European Resuscitation Council Guidelines for Resuscitation.

Plethysmographic signals were measured remotely (>1m) using ambient light and a simple consumer level digital camera in movie mode. Heart and respiration rates could be quantified up to several harmonics. Although the green channel featuring the strongest plethysmographic signal, corresponding to an absorption peak by (oxy-) hemoglobin, the red and blue channels also contained plethysmographic information. The results show that ambient light photo-plethysmography may be useful for medical purposes such as characterization of vascular skin lesions (e.g., port wine stains) and remote sensing of vital signs (e.g., heart and respiration rates) for triage or sports purposes.

/pdf/remote-plethysmographic-imaging-using-ambient-light-2yjd5b5jb7.pdf

Remote plethysmographic imaging using ambient light

In recent years, there has been an increasing interest in the adoption of emerging sensing technologies for instrumentation within a variety of structural systems. Wireless sensors and sensor networks are emerging as sensing paradigms that the structural engineering field has begun to consider as substitutes for traditional tethered monitoring systems. A benefit of wireless structural monitoring systems is that they are inexpensive to install because extensive wiring is no longer required between sensors and the data acquisition system. Researchers are discovering that wireless sensors are an exciting technology that should not be viewed as simply a substitute for traditional tethered monitoring systems. Rather, wireless sensors can play greater roles in the processing of structural response data; this feature can be utilized to screen data for signs of structural damage. Also, wireless sensors have limitations that require novel system architectures and modes of operation. This paper is intended to serve as a summary review of the collective experience the structural engineering community has gained from the use of wireless sensors and sensor networks for monitoring structural performance and health.

http://www-personal.umich.edu/~jerlynch/papers/SVDReview.pdf

A summary review of wireless sensors and sensor networks for structural health monitoring

Staff members at Los Alamos National Laboratory (LANL) produced a summary of the structural health monitoring literature in 1995. This presentation will summarize the outcome of an updated review covering the years 1996 2001. The updated review follows the LANL statistical pattern recognition paradigm for SHM, which addresses four topics: 1. Operational Evaluation; 2. Data Acquisition and Cleansing; 3. Feature Extraction; and 4. Statistical Modeling for Feature Discrimination. The literature has been reviewed based on how a particular study addresses these four topics. A significant observation from this review is that although there are many more SHM studies being reported, the investigators, in general, have not yet fully embraced the well-developed tools from statistical pattern recognition. As such, the discrimination procedures employed are often lacking the appropriate rigor necessary for this technology to evolve beyond demonstration problems carried out in laboratory setting.

A review of structural health monitoring literature 1996-2001

The QRS complex is the most striking waveform within the electrocardiogram (ECG). Since it reflects the electrical activity within the heart during the ventricular contraction, the time of its occurrence as well as its shape provide much information about the current state of the heart. Due to its characteristic shape it serves as the basis for the automated determination of the heart rate, as an entry point for classification schemes of the cardiac cycle, and often it is also used in ECG data compression algorithms. In that sense, QRS detection provides the fundamentals for almost all automated ECG analysis algorithms. Software QRS detection has been a research topic for more than 30 years. The evolution of these algorithms clearly reflects the great advances in computer technology. Within the last decade many new approaches to QRS detection have been proposed; for example, algorithms from the field of artificial neural networks genetic algorithms wavelet transforms, filter banks as well as heuristic methods mostly based on nonlinear transforms. The authors provide an overview of these recent developments as well as of formerly proposed algorithms.

