39 research outputs found
Treatment incidence of and medical utilization for hospitalized subjects with pathologic fractures in Taiwan-Survey of the 2008 National Health Insurance data
<p>Abstract</p> <p>Background</p> <p>Almost all studies of pathologic fractures have been conducted based on patients with tumours and hospital-based data; however, in the present study, a nationwide epidemiological survey of pathologic fractures in Taiwan was performed and the medical utilization was calculated.</p> <p>Methods</p> <p>All claimants of Taiwan's National Health Insurance (NHI) Program in 2008 were included in the target population of this descriptive cross-sectional study. The registration and inpatient expenditure claims data by admission of all hospitalized subjects of the target population were examined and the concomitant International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) diagnosis codes were evaluated and classified into seven major categories of fracture.</p> <p>Results</p> <p>A total of 5,244 incident cases of pathologic fracture were identified from the 2008 hospitalized patient claims data. The incidence of pathologic fracture of the humerus, distal radius/ulna, vertebrae, femoral neck, other part of the femur, and tibia/fibula was 0.67, 0.08, 10.58, 1.11, 0.56, and 0.11 per 100,000 people, respectively, and patients with those fractures were hospitalized for 43.9 ± 42.9, 31.1 ± 32.9, 29. 4 ± 34.4, 43.3 ± 41.2, 42.4 ± 38.1, and 42.0 ± 32.8 days, respectively, incurring an average medical cost of US9,181 ± 12,115, US9,619 ± 8,906, US9,403 ± 9,882, respectively. The percentage of patients undergoing bone surgery for pathologic fracture of the humerus, radius/ulna, vertebrae, femoral neck, other part of the femur, and tibia/fibula was 31.2%, 44.4%, 11.3%, 46.5%, 48.4%, and 52.5% respectively.</p> <p>Conclusions</p> <p>Comparing Taiwan to other countries, this study observed for Taiwan higher medical utilization and less-aggressive surgical intervention for patients hospitalized with pathologic fractures.</p
Mouth State Detection From Low-Frequency Ultrasonic Reflection
This paper develops, simulates and experimentally evaluates a novel method based on non-contact low frequency (LF) ultrasound which can determine, from airborne reflection, whether the lips of a subject are open or closed. The method is capable of accurately distinguishing between open and closed lip states through the use of a low-complexity detection algorithm, and is highly robust to interfering audible noise. A novel voice activity detector is implemented and evaluated using the proposed method and shown to detect voice activity with high accuracy, even in the presence of high levels of background noise. The lip state detector is evaluated at a number of angles of incidence to the mouth and under various conditions of background noise. The underlying mouth state detection technique relies upon an inaudible LF ultrasonic excitation, generated in front of the face of a user, either reflecting back from their face as a simple echo in the closed mouth state or resonating inside the open mouth and vocal tract, affecting the spectral response of the reflected wave when the mouth is open. The difference between echo and resonance behaviours is used as the basis for automated lip opening detection, which implies determining whether the mouth is open or closed at the lips. Apart from this, potential applications include use in voice generation prosthesis for speech impaired patients, or as a hands-free control for electrolarynx and similar rehabilitation devices. It is also applicable to silent speech interfaces and may have use for speech authentication
The Understandability of models for behaviour
Comunicació presentada a: SMODELSWARD 2019: International Conference on Model-Driven Engineering and Software Development, celebrat del 20 al 22 de febrer de 2019 a Praga, República Txeca.Models are used mainly to communicate among humans the most relevant aspects of the item being modelled. Moreover, for achieving impact in modern complex applications, modelling languages and tools must support some level of composition. Furthermore, executable models are the foundations of model-driven development; therefore, it is crucial that we study the understandability of executable behaviour models, especially from the perspective of modular composition. We examine the match between the delicate semantics of executable models for applications such as reactive- and real-time systems and developers’ usually simple conception. Performing a series of experiments with UML statecharts and logic-labelled finite-state machines (LLFSMs), we explore understandability of event-driven vs. logic-labelled state machines as well as the architectural options for modular composition. We find that expertise in model manipulation is essential, and that clarification of the semantics of LLFSMs is necessary for them to remain formally verifiable and suitable for robotic and embedded systems