Rome: July 5th, 2020

Current tag list

From Biolab3

coactivation parameters processing parameter
signal signals index phone
medical analysis functional
kinematics muscle sensors mobile
machine myoelectric deep eeg
gait stimulation stroke electrical
imaging fem synergies pedals
cycling accelerometer learning engagement
inertial ergonomics social dmd
emg reality virtual ann
neurorehabilitation

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

Modular motor control of the sound limb in gait of people with trans-femoral amputation
C. De Marchis, S. Ranaldi, M. Serrao, A. Ranavolo, F. Draicchio, F. Lacquaniti, S. Conforto
Journal of Neuroengineering and Rehabilitation

Optimizing the Scale of a Wavelet-Based Method for the Detection of Gait Events from a Waist-Mounted Accelerometer under Different Walking Speeds
C. Caramia, C. De Marchis, M. Schmid
Sensors

BioLab3

Biomedical Engineering Laboratory

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