Background: Wearable monitoring devices based on inertial sensors have the potential to be used as a quantitative method in clinical practice for continuous assessment of gait disabilities in Parkinson's disease (...
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Background: Wearable monitoring devices based on inertial sensors have the potential to be used as a quantitative method in clinical practice for continuous assessment of gait disabilities in Parkinson's disease (PD). methods: This manuscript introduces a new gait monitoring system adapted to patients with PD, based on a wearable monitoring device. To eliminate inter- and intra-subject variability, the computationalmethod was based on heuristic rules with adaptive thresholds and ranges and a motion compensation strategy. The experimental trials involved repeated measurements of walking trials from two cross-sectional studies: the first study was performed in order to validate the effectiveness of the system against a robust 3D motion analysis with 10 healthy subjects;and the second-one aimed to validate our approach against a well-studied wearable IMU-based system on a hospital environment with 20 patients with PD. Results: The proposed system proved to be efficient (Experiment I: sensitivity = 95,09% and accuracy = 93,64%;Experiment II: sensitivity = 99,53% and accuracy = 97,42%), time-effective (Experiment I: earlies = 13,71 ms and delays = 12,91 ms;Experiment II: earlies = 12,94 ms and delays = 12,71 ms), user and user-motion adaptable and a low computational-load strategy for real-time gait events detection. Further, it was measured the percentage of absolute error classified with a good acceptability (Experiment I: 3,02 < epsilon%<12,94;Experiment II: 2,81 < epsilon%<13,45). Lastly, regarding the measured gait parameters, it was observed a reflection of the typical levels of motor impairment for the different disease stages. Conclusion: The achieved outcomes enabled to verify that the proposed system can be suitable for gait analysis in the assistance and rehabilitation fields.
We propose in this paper a quantum correction transport model for nanoscale double-gate metal-oxide-semiconductor field effect transistor (MOSFET) device simulation. Based on adaptive finite volume, parallel domain de...
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We propose in this paper a quantum correction transport model for nanoscale double-gate metal-oxide-semiconductor field effect transistor (MOSFET) device simulation. Based on adaptive finite volume, parallel domain decomposition, monotone iterative, and a posteriori error estimation methods, the model is solved numerically on a PC-based Linux cluster with MPI libraries. Quantum mechanical effect plays an important role in semiconductor nanoscale device simulation. To model this effect. a physical-based quantum correction equation is derived and solved with the hydrodynamic transport model. Numerical calculation of the quantum correction transport model is implemented with the parallel adaptive finite volume method which has recently been proposed by us in deep-submicron semiconductor device simulation. A 20 nm double-gate MOSFET is simulated with the developed quantum transport model and computational technique. Compared with a classical transport model. it is found that this model can account for the quantum mechanical effects of the nanoscale double-gate MOSFET quantitatively. Various biasing conditions have been verified on the simulated device to demonstrate its accuracy. Furthermore. for the same tested problem, the parallel adaptive computation shows very good computational performance in terms of the mesh refinements, the parallel speedup, the load-balancing, and the efficiency. (C) 2004 Elsevier B.V. All rights reserved.
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