (summa cum laude)
1989-1991: Ph.D. in Biomedical Robotics, SSSA
1986: M.Sc. thesis: "Studio di ricevitori coerenti per Modulazioni Offset-Binary" (summa cum laude)
1979-1986: M.Sc. in Electrical Engineering, Faculty of Engineering, University of Pisa

ACADEMIC POSITIONS

2011-present: Area leader, "Sensor Signals and Information Processing", The BioRobotics Institute, SSSA
2001-present: Associate Professor in Biomedical Engineering, SSSA
1991-2001: Assistant Professor in Biomedical Engineering, SSSA
1987-1989: Research fellow at Centro E. Piaggio, Faculty of Engineering, University of Pisa
1988: Visiting scientist (3 months) in the project "Nerve regeneration through electrical stimulation", Lab Artificial Organs, Division of Medicine and Biology, Brown University, Providence, RI, U.S.A.

SCIENTIFIC MEMBERSHIP

2006-present: elected Senior Member IEEE
2004-present: member, IMEKO Technical Committee 18, Measurements of Human Functions

TEACHING

Courses at SSSA
2017-present: "Introduction to statistics and data analysis using MATLAB", Ph.D. school in Biorobotics
Courses at the University of Pisa (Faculty of Engineering)
M.Sc. in Bionics Engineering
2014-present: "Instrumentation and measurement for bionic systems"

RESEARCH TOPICS

Computational methods to process sensor data for applications in several technical fields, including:
Navigation systems for mobile robots, wheelchairs and smart walking support systems:
(a) obstacle detection and avoidance (ultrasonic/infrared range sensors);
(b) static and dynamic localization (ultrasonic/laser range sensors);
(c) guidance (force-based joysticks, short-range proximity sensors);
Human movement research - development of computational methods (in particular: sensor fusion and machine learning), which have also been applied to analyze and study pathologic conditions:
(a) postural balance (force plates);
(b) upper-arm/hand assessment (instrumented gloves, EMG, optical motion capture systems);
(c) gait assessment (magneto-inertial measurement units, optical motion capture systems);
(d) spontaneous movements in newborns (optical motion capture systems);
(e) fall detection (magneto-inertial measurement units, air pressure sensors);
(f) fall prevention (inertial measurement units);
(g) activity recognition (inertial measurement units)
(h) pedestrian navigation (magneto-inertial measurement units, GPS)