Rome: March 21st, 2019

Current tag list

From Biolab3

gait deep parameters dynamics
learning disease stability medical
emg synergies nanogenerator parkinson's
coactivation classification machine coordination
inertial load limbs muscle
sensors lower limb prosthetics
analysis force cells harvesting

Does cycling training augmented by functional electrical stimulation impact on muscle synergies in post-acute stroke patients?
E. Peri, E. Ambrosini, C. De Marchis, C. Nava, L. Longoni, A. Pedrocchi, G. Ferriero, S. Ferrante
International Conference on NeuroRehabilitation 2018

Human body energy harvesting solutions for wearable technologies
A. Proto, L. Peter, M. Cerny, M. Penhaker, D. Bibbo, S. Conforto, M. Schmid
IEEE 20th International Conference on e-Health Networking, Applications and Services (Healthcom)

Kinetic and kinematic patterns for prosthetic gait analysis
S. Conforto, M. Serrao, T. Varrecchia, M. Rinaldi
XXII Congress of the International Society of Electrophysiology and Kinesiology (ISEK 2018)


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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