Publications by authors named "R Karthik Vaidyanathan"

Background: Haemorrhage remains the leading cause of preventable mortality following trauma, often aggravated by the acidosis, hypothermia and coagulopathy-the lethal triad of trauma. However, the impact of trauma-induced hypocalcemia on the haemorrhage remains unclear. It is intuitive to consider perturbations of ionised calcium early during trauma resuscitation in acutely injured patients given its pathophysiological significance for an improved outcome.

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Article Synopsis
  • Stillbirth is often linked to decreased fetal movements, but current methods for tracking these movements lack accuracy and can lead to unnecessary medical interventions.
  • New technologies, including electrocardiography and accelerometry, are being developed to provide more objective and reliable quantification of fetal movements.
  • The review highlights the need for improved fetal movement monitoring solutions that allow pregnant women to maintain their daily activities while ensuring their baby's wellbeing is effectively monitored.
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Purpose: Non-operative management (NOM) has been validated for blunt liver and splenic injuries. Literature on continuous intra-abdominal pressure (IAP) monitoring as a part of NOM remains to be equivocal. The study aimed to find any correlation between clinical parameters and IAP, and their effect on the NOM of patients with blunt liver and splenic injury.

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In hand gesture recognition, classifying gestures across multiple arm postures is challenging due to the dynamic nature of muscle fibers and the need to capture muscle activity through electrical connections with the skin. This paper presents a gesture recognition architecture addressing the arm posture challenges using an unsupervised domain adaptation technique and a wearable mechanomyogram (MMG) device that does not require electrical contact with the skin. To deal with the transient characteristics of muscle activities caused by changing arm posture, Continuous Wavelet Transform (CWT) combined with Domain-Adversarial Convolutional Neural Networks (DACNN) were used to extract MMG features and classify hand gestures.

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Robotic minimally invasive surgery (MIS) has changed numerous surgical techniques in the past few years and enhanced their results. Haptic feedback is integrated into robotic surgical systems to restore the surgeon's perception of forces in response to interaction with objects in the surgical environment. The ideal exact emulation of the robot's interaction with its physical environment in free space is a very challenging problem to solve completely.

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