Harmonizing Innovation: The Beatles, EMI, and the Birth of Computed Tomography Imaging.

Description Computed tomography (CT) imaging has become a cornerstone of modern medical diagnostics, thanks to the groundbreaking work of Sir Godfrey Hounsfield. However, the significant role played by his employer, Electric and Musical Industries (EMI), in providing financial support for his research is often overlooked. In this paper, we explore the connection between EMI's success in the music industry, particularly its signing of the Beatles, and Hounsfield's pioneering work on CT imaging.

Inpatient Falls: Epidemiology, Risk Assessment, and Prevention Measures. A Narrative Review.

Background Patient falls are a common inpatient dilemma and comprise the largest category of preventable adverse events in hospitalized patients. These events place a clinical burden on the patient, such as increased morbidity and reduced quality of life, in addition to an economic burden on the hospital system. Fall prevention strategies have the opportunity to decrease inpatient health care costs and length of stay.

Necrotizing Fasciitis Masquerading as Stroke: A Diagnostic Dilemma.

Necrotizing fasciitis (NF) poses a diagnostic challenge due to its rarity and similarity in presentation with other critical conditions. We report a case of a 79-year-old male who initially presented with altered mental status and stroke-like symptoms; he was ultimately diagnosed with abdominal wall NF spreading to the lower extremity. Despite a history of cecal mass perforation noted in prior imaging, the patient had been discharged from an outside emergency room on antibiotics, highlighting a missed opportunity for early intervention.

Regression of diabetic nephropathy by treatment with empagliflozin in BTBR ob/ob mice.

Background: The sodium-glucose cotransporter-2 (SGLT2) inhibitor empagliflozin lowers blood glucose via reduced tubular reabsorption of filtered glucose and is an important new therapy for diabetic nephropathy (DN). This study tested whether treatment with empagliflozin would ameliorate proteinuria and the pathologic alterations of DN including podocyte number and integrity in the leptin-deficient BTBR ob/ob mouse model of DN.

Methods: Study cohorts included wild-type (WT) BTBR mice, untreated diabetic BTBR ob/ob mice and mice treated with empagliflozin for 6 weeks after development of established DN at 18 weeks of age.

A Simple Unsupervised, Real-time Clustering Method for Arterial Blood Pressure Signal Classification.

Biomedical signal analysis often depends on methods to detect and distinguish abnormal or high noise/artifact signal from normal signal. A novel unsupervised clustering method suitable for resource constrained embedded computing contexts, classifies arterial blood pressure (ABP) beat cycles as normal or abnormal. A cycle detection algorithm delineates beat cycles, so that each cycle can be modeled by a continuous time Fourier series decomposition.

Electrochemically Treated TiO₂ for Enhanced Performance in Aqueous Al-Ion Batteries.

The potential for low cost, environmentally friendly and high rate energy storage has led to the study of anatase-TiO₂ as an electrode material in aqueous Al electrolytes. This paper describes the improved performance from an electrochemically treated composite TiO₂ electrode for use in aqueous Al-ion batteries. After application of the cathodic electrochemical treatment in 1 mol/dm³ KOH, Mott⁻Schottky analysis showed the treated electrode as having an increased electron density and an altered open circuit potential, which remained stable throughout cycling.

An adaptive prediction method for signal fusion.

Many biomedical signal processing applications include the significant challenge of sensor data fusion. In this work, an adaptive prediction method fuses a relatively higher bandwidth, lower absolute accuracy (fast) signal with a relatively lower bandwidth, higher absolute accuracy (accurate) signal of the same quantity into a combined signal that is both fast and accurate. Iterative estimates of model parameters minimize a regularized mean square prediction error that arises from using the fast signal to predict the accurate signal.

A novel statistical model for arterial blood pressure signals.

This paper introduces a novel arterial blood pressure (ABP) signal model that generates statistically accurate synthetic signals with known characteristics. Using parameter identification from real ABP signals to form base parameter templates, our model applies stochastic processes to modulate cardiac cycle period and shape. A real-time control component modulates model parameters between cycle boundaries to emulate properties of real cardiovascular signals, such as arrhythmia, ectopic beats, resonances in the heart-rate variability spectrum, and respiratory cycle modulation of ABP signal amplitude.

A novel recursive Fourier transform for nonuniform sampled signals: application to heart rate variability spectrum estimation.

We present a novel method to iteratively calculate discrete Fourier transforms for discrete time signals with sample time intervals that may be widely nonuniform. The proposed recursive Fourier transform (RFT) does not require interpolation of the samples to uniform time intervals, and each iterative transform update of N frequencies has computational order N. Because of the inherent non-uniformity in the time between successive heart beats, an application particularly well suited for this transform is power spectral density (PSD) estimation for heart rate variability.

Signal conditioning with almost no multiplications via filter sharpening.

"Filter Sharpening" creates a filter network using the same computationally simple filter [1] or selections from a set of computationally simple filters [2]. Applications include high-quality signal conditioning using fixed-point arithmetic and only a handful of mostly add/subtract arithmetic operations to compute each output sample value. Applied to electrocardiogram baseline wander removal, for example, the highpass filter has 3 dB corner at 0.