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<p>The use of pulse wave analysis may assist cardiologists in diagnosing patients with vascular diseases. However, it is not common in clinical practice to interpret and analyze pulse wave data and utilize them to detect the abnormalities of the signal. This paper presents a novel approach to the clinical application of pulse waveform analysis using the wavelet technique by decomposing the normal and pathology signal into many levels. The discrete wavelet transform (DWT) decomposes the carotid arterial pulse wave (CAPW) signal, and the continuous wavelet transform (CWT) creates images of the decomposed signal. The wavelet analysis technique in this work aims to strengthen the medical benefits of the pulse wave. The obtained results show a clear difference between the signal and the images of the arterial pathologies in comparison with normal ones. The certain distinct that were achieved are promising but further improvement may be required in the future.</p>

Abstract-The assessment of medical equipment condition has become an issue of increasing concern within healthcare services over the recent years. Most of the used tools to assess medical equipment condition ignore the effect of equipment Down Time (DT) as major factors in determining medical equipment status. This manuscript describes the use of equipment DT over the assessment process, factors that impact equipment DT , auto measurement of equipment Up Time and DT, the assessment criteria, and the assessment of medical equipment condition (MEC) in respect to their DT. The assessment process was implemented for 27653 medical equipment in 30 hospitals, 732 health centers at the Jordanian Ministry of Health (MOH). Along with the use of others assessment factors, the assessment of MEC in respect to their DT provided a significant improvement to the assessment, planning, and replacement processes of medical equipment at the Jordanian Ministry of Health during the last three years.