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 have built a smartphone-based architecture in agreement with acceptability and usability requirements which is able to detect FOG and provide acoustic feedback to the patient. The aim of this work is to compare the reliability of a real-time FOG detection using two different algorithms implemented on the smartphone
Predicting Freezing of Gait in Parkinson’s Disease with a smartphone: comparison between two algorithms / Pepa, Lucia; Verdini, Federica; Capecci, Marianna; Maracci, F; Ceravolo, MARIA GABRIELLA; Leo, Tommaso. - STAMPA. - (2014). (Intervento presentato al convegno Conference: 5th Italian Forum on Ambient Assisted Living (ForItAAL) tenutosi a Catania nel settembre 2014).
Predicting Freezing of Gait in Parkinson’s Disease with a smartphone: comparison between two algorithms
PEPA, LUCIA;VERDINI, Federica;CAPECCI, Marianna;CERAVOLO, MARIA GABRIELLA;LEO, TOMMASO
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 have built a smartphone-based architecture in agreement with acceptability and usability requirements which is able to detect FOG and provide acoustic feedback to the patient. The aim of this work is to compare the reliability of a real-time FOG detection using two different algorithms implemented on the smartphoneI documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
