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Tremor is the most common motor disorder of Parkinson's disease (PD) and consequently its detection plays a crucial role in the management and treatment of PD patients. The current diagnosis procedure is based on subject-dependent clinical assessment, which has a difficulty in capturing subtle tremor features. In this paper, an automated method for both(More)
The aim of this study is to detect freezing of gait (FoG) events in patients suffering from Parkinson's disease (PD) using signals received from wearable sensors (six accelerometers and two gyroscopes) placed on the patients' body. For this purpose, an automated methodology has been developed which consists of four stages. In the first stage, missing values(More)
In this paper, a real-time methodology for the detection of stress events while driving is presented. The detection is based on the use of physiological signals, i.e., electrocardiogram, electrodermal activity, and respiration, as well as past observations of driving behavior. Features are calculated over windows of specific length and are introduced in a(More)
OBJECTIVE In this study, a methodology is presented for an automated levodopa-induced dyskinesia (LID) assessment in patients suffering from Parkinson's disease (PD) under real-life conditions. METHODS AND MATERIAL The methodology is based on the analysis of signals recorded from several accelerometers and gyroscopes, which are placed on the subjects'(More)
This paper presents the economic design of X control charts for monitoring a critical stage of the main production process at a tile manufacturer in Greece. Two types of X-charts are developed: a chart of the Shewhart type with fixed parameters and adaptive charts with variable sampling intervals and/or sample size. Our prime motivation was to improve the(More)
—This paper describes a novel Alert Manager which merges information coming from: (i) an in-vehicle sensing system, (ii) the road infrastructure and (iii) neighbouring cars to generate more high level and useful information for the driver. It has been developed as a part of the I-WAY system, whose aim is to provide drivers with timely warnings and(More)
In this work we present a methodology for modeling and monitoring the evolvement of oral cancer in remittent patients during the post-treatment follow-up period. Our primary aim is to calculate the probability that a patient will develop a relapse but also to identify the approximate time-frame that this relapse is prone to appear. To this end, we start off(More)
In this paper, we propose a method to estimate the density of a data space represented by a geometric transformation of an initial Gaussian mixture model. The geometric transformation is hierarchical, and it is decomposed into two steps. At first, the initial model is assumed to undergo a global similarity transformation modeled by translation, rotation,(More)