Rome: July 23rd, 2019

Current tag list

From Biolab3

networks cognitive posture analysis
wavelet gait emg parameters
cells load sensors dual
task force harvesting
ergonomics neural inertial coactivation
smartphone laod dynamics limbs
nanogenerator muscle sensitivity synergies

A non-intrusive system for seated posture identification
D. Bibbo, F. Battisti, S. Conforto, M. Carli
IEEE 20th International Conference on e-Health Networking, Applications and Services (Healthcom)

Muscle synergies of the contralateral lower limb in trans-femoral amputees gait
C. De Marchis, S. Ranaldi, S. Conforto
XXII Congress of the International Society of Electrophysiology and Kinesiology (ISEK 2018)

Common and specific gait patterns in people with varying anatomical levels of lower limb amputation and different prosthetic components
T. Varrecchia, M. Serrao, M. Rinaldi, A. Ranavolo, S. Conforto, C. De Marchis, A. Simonetti, I. Poni, S. Castellano, A. Silvetti, A. Tatarelli, L. Fiori, C. Conte, F. Draicchio
Human Movement Science


Biomedical Engineering Laboratory

Phone Number +39 06 5733 7057
Fax +39 06 5733 7026
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 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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