Rome: July 13th, 2025

Current tag list

From Biolab3

synergies imu ergonomics classification
emg sts disorders echography
com parkinson's medical vcg
work-related elevation electromyography angles
muscle cop stroke disease
prosthetics modular walking ai
control hrc wearable imaging

Comparative Approach to Performance Estimation of Pulsed Wave Doppler Equipment Based on Kiviat Diagram
G. Fiori, A. Scorza, M. Schmid, S. Conforto, S.A. Sciuto
Sensors

Using adaptive surface EMG envelope extraction for onset detection: a preliminary study on upper limb amputees
S. Ranaldi, A. Tigrini, A.H. Al-Timemy, F. Verdini, A. Mengarelli, M. Schmid, S. Fioretti, L. Burattini, S. Conforto
2024 IEEE International Symposium on Medical Measurements and Applications (MeMeA)

Optimization of a feedforward neural network’s architecture for an HVAC system problem
M. Palermo, F. Forconi, E. Belloni, M. Quercio, G. M. Lozito, F. R. Fulginei
International Conference on Electrical, Computer, Communications and Mechatronics Engineering, ICECCME 2023

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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