Search Results - di Credico, A.
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DE-PASS Best Evidence statement (BESt): A systematic review and meta-analysis on the effectiveness of trials on device-measured physical activity and sedentary behaviour and their...
Bartoš, F., Brandes, M., Capranica, L., Carlin, A., Ciaccioni, S., Corvino, C., Cortis, C., di Credico, A., Drid, P., Gallè, F., Izzicupo, P., Jahre, H., Khudair, M., Kolovelonis, A., Kongsvold, A., Kouidi, E., Ling, F. C. M., MacDonncha, C., Maier, M., Marcuzzi, A., Mork, P. J., Ng, K., Palumbo, F., Peric, R., Rumbold, P. L. S., Sandu, P., Stavnsbo, M., Syrmpas, I., Tempest, G. D., Vilela, S., Woods, C., Wunsch, K.Published in Sports Medicine (2025)“…di Credico, A.…”
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Can data-driven supervised machine learning approaches applied to infrared thermal imaging data estimate muscular activity and fatigue?
Perpetuini, D., Formenti, D., Cardone, D., Trecroci, A., Rossi, A., Di Credico, A., Merati, G., Alberti, G., Di Baldassarre, A., Merla, A.Published in Sensors (2023)“…Di Credico, A.…”