Cristiano De Marchis

Dr. Cristiano De Marchis

orcid

Research Focus & Metrics

Academic Career Length

16Years (2011-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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28 March 2015 in Experimental Brain Research
Verified
Journal Article
Closed access
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CMCristiano De Marchis
Cristiano De Marchis
GSGiacomo Severini
Giacomo Severini
ACAnna Margherita Castronovo
Anna Margherita Castronovo
MSMaurizio Schmid
Maurizio Schmid
SCSilvia Conforto
Silvia Conforto

1 August 2019 in Human Movement Science
Verified
Journal Article
Closed access
TVTiwana VARRECCHIA
Tiwana VARRECCHIA
MSMariano Serrao
Mariano Serrao
MRMartina Rinaldi
Martina Rinaldi
ARAlberto Ranavolo
Alberto Ranavolo
SCSilvia Conforto
Silvia Conforto
FDFrancesco Draicchio
Francesco Draicchio

6 August 2024 in Sensors
Verified
Journal Article
Open access
PDF file
Antonino QuattrocchiAntonino Quattrocchi
Antonino Quattrocchi
Giada GarufiGiada Garufi
Giada Garufi
Giovanni GugliandoloGiovanni Gugliandolo
Giovanni Gugliandolo
CMCristiano De Marchis
Cristiano De Marchis
DCDomenicantonio Collufio
Domenicantonio Collufio
Nicola DonatoNicola Donato
Nicola Donato
This narrative review provides a comprehensive analysis of the several methods and technologies employed to measure handgrip strength (HGS), a significant indicator of neuromuscular strength and overall health. The document evaluates a range of devices, from traditional dynamometers to innovative sensor-based systems, and assesses their effectiveness and application in different demographic groups. Special attention is given to the methodological aspects of HGS estimation, including the influence of device design and measurement protocols. Endogenous factors such as hand dominance and size, body mass, age and gender, as well as exogenous factors including circadian influences and psychological factors, are examined. The review identifies significant variations in the implementation of HGS measurements and interpretation of the resultant data, emphasizing the need for careful consideration of these factors when using HGS as a diagnostic or research tool. It highlights the necessity of standardizing measurement protocols to establish universal guidelines that enhance the comparability and consistency of HGS assessments across various settings and populations.

1 December 2013 in Human Movement Science
Verified
Journal Article
Closed access
CMCristiano De Marchis
Cristiano De Marchis
MSMaurizio Schmid
Maurizio Schmid
DBDaniele Bibbo
Daniele Bibbo
IBIvan Bernabucci
Ivan Bernabucci
SCSilvia Conforto
Silvia Conforto

1 June 2016 in Annals of Biomedical Engineering
Verified
Journal Article
Open access
PDF file
EAEmilia Ambrosini
Emilia Ambrosini
CMCristiano De Marchis
Cristiano De Marchis
APAlessandra Pedrocchi
Alessandra Pedrocchi
Giancarlo FerrignoGiancarlo Ferrigno
Giancarlo Ferrigno
MMMarco Monticone
Marco Monticone
SFSimona Ferrante
Simona Ferrante
Cycling training is strongly applied in post-stroke rehabilitation, but how its modular control is altered soon after stroke has been not analyzed yet. EMG signals from 9 leg muscles and pedal forces were measured bilaterally during recumbent pedaling in 16 post-acute stroke patients and 12 age-matched healthy controls. Patients were asked to walk over a GaitRite mat and standard gait parameters were computed. Four muscle synergies were extracted through nonnegative matrix factorization in healthy subjects and patients unaffected legs. Two to four synergies were identified in the affected sides and the number of synergies significantly correlated with the Motricity Index (Spearman’s coefficient = 0.521). The reduced coordination complexity resulted in a reduced biomechanical performance, with the two-module sub-group showing the lowest work production and mechanical effectiveness in the affected side. These patients also exhibited locomotor impairments (reduced gait speed, asymmetrical stance time, prolonged double support time). Significant correlations were found between cycling-based metrics and gait parameters, suggesting that neuro-mechanical quantities of pedaling can inform on walking dysfunctions. Our findings support the use of pedaling as a rehabilitation method and an assessment tool after stroke, mainly in the early phase, when patients can be unable to perform a safe and active gait training.

1 July 2018 in International Journal of Industrial Ergonomics
Verified
Journal Article
Closed access
TVTiwana VARRECCHIA
Tiwana VARRECCHIA
CMCristiano De Marchis
Cristiano De Marchis
MRMartina Rinaldi
Martina Rinaldi
FDFrancesco Draicchio
Francesco Draicchio
MSMariano Serrao
Mariano Serrao
ARAlberto Ranavolo
Alberto Ranavolo