Electrical phase angle as a new method to measure fish condition

In this study, phase angle (the ratio of resistance and reactance of tissue to applied electrical current) is presented as a possible new method to measure fish condition. Condition indices for fish have historically been based on simple weight-at-length relationships, or on costly and timeconsuming laboratory procedures that measure specific physiological parameters. Phase angle is introduced to combine the simplicity of a quick field-based measurement with the specificity of laboratory analysis by directly measuring extra- and intracellular water distribution within an organism, which is indicative of its condition. Phase angle, which can be measured in the field or laboratory in the time it takes to measure length and weight, was measured in six species of fish at different states (e.g., fed vs. fasted, and postmortem) and under different environmental treatments (wild vs. hatchery, winter vs. spring). Phase angle reflected different states of condition. Phase angles <15° indicated fish in poor condition, and phase angles >15° indicated fish that were in better condition. Phase angle was slightly affected by temperatures (slope = – 0.19) in the 0–8°C range and did not change in fish placed on ice for <12 hours. Phase angle also decreased over time in postmortem fish because of cell membrane degradation and subsequent water movement from intra- to extracellular (interstitial) spaces. Phase angle also reflected condition of specific anatomical locations within the fish.

A Reliable Method for Rhythm Analysis during Cardiopulmonary Resuscitation

nterruptions in cardiopulmonary resuscitation (CPR) compromise defibrillation success. However, CPR must be interrupted to analyze the rhythm because although current methods for rhythm analysis during CPR have high sensitivity for shockable rhythms, the specificity for nonshockable rhythms is still too low. This paper introduces a new approach to rhythm analysis during CPR that combines two strategies: a state-of-the-art CPR artifact suppression filter and a shock advice algorithm (SAA) designed to optimally classify the filtered signal. Emphasis is on designing an algorithm with high specificity. The SAA includes a detector for low electrical activity rhythms to increase the specificity, and a shock/no-shock decision algorithm based on a support vector machine classifier using slope and frequency features. For this study, 1185 shockable and 6482 nonshockable 9-s segments corrupted by CPR artifacts were obtained from 247 patients suffering out-of-hospital cardiac arrest. The segments were split into a training and a test set. For the test set, the sensitivity and specificity for rhythm analysis during CPR were 91.0% and 96.6%, respectively. This new approach shows an important increase in specificity without compromising the sensitivity when compared to previous studies.