Publications by authors named "Y Mendelson"

Article Synopsis
  • Deep learning has shown promise in enhancing the diagnosis of acutely decompensated heart failure (ADHF) through the analysis of ECG data, but past efforts have mainly relied on predefined ECG patterns in controlled settings.
  • This study created a new model, ECGX-Net, which combines raw ECG data and bioimpedance data from wearable devices to improve ADHF prediction using deep feature learning techniques.
  • The results indicated that ECGX-Net achieved a high precision in predicting ADHF (94% precision, 79% recall), while a simpler model using DenseNet121 was better for high recall tasks (98% recall, 80% precision), showcasing different strengths in ECG data analysis.
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Objective: Rises in the incidence of pressure ulcers are increasingly prevalent in an aging population. Pressure ulcers are painful, are associated with increased morbidity and mortality, increase the risk for secondary infections and inpatient stay, and adds $26.8 billion annually to the healthcare costs of the USA.

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Pressure ulcers are increasingly prevalent in an aging population. The most commonly used method of pressure ulcer prevention is pressure off-loading achieved by physically turning bedbound patients or by using expensive, single application devices such as wheelchair cushions. Our aim is to approach the problem of pressure ulcer prevention in a new way: a wireless sensor worn by the patient at locations susceptible to pressure injury.

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With an aging population, the incidence and prevalence of wound problems is on the rise. Bedsores (also known as pressure ulcers or decubitus ulcers) are painful, take months to heal, and, for many patients, never do, leading to other health problems. The condition has become so acute that treating bedsores is now a significant burden on the healthcare system.

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Objective: Pulse oximetry, a widely accepted method for non-invasive estimation of arterial oxygen saturation (SpO) and pulse rate (PR), is increasingly being adapted for mobile applications. Previous work in mitigating motion artefact, which corrupts the photoplethysmogram (PPG) used in pulse oximetry, has focused on reducing noise using signal processing algorithms or through sensor design that controlled only one variable at a time. In this work, we have investigated the effect of several variables such as sensor weight, relative motion, placement, and contact force against the skin that can impact motion artefact independently or by interacting with each other.

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