Cereatti, Andrea
Politecnico di Torino
5 papers on CoChatORCID 0000-0002-7276-5382
Most cited papers
- Verified
A machine Learning Framework for Gait classification using inertial sensors: application to Elderly, Post-Stroke and Huntington’s Disease Patients
Mannini, A., Trojaniello, D., Cereatti, A., & Sabatini, A. (2016) · Sensors
Gait Recognition and AnalysisBalance, Gait, and Falls Prevention
Cited by 242
- Verified
ISB recommendations on the definition, estimation, and reporting of joint kinematics in human motion analysis applications using wearable inertial measurement technology
Cereatti, A., Gurchiek, R., Mündermann, A., Fantozzi, S., Horak, F., Delp, S., & Aminian, K. (2024) · Journal of Biomechanics
Context-Aware Activity Recognition SystemsLower Extremity Biomechanics and Pathologies
Cited by 79
- Verified
Mobility recorded by wearable devices and gold standards: the Mobilise-D procedure for data standardization
Palmerini, L., Reggi, L., Bonci, T., Del Din, S., Micó-Amigo, M. E., Salis, F., Bertuletti, S., Caruso, M., Cereatti, A., Gazit, E., et al. (2023) · Scientific Data
Context-Aware Activity Recognition SystemsPhysical Activity and Health
Cited by 52
- Verified
Self-supervised learning of wrist-worn daily living accelerometer data improves the automated detection of gait in older adults
Brand, Y. E., Kluge, F., Palmerini, L., Paraschiv-Ionescu, A., Becker, C., Cereatti, A., Maetzler, W., Sharrack, B., Vereijken, B., Yarnall, A. J., et al. (2024) · Scientific Reports
Context-Aware Activity Recognition SystemsBalance, Gait, and Falls Prevention
Cited by 19
- Verified
Automated Gait Detection in Older Adults during Daily-Living using Self-Supervised Learning of Wrist- Worn Accelerometer Data: Development and Validation of ElderNet
Brand, Y. E., Kluge, F., Palmerini, L., Paraschiv-Ionescu, A., Becker, C., Cereatti, A., Maetzler, W., Sharrack, B., Vereijken, B., Yarnall, A. J., et al. (2024) · Scientific Reports
Context-Aware Activity Recognition SystemsBalance, Gait, and Falls Prevention
Cited by 19
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