Rome: April 26th, 2024

Current tag list

From Biolab3

walking elevation parkinson's robots
null ai imu
ultrasound angles cop prosthetics
wearable energy work-related ergonomics
hrc echography ml renewable
disorders emg communities doppler
disease

Cyclin D3 deficiency promotes a slower, more oxidative skeletal muscle phenotype and ameliorates pathophysiology in the mdx mouse model of Duchenne muscular dystrophy
A. Bonato, G. Raparelli, S. Luvisetto, F. Forconi, M. Cosentino, F. Tirone, E. Rizzuto, M. Caruso
FASEB Journal

A Novel Equivalent Time Sampling-Based Method for Pulse Transit Time Estimation with Applications into the Cardiovascular Disease Diagnosis
G. Fiori, F. Fuiano, S. Conforto, S.A. Sciuto, A. Scorza
Sensors

High-density surface electromyography allows to identify risk conditions and people with and without low back pain during fatiguing frequency-dependent lifting activities
T. Varrecchia, A. Ranavolo, G. Chini, A.M. De Nunzio, F. Draicchio, E. Martinez-Valdes, D. Falla, S. Conforto
Journal of Electromyography and Kinesiology

BioLab3

Biomedical Engineering Laboratory

Phone Number +39 06 5733 7057
Website http://biolab.uniroma3.it
Founder Tommaso D'Alessio
Research group head Silvia Conforto
Lab coordinator Maurizio Schmid
to send an email please replace AT with @

BioLabĀ³, the Biomedical Engineering Laboratory at the Department of Industrial, Electronic and Mechanical Engineering, Roma Tre University, aims at developing and offering new approaches, methodological innovations, and technological solutions to be applied in the field of human movement science at large.

The field of application ranges from the functional evaluation and analysis of motor and physiological markers associated with neuromuscular disorders and conditions (e.g. Parkinson's disease, Stroke, Prosthesis use, Ageing), to the long-term monitoring and description of the quality of human movement and behaviour in unconstrained scenarios, to the development of technologies for human enhancement, rehabilitation, assistance and social inclusion at all age levels.

To this end, EMG, wearable inertial sensors, marker-based and marker-free kinematics, force sensors are used as data sources, and investigated, often in combination. Application fields include performance optimisation in sport activities, risk assessment in ergonomics, motor recovery monitoring in rehabilitation, evaluation of bio-feedback effects on motor control in neuromechanics.



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