Alessandra Pedrocchi,
Full professor
Biomedical Engineer
Research Areas:
Rehabilitation Robotics, Digital Health, Computational Neuroscience
Location
Polimi Campus Colombo
3rd Floor, building 32.2
Via Colombo 40, 20133, Milan, Italy
Polimi Campus Leonardo
4th Floor, building 21
Piazza Leonardo da Vinci 32, 20133, Milan, Italy
Phone
+39 02 2399 3363
Alessandra Pedrocchi received her degree in electronic engineering and her doctorate in bioengineering at the Politecnico di Milano in 1997 and 2001. She is currently an associate professor at the Department of Electronics, Computer Science, and Bioengineering of the Politecnico di Milano, where she teaches Neuroengineering and Biomedical Instrumentation in the course of studies in Biomedical Engineering. She is one of the founders of the Nearlab laboratory, the NeuroEngineering And Medical Robotics lab, established in 2008 at POLIMI. Since then, she has been in charge of the Neuroengineering section. Since 2019 she has been in charge of the interdepartmental laboratory “WE-COBOT LAB Wearable and collaborative robotics Laboratory”.
She is director of the first and second-level university master on “RehabTech: Technologies for innovation in Rehabilitation Medicine and for assistance – From technological innovation to clinical translation, research and healthcare management” (www.rehabtech.polimi.it ).
She has been a senior member of the IEEE since 2018 and is Associate Editor of IEEE Transaction of Neural System and Rehabilitation and Frontiers in Neuroscience.
Interests & Projects
Alessandra’s research interest is neuroengineering, including biomechanics in motor control, neurorobotics, new technologies for neurorehabilitation, with particular emphasis on the control systems and Human-robot interfaces of upper and lower limb exoskeletons for rehabilitation and assistive devices, neuroprostheses, and the study of the correlation between brain plasticity and functional recovery. She has coordinated various research projects funded by national private foundations (Fnd. Cariplo and Fnd. Telethon), European projects (Horizon 2020 -RETRAINER, H2020- FET Flagship Human Brain Project, FP7-REALNET), national funding (PRIN), regional projects (GenePark, Ability, Empatia, AGREE) and NIH funding and joint projects with INAIL (FESleg).
Courses held
Bachelor of Science courses
086030 – BIOELETTROMAGNETISM AND BIOMEDICAL INSTRUMENTATION [I.C.]
Models and methods for the analysis of membrane potentials. Hodgkin-Huxley Model (H-H). Impulse propagation and conduction in fibres. Neuron models and networks. Extra-cellular potentials. Introduction to forward and inverse problem. Lead vector. Methods for the evaluation of electric and magnetic fields from/in biological tissues at low and high frequency. Electrical stimulation of biological system. Magnetic stimulation of the nervous system. Study of the biological effects of electromagnetic fields and dosimetry. Clinical meaning, characteristics and dimensionality of biomedical signals. Biomedical instrumentation: definition, characteristics and classification. Biological-technological interfaces and related problems: reliability, safety, signal to noise ratio, interferences. Transduction and signal conditioning : amplification, filtering and A/D conversion. Biomedical sensors: classification and principles of transduction. Force and displacement sensors, pressure and flow transduction. Piezoelectric devices and ultrasounds. Temperature sensors and radiation thermometry. Optical measurements and related instrumentation.
Master of Science courses
052372 – NEUROENGINEERING
For each of the four topics of the Neuroengineering [2] the students are expected to achieve:
– Knowledge and understanding with a crossdisciplinary approach the major assumption for the design, the definition of user requirements, the translation of requirements to technical specifications, the process of proper validation metrics.
– Implement simple projects tailored to specific research or clinical scenarios, starting from a proper understanding of current state of the art (scientific literature).
– Making judgement on the assumptions, their validations, the achieved accuracy, their complexity and their feasibility in different scenarios of applications.
– Being able to effectively work in group, and communicate by public speaking
Publications