In this paper, a Machine-Learning Based Emotion Recognition System in patients with Parkinson's disease is presented. The development of this system is composed of three steps. Firstly, each user is required to execute an experimental protocol while a simple device (i.e., smartwatch), worn on the wrist, collects data. During the experimental protocol, a nine-point clinical scale and a commercial emotion recognition software have been used to identify emotions. Secondly, from smartwatch data, features extraction is implemented. Lastly, a Machine Learning Algorithm (MLA) is trained with extracted features as input and emotion classes as output.
A machine-learning based emotion recognition system in patients with Parkinson's disease / Capecci, M.; Ciabattoni, L.; Foresi, G.; Monteriu, A.; Pepa, L.. - ELETTRONICO. - 2019-:(2019), pp. 20-21. (Intervento presentato al convegno 9th IEEE International Conference on Consumer Electronics, ICCE-Berlin 2019 tenutosi a deu nel 2019) [10.1109/ICCE-Berlin47944.2019.8966224].
A machine-learning based emotion recognition system in patients with Parkinson's disease
Capecci M.;Ciabattoni L.;Foresi G.;Monteriu A.;Pepa L.
2019-01-01
Abstract
In this paper, a Machine-Learning Based Emotion Recognition System in patients with Parkinson's disease is presented. The development of this system is composed of three steps. Firstly, each user is required to execute an experimental protocol while a simple device (i.e., smartwatch), worn on the wrist, collects data. During the experimental protocol, a nine-point clinical scale and a commercial emotion recognition software have been used to identify emotions. Secondly, from smartwatch data, features extraction is implemented. Lastly, a Machine Learning Algorithm (MLA) is trained with extracted features as input and emotion classes as output.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
