ABSTRACT

Pressure ulcers are caused by tissue damage, which occurs when the blood supply to an area of skin is diminished because of sustained or concentrated pressure on a patient from the mattresses of a bed. One action that concentrates the pressure is a bed head elevation operation. Recently, a control system known as the alternative pressure mattress has been proposed to prevent the concentration of pressure. However, the challenge with this controlled system is that it has a slow response because it uses air cells. The slow response causes controlling the air cells to lag behind the change in pressure during the bed head elevation operation. Therefore, this system cannot adequately prevent the concentration of pressure on a patient. To address this issue, we need to predict the change in pressure during the bed head elevation operation and control the pressure based on this prediction. In the current work, we focus on predicting the pressure distribution. This prediction is high-dimensional. We regarded the pressure distribution as an image and predicted the change in pressure by applying a deep neural network. To the best of our knowledge, this paper is the first to propose the body pressure predictive model.

摘要

压疮是由组织损伤引起的，组织损伤是由于床褥对患者的持续或集中压力使皮肤区域的血液供应减少而发生的。集中压力的一个动作是床头抬高操作。最近，已经提出了一种称为替代压力床垫的控制系统，以防止压力集中。但是，这种受控系统面临的挑战是由于使用气室，因此响应速度较慢。缓慢的响应导致控制气室滞后于床头抬高操作期间的压力变化。因此，该系统不能充分防止压力集中在患者身上。为了解决这个问题，我们需要预测床头抬高操作期间的压力变化，并根据此预测来控制压力。在当前的工作中，我们专注于预测压力分布。该预测是高维的。我们将压力分布视为一幅图像，并通过应用深度神经网络来预测压力的变化。据我们所知，本文是第一个提出体压预测模型的论文。