I am a post-doctoral research fellow at the BioRobotics Institute, Pisa, Italy. My research focuses on machine learning algorithms applied to the human movement recognition and analysis. I am interested in innovative strategies for postures and movements classification from inertial sensors data. Activity classification in my research is applied to the physical activity level assessment and to the improvement of the estimates of biomechanical quantities such as energy expenditure, walking speed and gait parameters.
From March to August 2012 I joined as a visiting scholar the mHealth group at the College of Computer and Information Science, Northeastern University, Boston MA, USA, where I worked on human activity classification from wrist accelerometer data.
- A Mannini, D Trojaniello, A Cereatti, AM Sabatini, A Machine Learning Framework for Gait Classification Using Inertial Sensors: Application to Elderly, Post-Stroke and Huntington’s Disease Patients, Sensors 16 (1), 134(2), 2016
- AM Sabatini, G Ligorio, A Mannini, Fourier-based integration of quasi-periodic gait accelerations for drift-free displacement estimation using inertial sensors, Biomedical Engineering Online 14,(106), 1-18, 2015
- A Sabatini, G Ligorio, A Mannini, V Genovese, L Pinna, Prior-to-and post-impact fall detection using inertial and barometric altimeter measurements, IEEE Transactions on Neural Systems and Rehabilitation Engineering 24(7), 2016
- A Mannini, AM Sabatini, SS Intille, Accelerometry-based recognition of the placement sites of a wearable sensor, Pervasive and Mobile Computing 21, 62–74, 2015
- A. M. Sabatini, G. Ligorio, A. Mannini, V. Genovese and L. Pinna, Prior-to and post-impact fall detection using inertial and barometric altimeter measurements, IEEE Trans. Neural Systems and Rehabilitation Engineering, in press, accepted in July 2015.
- A. Mannini, A. M. Sabatini and S. S. Intille, Accelerometry-based recognition of the placement site of a wearable sensor, Pervasive and Mobile Computing, vol. 21C, pp. 62-74, August 2015;.
- A. Mannini and A. M. Sabatini, Walking speed estimation using foot-mounted inertial sensors: comparing machine learning and strap-down integration methods, Medical Engineering and Physics vol. 36, no. 10, 1122-1130,2014.
- A. Mannini, V. Genovese and A. M. Sabatini, Online decoding if hidden Markov models for gait event detection using foot-mounted gyroscopes, IEEE Journal on Biomedical and Health Informatics, vol. 18, no. 4, pp. 1122-1130, 2014;
- A. Mannini, S.S. Intille, M. Rosenberger, A.M. Sabatini, and W. Haskell. Activity recognition using a single accelerometer placed at the wrist or ankle. Medicine & Science in Sports & Exercise, vol. 45, no. 11, pp. 2193-2203, 2013;
- A. Mannini, A.M. Sabatini. Single stride speed estimation using support vector regression. Gait & Posture, 37(Supplement 1), S25-S26 (2013)
- A. Mannini, A.M. Sabatini and S.S. Intille. Human gait detection from wrist-worn accelerometer data. Gait & Posture, 37(Supplement 1), S26-S27 (2013).
- A. Mannini, A. M. Sabatini, Gait phase detection and discrimination between walking–jogging activities using hidden Markov models applied to foot motion data from a gyroscope, Gait & posture, 36 (4), pp. 657-661, (2012).
- A. Mannini and A. M. Sabatini, Automatic gait phase segmentation method using a Hidden Markov Model, Gait & Posture, 35, pp. S17–S18, (2012);
- A. Mannini, A.M. Sabatini, A hidden Markov model-based technique for gait segmentation using a foot-mounted gyroscope, 33rd IEEE Annual International Engineering in Medicine and Biology Conference 2011: 4369-4373 (2011)
- A. Mannini, A.M. Sabatini, On-line classification of human activity and estimation of walk-run speed from acceleration data using support vector machines, 33rd IEEE Annual International Engineering in Medicine and Biology Conference 2011: 3302-3305 (2011)
- A. Mannini, A.M. Sabatini Accelerometry-based classification of human activities using Markov modeling Computational Intelligence And Neuroscience - 2011 : 1:10 (2011)
- A. Mannini and A. M. Sabatini, Healthcare and accelerometry: applications for activity monitoring, recognition and functional assessment, as part of a work entitled Healthcare Sensor Networks Challenges Toward Practical Implementation. Editors: D. Lai, R. Begg, M. Palaniswami, Taylor & Francis CRC Press, ISBN:978-1-439-82181-7, October 2011;
- A. Mannini and A. M. Sabatini, Classification of human physical activities from on-body accelerometers: a Markov modeling approach, Proceedings of the Internat. Conf. on Bio-inspired Systems and Signal Processing, INSTICC-SciTe Press, pp. 201–208, Rome (Italy), 26th–29th January 2011;
- A. Mannini and A. M. Sabatini, Automatic machine learning methods for analysis of signals from accelerometers: classification of human activity and walking-running speed estimation, Gait & Posture, Vol. 33, p. S24, 2011;
- S. Micera, A. M. Sabatini, V. Genovese, J. Carpaneto, L. Bacci, A. Mannini, V. Monaco, L. Odetti, W. Poppendieck, K. P. Hoffmann, Assessment technologies for the analysis of the efficacy of a Vestibular Neural Prosthesis, BMT 2010, Rostok (Germany), 4–8 Oct 2010;
- A. Mannini, A.M. Sabatini Machine Learning Methods for Classifying Human Physical Activity from On-Body Accelerometers Sensors - 10(2) : 1154:1175 (2010)
- A. Mannini and A. M. Sabatini, Computational methods for the automatic classification of postures and movements from acceleration data, Gait & Posture, Vol. 30, pp. S68–S69, 2009;
- F. Carpi, A. Mannini and D. De Rossi, Dynamic splint-like hand orthosis for finger rehabilitation, as part of a work entitled Biomedical applications of electroactive polymer actuators, Editors: F. Carpi and E. Smela, John Wiley & Sons LTD, Chichester (United Kingdom), ISBN:978-0-470-77305-5, April 2009;
- A. Mannini, A. Gaglianese, S. Perondi, G. Ciofani and A. Landi, A Model of Transcytosis Processes across the Blood Brain Barrier, Communications of SIWN, Vol. 3, pp. 88–94, July 2008;
- F. Carpi, A. Mannini, D. De Rossi, Elastomeric contractile actuators for hand rehabilitation splints, Proceedings of SPIE, Volume 6927(1), pp. 692–705, March 2008;
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