Journal of medical engineering & technology
-
Pulmonary ventilators for intensive care provide information on, among many other patient respiratory parameters, patient resistance, compliance and 'work of breathing' values calculated from pressure and flow data patterns according to a widely utilized algorithm. The effects induced by the breathing circuit and analogue filtering of the ventilator measuring system are experimentally investigated during controlled ventilation. Three main phenomena are observed: (a) errors in calculation of resistance and compliance due to filtering of pressure and flow waveforms; (b) the presence of pressure oscillations at the beginning of inspiration and expiration phases; and (c) the phase shift between pressure and flow waveforms. The experimental evaluation of the measuring system of a neonatal ventilator is then conducted and: (a) a delay in pressure and flow measurement synchronization equal to 22 +/- 2 ms is evaluated; moreover, (b) a difference between the values provided by the ventilator and those measured by the reference experimental setup on respiratory parameters such as the compliance, resistance and work of breathing that lies in the range of 7-16% of reading is observed.
-
A novel homomorphic wavelet thresholding technique for reducing speckle noise in medical ultrasound images is presented. First, we show that the speckle wavelet coefficients in the logarithmically transformed ultrasound images are best described by the Nakagami family of distributions. By exploiting this speckle model and the Laplacian signal prior, a closed form, data-driven, and spatially adaptive threshold is derived in the Bayesian framework. ⋯ Further, the threshold has been extended to the redundant wavelet representation, which yields better results than the decimated wavelet transform. Experimental results demonstrate the improved performance of the proposed method over other well-known speckle reduction filters. The application of the proposed method to a realistic US test image shows that the new technique, named HomoGenThresh, outperforms the best wavelet-based denoising method reported in [1] by more than 1.6 dB, Lee filter by 3.6 dB, Kaun filter by 3.1 dB and band-adaptive soft thresholding [2] by 2.1 dB at an input signal-to-noise ratio (SNR) of 13.6 dB.
-
The evaluation of medical devices in the UK has been through many changes since the early hospital equipment assessments in the 1960s. The range of medical devices evaluated has increased and the evaluation reports published have changed, but the evaluation programme continues to be a respected service for the NHS and social care. This review documents the history of the Device Evaluation Service, from its beginnings to the present day, and looks forward to its future. Following an independent strategic review and the Healthcare Industries Task Force (HITF) recommendations, the Device Evaluation Service is now entering a new and exciting developmental phase.
-
Comparative Study
Automatic segmentation of medical images using image registration: diagnostic and simulation applications.
Automatic identification of the boundaries of significant structure (segmentation) within a medical image is an are of ongoing research. Various approaches have been proposed but only two methods have achieved widespread use: manual delineation of boundaries and segmentation using intensity values. In this paper we describe an approach based on image registration. ⋯ All knowledge about the problem at hand is contained in files of reference data. A secondary benefit is that the continuous three-dimensional mapping generated is well suited to the generation of patient-specific numerical models (e.g. finite element meshes) from the library models. Smoothness constraints in the morphing algorithm tend to maintain the geometric quality of the reference mesh.
-
Comparative Study
Sampling frequency of the RR interval time series for spectral analysis of heart rate variability.
Spectral analysis of heart rate variability (HRV) is an accepted method for assessment of cardiac autonomic function and its relationship to numerous disorders and diseases. Various non-parametric methods for HRV estimation have been developed and extensive literature on their respective properties is available. The RR interval time series can be seen as a series of non-uniformly spaced samples. ⋯ While the choice of RR interval sampling frequency (f(s)) is arbitrary, the sampling rate of RR interval series must be selected with due consideration to mean and minimum RR interval; f(s = )4 Hz was proposed for a majority of cases. This is an appropriate sampling rate for the study of autonomic regulation, since it enables us to compute reliable spectral estimates between dc and 1 Hz, which represents the frequency band within which the autonomic nervous system has significant response. Furthermore, resampled RR intervals are evenly spaced in time and are synchronized with the samples of the other physiologic signals, enabling cross-spectral estimates with these signals.