TY - JOUR
T1 - Body pressure prediction for pressure ulcer prevention in a bed head elevation operation
AU - Kosuge, M.
AU - Ishihara, Y.
AU - Takahashi, M.
N1 - Publisher Copyright:
© 2021 Informa UK Limited, trading as Taylor & Francis Group and The Robotics Society of Japan.
PY - 2021
Y1 - 2021
N2 - 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.
AB - 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.
KW - Medical robots and systems
KW - pressure ulcers
KW - video predictive model
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U2 - 10.1080/01691864.2021.1873844
DO - 10.1080/01691864.2021.1873844
M3 - Article
AN - SCOPUS:85099994504
SN - 0169-1864
VL - 35
SP - 181
EP - 193
JO - Advanced Robotics
JF - Advanced Robotics
IS - 3-4
ER -