Tesi etd-03212023-094216
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Tipo di tesi
Dottorato
Autore
LOSANNO, ELENA
URN
etd-03212023-094216
Titolo
Hand neuroprostheses based on intrafascicular stimulation: preclinical validation and tools to promote clinical translation
Settore scientifico disciplinare
ING-INF/06
Corso di studi
Istituto di Biorobotica - PHD IN BIOROBOTICA
Commissione
relatore Prof. MICERA, SILVESTRO
Parole chiave
- hand movement restoration
- hand paralysis
- intracortical control
- intrafascicular stimulation
- neuroprostheses
- stimulation protocol optimization
- virtual reality
Data inizio appello
25/07/2023;
Disponibilità
parziale
Riassunto analitico
Recovery of hand functions is of primary importance for people living with paralysis after neurological diseases such as stroke and spinal cord injury. Neuroprostheses represent a radical solution to bypass the lesion and artificially restore hand control. Current stimulation techniques for hand neuroprostheses suffer from different drawbacks. On the one hand, stimulation via transcutaneous or spinal interfaces offers low selectivity for hand muscles and thus low dexterity. On the other hand, devices based on implanted muscle stimulation have limited deployment because they require multiple implants distributed along the body. Intrafascicular stimulation of the arm's peripheral nerve is an alternative that offers advantages over these techniques because it potentially allows high dexterity with less invasiveness. In this thesis, I preclinically validated this hypothesis by showing that intrafascicular stimulation via thin-film electrodes can evoke a variety of hand functions in the monkey animal model with few implants. Next, I developed tools to improve the usability and reliability of hand neuroprostheses based on intrafascicular stimulation which are useful to promote clinical translation. I implemented and validated an algorithmic framework to efficiently tune the parameters of intrafascicular stimulation to optimally elicit motor functions, which will be helpful for the fast and reliable configuration of clinical hand neuroprostheses. Furthermore, I preclinically verified the intuitiveness and stability of an intracortical decoding strategy based on neural ensemble dynamics and demonstrated the feasibility of using it to control intrafascicular stimuli. This pilot experiment provides an important basis for the design of intuitive and robust intracortical control schemes for hand neuroprostheses. Finally, I developed and pilot-tested a virtual reality environment that simulates the use of a hand neuroprosthesis and allows to personalize the body control strategy for each patient, potentially favoring ease of use and acceptance. This thesis provides evidence for the efficacy of intrafascicular stimulation in restoring hand functions and paves the way for the development of clinical devices based on this technique. These developments have important implications for improving the independence and quality of life of individuals with hand paralysis.
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