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Thesis Project Form

Title (tentative): Design and validation of a sensory restoration strategy based on intraneural stimulation

Thesis advisor(s): Chiappalone Michela, Silvestro Micera (silvestro.micera@santannapisa.it) E-mail:
Address: Via Opera Pia 13, 16145 Genova Phone:
Description

Motivation and application domain
In the field of neuroprosthetics for tactile feedback restoration, providing meaningful and intuitive sensory information remains a significant challenge. This thesis builds upon the results achieved by Prof. Silvestro Micera’s research group on neural implants in individuals with upper-limb amputation. The project aims to design and validate novel stimulation strategies to enhance the naturalness and effectiveness of sensory feedback.

General objectives and main activities
- Design and development of an intraneural stimulation strategy for sensory restoration in prosthetic hand users. Specifically, restoration of intuitive and natural tactile sensation through biomimetic modulation of stimulation parameters.
- Experimental validation of the strategy through micro-stimulation of the median and ulnar nerves of the wrist, at the N2Lab laboratory in Pisa.

Training Objectives (technical/analytical tools, experimental methodologies)
The student will develop expertise in the following technical and analytical areas:
- Embedded Systems & Software Development: Design and implementation of firmware for real-time applications and dedicated user interfaces for system control.
- Experimental Design: Definition and formalization of an experimental protocol for sensory feedback characterization.
- System Integration: Integration of the proposed stimulation patterns into microneurography experimental setups.
- Data Analysis & Validation: Quantitative and qualitative evaluation of user responses to neural stimulation to assess the performance of the developed strategies.

Place(s) where the thesis work will be carried out: “Institute of BioRobotics-SSSA”, Pontedera (PI)

Additional information

Pre-requisite abilities/skills: Data Analysis, Coding (Python, Matlab, C++), Rehabilitation Engineering fundamentals, Physiology & Biomechanics, Analysis of Biomedical Data and Signals, Machine Learning.

Maximum number of students: 1