AGE-IT  Spoke 9

Funded by: PIANO NAZIONALE DI RIPRESA E RESILIENZA (PNRR) – MISSIONE 4 COMPONENTE 2, “Dalla ricerca all’impresa” INVESTIMENTO 1.3, Creazione di “Partenariati estesi alle università, ai centri di ricerca, alle aziende per il finanziamento di progetti di ricerca di base”

The project objectives are to identify neurophysiological and kinematic features of static and dynamic balance with & without a lower limb exoskeleton. In parallel, we will develop a set of psychometric measures to test embodiment and user’s acceptability. The multidisciplinary team, merging neurophysiological, rehabilitation, engineering & robotics, and neuropsychological expertise , will ensure the design of innovative technologies to boost motor performance and reduce loss of balance in the elderly and address the neglected issue of embodiment in wearable robotics.

REBALANCE

REinforcing BALANCE with a neurally-driven wearable assistive device (PRIN: PROGETTI DI RICERCA DI RILEVANTE INTERESSE NAZIONALE – Bando 2022 Prot. 2022YPK5YB)

The project aims to reduce falls and related healthcare and social costs in the elderly. To tackle this pressing problem, two top-end Italian universities will collaborate developing an innovative, low-cost, neurally-driven, wearable assistive device (WAD) to prevent loss of balance (LoB), a prodromal sign of an incipient fall, in ecological environments. In this project, the WAD will be deployed as a rehabilitative tool in conjunction with an active balance board, to reinforce balance control based on individual cerebral, muscular, and kinematic responses.The expected results will translate in advancement of scientific and technical knowledge and economic impact in terms of reduction of LoB and market access of the end products.

PROGAIT

Co-Funded by European Commission Horizon 2020 Programme H2020-MSCA-RISE-2017 Grant n.778043

Physiological and rehabilitation outcomes gains from automated interventions in stroke therapy
Local Investigator: Alessandra Del Felice
PI: Olive Lennon - University College Dublin

Developments in robotics allow people with profound neuromuscular deficits after stroke to walk with assistance (during the gait cycle) using an exoskeleton robot. Integrating a robotic device with individualised user electroencephalography (EEG /electrical activity in the motor areas in the brain) and EMG (muscle)feedback would allow more physiological and targeted gait parameters in response to effort, and confer neuroplastic training effects including neuromodulation of temporal and spatial features of gait.
Future integration of EEG/EMGsignals with robotic devices will allow patient initiated movement through thought and/or attempted effort, where currently parameters for devices are therapist set and usage is not functionally driven by the patient. Advancement in this regard is stalled primarily because of difficulty in 3D modelling of gait by EEG.
This collaborative consortium through secondments and return and built in knowledge sharing strategies will exchange knowledge and expertise across: Design, development and production of exoskeleton gait devices; neuro-rehabilitation; bioelectric EEG/EMG signal capture and interpretation; mathematical modelling and brain computer interface (BCI) platform development can advance the state of the art in gait rehabilitation after stroke rehabilitation. The proposal will allow development of 3D modelling of gait, for gait restoration and explore integration with robotics from multi-stakeholder perspectives. Aims:
1. Define current state of the art in EEG modelling of gait post stroke by systematic review and meta-synthesis;
2. Complete 3D modelling of gait as visualised gait, overground gait and robotic walking in healthy individuals and stroke survivors;
3. Develop and test a virtual reality BCI gait training device, including end-user feedback;
4. Explore integration of this prototype with robotic software platforms.
Website: www.progait.eu

SoftAct

Funded by: Ministry of Affari Esteri e della Cooperazione Internazionale NUMBER-PGR00807

Prevention of falls: a synergic soft exoskeleton with integrated muscle and brain biosignals to minimize gait instability in the elderly
PI: Alessandra Del Felice

Gait performance and posture can be affected by aging. Falls due to lack of stability is one of the most common causes of injury and disability in the elderly. Multiple causative factors concur; older people are usually not aware of these risks and they do not report them to physicians. As a consequence, prevention of falling is often overlooked and technological solutions are proposed to detect the fall itself. The aim of this 3-y project is to develop a novel neuromuscular controller for a soft lower-limb exoskeleton to detect the loss of stability during walking or standing and apply the proper torques to restore stability. The project is structured on two consecutive phases: an offline acquisition of kinematic, cerebral activity and muscular signal during over-ground gait and during postural adjustments induced by an instrumented balance platform, and an online implementation of the closed-loop controller for detecting and preventing falls. At the end of the project, we expect to deliver a robust and efficient system, that should increase the stability and the safety of elderlies, with possible commercial exploitation.
Poster presented at The Hamlyn Symposium on Medical Robotics 2019 (London, UK).

DISCO

Funded by: Crowdfunding UNIPD

DIsturbi psico-patologici, cognitivi e del SOnno in sopravvissuti COvid-19.
PI: Alessandra Del Felice

ITA: Il progetto vuole studiare la prevalenza degli effetti a lungo termine a carico del sistema nervoso centrale in un campione di soggetti negativizzati e dimessi a domicilio dopo infezione da COVID-19. I soggetti verranno monitorati clinicamente e strumentalmente: verrà quantificata l'attività cerebrale a riposo e durante il sonno, i sintomi affettivi (es. depressione) e le funzioni cognitive (es. attenzione/memoria/funzioni esecutive).

EN:The project aims at identifying long-term central nervous system (CNS) sequelae in people who recovered from COVID-19. We will follow-up with clinical, neuropsychological and neurophysiological investigation this cohort.

web.unipd.it/covid19/ricerca