Rome: June 4th, 2020

Current tag list

From Biolab3

functional synergies gait fem
pedals accelerometer analysis virtual
posture asymmetry imaging sensors
eeg medical cycling
load muscle index stroke
amputees ann parameters social
cognitive kinematics force mri
ergonomics reality electrical engagement
inertial stimulation neurorehabilitation

EMG-based Indicators of Muscular Co-Activation during Gait in Children with Duchenne Muscular Dystrophy
M. Rinaldi, M. Petrarca, A. Romano, G. Vasco, C. D'Anna, M. Schmid, E. Castelli, S. Conforto
41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

Prosocial virtual reality, empathy, and EEG measures: a pilot study aimed at monitoring emotional processes in intergroup helping behaviors
F. D'Errico, G. Leone, M. Schmid, C. D'Anna
Applied Sciences

Generalization of a wavelet-based algorithm to adaptively detect activation intervals in weak and noisy myoelectric signals
T. Varrecchia, C. D'Anna, M. Schmid, S. Conforto
Biomedical signal processing and control


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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