000260469 001__ 260469
000260469 005__ 20190509131803.0
000260469 0247_ $$2doi$$a10.5075/epfl-thesis-9013
000260469 037__ $$aTHESIS
000260469 041__ $$aeng
000260469 088__ $$a9013
000260469 245__ $$aNeuroprosthetics to support impaired hand functions: A multidisciplinary approach combining brain-machine interfaces and wearable exoskeletons
000260469 260__ $$aLausanne$$bEPFL$$c2018
000260469 269__ $$a2018
000260469 300__ $$a115
000260469 336__ $$aTheses
000260469 502__ $$aProf. Hannes Bleuler (président) ; Prof. José del Rocio Millán-Ruiz (directeur de thèse) ; Prof. Jamie Paik, Prof. Jose Pons, Prof. Gernot Müller-Putz (rapporteurs)
000260469 520__ $$aNeuroprosthetics, the discipline that aims at interfacing neural systems to artificially engineered devices, has witnessed in recent years important advancements towards the ultimate goal of augmenting and restoring human functions through technology and artificial systems.

Research in this field covers a wide range of efforts, from advancing our basic understanding of the neural processes involved into human sensory, motor and cognitive functions, to developing artificial intelligence algorithms for their decoding, to the physical interfacing between artificial devices and the human nervous system and biomechanics. Ultimately, this discipline aims at fusing these systems in order to restore, replace and rehabilitate lost and impaired functions due to motor disabling conditions or traumatic accidents.

In this thesis, I present a multidisciplinary approach that aimed at developing a neuroprosthesis for the assistance and restoration of hand functions impaired by neurological disorders or traumatic accidents, such as cerebrovascular accidents and spinal cord injuries.
These efforts encompassed the conceptualization and development of a robotic hand exoskeleton and brain-machine interface (BMI) algorithms for its control. Specifically, this thesis focused on the design, development and testing of (i) a novel mechatronic hand exoskeleton to assist hand motions within domestic and clinical settings, (ii) non-invasive BMI approaches based on electroencephalography (EEG) to decode neural correlates of intended hand movements, and on (iii) the closed-loop integration of the proposed exoskeleton and BMI for the sake of providing continuous feedback about ongoing neural modulations through hand motions and to trigger sensorimotor rehabilitation within clinical scenarios.

Results showed that the proposed mechatronic system can successfully control hand opening and closing within a fully wearable, portable and lightweight package. The system was tested with users who suffered from motor disabling impairments, showing that it could help them in performing several activities of daily living for the first time since their accidents.
From a brain-machine interfacing perspective, this work shows how imagined hand movements can be decoded, through EEG, in parallel with exoskeleton-induced motions, with important implications for the development of more embodied human-machine interaction protocols. Finally, this work shows how the closed-loop control of exoskeleton motions by means of the decoded ongoing neural activity enhances the discriminability of sensorimotor neural patterns and improves the performance of the brain-machine control channel.

Overall, the results presented here represent important advancements within the field of neuroprosthetics, with interesting implications for the development of assistive exoskeletal technologies and non-invasive brain-machine interfaces aimed at controlling such systems in clinical or domestic settings, for both assistive and neurorehabilitative purposes.
000260469 592__ $$b2018
000260469 6531_ $$aNeuroprosthetics
000260469 6531_ $$aexoskeletons
000260469 6531_ $$arehabilitation robotics
000260469 6531_ $$awearable robots
000260469 6531_ $$abrain-machine interface
000260469 6531_ $$aelectroencephalography
000260469 700__ $$0248113$$aRandazzo, Luca$$g241069
000260469 720_2 $$aMillán-Ruiz, José del Rocio$$edir.$$g149175
000260469 8564_ $$s10286882$$uhttps://infoscience.epfl.ch/record/260469/files/EPFL_TH9013.pdf
000260469 909C0 $$pCNBI
000260469 909CO $$ooai:infoscience.epfl.ch:260469$$pthesis$$pSTI$$pthesis-public$$pDOI$$qGLOBAL_SET
000260469 918__ $$aSTI$$cIBI-STI$$dEDRS
000260469 919__ $$aCNBI
000260469 920__ $$a2018-11-16$$b2018
000260469 970__ $$a9013/THESES
000260469 973__ $$aEPFL$$sPUBLISHED
000260469 980__ $$aTHESIS