Rome: November 15th, 2025

Current tag list

From Biolab3

imu onset detection hrc
medical muscle disorders ai
dynamics analysis prediction
echography fatigue fluid time-space
imaging ergonomics hd-emg communities
emg failure ultrasound work-related
electromyography renewable stroke vcg
task energy ml

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

The impact of human-robot collaboration levels on postural stability during working tasks performed while standing: experimental study
D. Bibbo, G. Corvini, M. Schmid, S. Ranaldi, S. Conforto
JMIR Human Factors

Mapping forearm muscle activity with a single linear HD-EMG grid and muscle synergy model during hand-wrist movements
F. Forconi, I. De Meis, A. De Nobile, M. Schmid, S. Conforto, and S. Ranaldi
47th Annual International Conference of IEEE Engineering in Medicine and Biology Society (EMBS 2025)

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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