Rome: July 19th, 2024

Current tag list

From Biolab3

duchenne elevation prosthetics ergonomics
parameters fatigue robots blood
emg echography hrc muscular
ultrasound gait angles ptt
muscle dynamics skeletal
doppler cop dystrophy walking

Machine learning to detect, stage and classify diseases and their symptoms based on inertial sensor data: a mapping review
D. Bibbo, C. De Marchis, M. Schmid, S. Ranaldi
Physiological Measurement

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

Novel quality assessment protocol based on Kiviat diagram for pulsed wave Doppler diagnostic systems: first results
G. Fiori, G. Bocchetta, M. Schmid, S. Conforto, S.A. Sciuto, A. Scorza
26th IMEKO TC4 International Symposium and 24th International Workshop on ADC/DAC Modelling and Testing


Biomedical Engineering Laboratory

Phone Number +39 06 5733 7057
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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Nuova Laurea Interclasse in Ingegneria Biomedica

Theses @ BioLab3