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Human movement analysis is a field of wide interest since it enables the assessment of a large variety of variables related to quality of life. Human movement can be accurately evaluated through Inertial Measurement Units (IMU), which are wearable and comfortable devices with long battery life. The IMU's movement signals might be, on the one hand, stored in(More)
BACKGROUND Patients with severe idiopathic Parkinson's disease experience motor fluctuations, which are often difficult to control. Accurate mapping of such motor fluctuations could help improve patients' treatment. OBJECTIVE The objective of the study was to focus on developing and validating an automatic detector of motor fluctuations. The device is(More)
Freezing of gait (FOG) is a common motor symptom of Parkinson’s disease (PD), which presents itself as an inability to initiate or continue gait. This paper presents a method to monitor FOG episodes based only on acceleration measurements obtained from a waist-worn device. Three approximations of this method are tested. Initially, FOG is directly detected(More)
This paper presents the design and methodology used to create a heterogeneous database for knowledge movement extraction in Parkinson's Disease. This database is being constructed as part of REM-PARK project and is composed of movement measurements acquired from inertial sensors, standard medical scales as Unified Parkinson's Disease Rating Scale, and other(More)
Parkinson's Disease (PD) is a neurodegenerative disease that alters the patients' motor performance. Patients suffer many motor symptoms: bradykinesia, dyskinesia and freezing of gait, among others. Furthermore, patients alternate between periods in which they are able to move smoothly for some hours (ON state), and periods with motor complications (OFF(More)
This paper evaluates a set of computational algorithms for the automatic estimation of human postures and gait properties from signals provided by an inertial body sensor. The use of a single sensor device imposes limitations for the automatic estimation of relevant properties, like step length and gait velocity, as well as for the detection of standard(More)
This paper presents an algorithm for the automatic estimation of spatio temporal gait properties from signals provided by inertial body sensors. The approach is based on time series analysis. Here, a minimum number of body sensor devices is used, which imposes limitations for the automatic extraction of relevant properties of the gait like step length and(More)