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Gait analysis is important in diagnosing and evaluating certain neurological diseases such as Parkinson's disease (PD). In this paper, we show the ability of our wireless inertial sensor system to characterize gait abnormalities in PD. We obtain physical features of pitch, roll, and yaw rotations of the foot during walking, use principal component analysis(More)
Gait analysis is important for the diagnosis of many neurological diseases such as Parkinson's. The discovery and interpretation of minor gait abnormalities can aid in early diagnosis. We have used an inertial measuring system mounted on the subject's foot to provide numerical measures of a subject's gait (3-D displacements and rotations), thereby creating(More)
Public infrastructure systems provide many of the services that are critical to the health, functioning, and security of society. Many of these infrastructures, however, lack continuous physical sensor monitoring to be able to detect failure events or damage that has occurred to these systems. We propose the use of social sensor big data to detect these(More)
Novel algorithms are developed to enable the modeling of large, complex infrastructure systems as Bayesian networks (BNs). These include a compression algorithm that significantly reduces the memory storage required to construct the BN model, and an updating algorithm that performs inference on compressed matrices. These algorithms address one of the major(More)
1 The human body is a complex structure, and its structural health can be monitored using sensors. A system using wireless inertial measurement units for data acquisition and the monitoring of human gait is described. Gait analysis is used in the medical community to diagnose and evaluate patients with Parkinson’s disease. Currently, such analysis is done(More)
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