Rome: June 17th, 2025

Current tag list

From Biolab3

quality dystrophy duchenne
ultrasound work-related imu imaging
muscular skeletal echography wearable
disorders null functionality robots
muscle ai disease parkinson's
ergonomics control hrc emg
cop medical

Transit time measurement method by complex cross-spectrum analysis applied to a variable PWV arterial simulator
F. Filippi, G. Fiori, S. Conforto, A. Scorza, S.A. Sciuto
2024 IEEE International Workshop on Metrology for Industry 4.0 & IoT

Automatic handwriting recognition with a minimal EMG electrodes setup: a preliminary investigation
A. Tigrini, S. Ranaldi, A. Mengarelli, F. Verdini, M. Scattolini, R. Mobarak, S. Fioretti, S. Conforto, L. Burattini
2024 IEEE International Symposium on Medical Measurements and Applications (MeMeA)

Image quality assurance for B-mode diagnostic ultrasound: Kiviat-based protocol first application
G. Fiori, M. Schmid, J. Galo, S. Conforto, S.A. Sciuto, A. Scorza
2024 IEEE International Workshop on Metrology for Industry 4.0 & IoT

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 @

BioLab³, 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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