The freezing of gait (FOG) is a common and highly distressing motor symptom of patients with Parkinson’s Disease (PD). Effective management of FOG is difficult given its episodic nature, heterogeneous manifestation and limited responsiveness to drug treatment. Clinicians found alternative approaches, such as rhythmic cueing. We built a smartphone-based architecture in agreement with acceptability and usability requirements which is able to gather data and information useful to detect FOG. In this work fusing together the information of freeze index, energy, cadency variation and the ratio of the derivative of the energy a novel Fuzzy Logic based algorithm is developed. Performances of the Fuzzy algorithm are compared with two other algorithms showing its capability to reduce false negative detection thus improving sensitivity and specificity

Smartphone Based Fuzzy Logic Freezing of Gait Detection in Parkinson’s Disease / Pepa, Lucia; Ciabattoni, Lucio; Verdini, Federica; Capecci, Marianna; Ceravolo, MARIA GABRIELLA. - STAMPA. - (2014). (Intervento presentato al convegno IEEE/ASME 10th International Conference tenutosi a Senigallia (AN) nel settembre 2014) [10.1109/MESA.2014.6935630].

Smartphone Based Fuzzy Logic Freezing of Gait Detection in Parkinson’s Disease

PEPA, LUCIA;CIABATTONI, LUCIO;VERDINI, Federica;CAPECCI, Marianna;CERAVOLO, MARIA GABRIELLA
2014-01-01

Abstract

The freezing of gait (FOG) is a common and highly distressing motor symptom of patients with Parkinson’s Disease (PD). Effective management of FOG is difficult given its episodic nature, heterogeneous manifestation and limited responsiveness to drug treatment. Clinicians found alternative approaches, such as rhythmic cueing. We built a smartphone-based architecture in agreement with acceptability and usability requirements which is able to gather data and information useful to detect FOG. In this work fusing together the information of freeze index, energy, cadency variation and the ratio of the derivative of the energy a novel Fuzzy Logic based algorithm is developed. Performances of the Fuzzy algorithm are compared with two other algorithms showing its capability to reduce false negative detection thus improving sensitivity and specificity
2014
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11566/214516
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