/pdf/the-principles-of-software-qrs-detection-1vgts9f7g6.pdf

The principles of software QRS detection

Tissue engineering scaffolds require a controlled pore size and structure to host tissue formation. Supercritical carbon dioxide (scCO2) processing may be used to form foamed scaffolds in which the escape of CO2 from a plasticized polymer melt generates gas bubbles that shape the developing pores. The process of forming these scaffolds involves a simultaneous change in phase in the CO2 and the polymer, resulting in rapid expansion of a surface area and changes in polymer rheological properties. Hence, the process is difficult to control with respect to the desired final pore size and structure. In this paper, we describe a detailed study of the effect of polymer chemical composition, molecular weight and processing parameters on final scaffold characteristics. The study focuses on poly(DL-lactic acid) (PDLLA) and poly(DL-lactic acid-co-glycolic acid) (PLGA) as polymer classes with potential application as controlled release scaffolds for growth factor delivery. Processing parameters under investigation were temperature (from 5 to 55 degrees C) and pressure (from 60 to 230 bar). A series of amorphous PDLLA and PLGA polymers with various molecular weights (from 13 KD to 96 KD) and/or chemical compositions (the mole percentage of glycolic acid in the polymers was 0, 15, 25, 35 and 50 respectively) were employed. The resulting scaffolds were characterised by optical microscopy, scanning electron microscopy (SEM), and micro X-ray computed tomography (microCT). This is the first detailed study on using these series polymers for scaffold formation by supercritical technique. This study has demonstrated that the pore size and structure of the supercritical PDLLA and PLGA scaffolds can be tailored by careful control of processing conditions.

/pdf/control-of-pore-size-and-structure-of-tissue-engineering-3y8g93kpow.pdf

Control of pore size and structure of tissue engineering scaffolds produced by supercritical fluid processing.

https://nottingham-repository.worktribe.com/preview/1015964/Medical_Device_Development_-_the_challenge_for_ergonomics.pdf

Medical Device Development: the challenge for ergonomics

The analysis of heart rate variability, involving changes in the autonomic modulation conditions, demands specific capabilities not provided by either parametric or non-parametric spectral estimation methods. Moreover, these methods produce time-averaged power estimates over the entire length of the record. Recently, empirical mode decomposition and the associated Hilbert spectra have been proposed for non-linear and non-stationary time series. The application of these techniques to real and simulated short-term heart rate variability data under stationary and non-stationary conditions is presented. The results demonstrate the ability of empirical mode decomposition to isolate the two main components of one chirp series and three signals simulated by the integral pulse frequency modulation model, and consistently to isolate at least four main components localised in the autonomic bands of 14 real signals under controlled breathing manoeuvres. In addition, within the short time-frequency range that is recognised for heart rate variability phenomena, the Hilbert amplitude component ratio and the instantaneous frequency representation are assessed for their suitability and accuracy in time-tracking changes in amplitude and frequency in the presence of non-stationary and non-linear conditions. The frequency tracking error is found to be less than 0.22% for two simulated signals and one chirp series.

Application of empirical mode decomposition to heart rate variability analysis.

Numerical double integration of acceleration measurements in noise

Doppler ultrasound, ultrasound M-mode analysis, fetal electrocardiography, and fetal magnetocardiography are methods by which the fetal heart can be monitored non-invasively. In this paper, they are evaluated and compared. Customarily, it is solely the fetal heart rate, which is monitored using the Doppler ultrasound technique since it is both simple to use and cheap. However, this method inherently produces an averaged heart rate and therefore cannot give the beat-to-beat variability. Fetal electrocardiography has similar advantages, but in addition offers the potential for monitoring beat-to-beat variability and performing electrocardiogram morphological analysis. Its disadvantage is that its reliability is only 60%, although it is the only technique that offers truly long-term ambulatory monitoring. Ultrasound M-mode analysis allows a estimation of atrial and ventricular coordination, as well as an estimation of PR intervals. Bradycardias, supraventricular tachycardias, extra systoles are readily diagnosed using this method although timing will be inaccurate. Fetal magnetocardiograms can be detected reliably and used for accurate beat-to-beat measurements and morphological analysis. Consequently, they can be used for the classification of arrhythmias and the diagnosis of a long QT syndrome and some congenital heart diseases.

John A. Crowe

Papers

Control of pore size and structure of tissue engineering scaffolds produced by supercritical fluid processing.

Medical Device Development: the challenge for ergonomics

Application of empirical mode decomposition to heart rate variability analysis.

Numerical double integration of acceleration measurements in noise

Monitoring the fetal heart non-invasively: a review of methods.