Background: Parkinson's Disease (PD) is a chronic neurodegenerative disease associated with motor problems such as gait impairment. Different systems based on 3D cameras, accelerometers or gyroscopes have been used in related works in order to study gait disturbances in PD. Kinect has also been used to build these kinds of systems, but contradictory results have been reported: some works conclude that Kinect does not provide an accurate method of measuring gait kinematics variables, but others, on the contrary, report good accuracy results.
View Article and Find Full Text PDFInnovation in the fields of wireless data communications, mobile devices and biosensor technology enables the development of new types of monitoring systems that provide people with assistance anywhere and at any time. In this paper we present an architecture useful to build those kind of systems that monitor data streams generated by biological sensors attached to mobile users. We pay special attention to three aspects related to the system efficiency: selection of the optimal granularity, that is, the selection of the size of the input data stream package that has to be acquired in order to start a new processing cycle; the possible use of compression techniques to store and send the acquired input data stream and; finally, the performance of a local analysis versus a remote one.
View Article and Find Full Text PDFCardiovascular diseases and, in particular, diseases related to arrhythmias are a problem that affects a significant percentage of the population, being one of the major causes of death in Europe. New advances in the fields of PDAs, mobile phones, wireless communications and vital parameter sensors have permitted the development of revolutionary medical monitoring systems, which strikingly improve the lifestyle of patients. However, not all those monitoring systems provide patients with real assistance - anywhere and at any time.
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