In-Bed Posture Classification Using Pressure Data from a Sensor Sheet Under the Mattress

被引：0
|
作者：
Serra, André [1 ]
Ribeiro, Fernando [1 ,2 ]
Metrôlho, José [1 ,2 ]
机构：
[1] Polytechnic Institute of Castelo Branco, Castelo Branco,6000-081, Portugal
[2] CISeD—Research Center in Digital Services, Instituto Politécnico de Viseu, Viseu,3504-510, Portugal
来源：
Information (Switzerland) | 2024年 / 15卷 / 12期
关键词：
Monitoring and controlling the condition of bedridden individuals can help reduce health risks; as improper nocturnal habits or body positioning can exacerbate issues such as apnea; insomnia; sleep disorders; spinal problems; and pressure ulcers. Techniques using pressure maps from sensors placed on top of the mattress; along with machine learning (ML) algorithms to classify main postures (prone; supine; left side; right side); have achieved up to 99% accuracy. This study evaluated the feasibility of using a sensor sheet placed under the mattress to minimize patient discomfort. Experiments with ten commonly used ML algorithms achieved average accuracy values ranging from 79.14% to 98.93% using K-Fold cross-validation and from 80.03% to 97.14% using Leave-One-Group-Out (LOGO) for classifying the four main postures. The classification was extended to include 28 posture variations (7 variations for each of the 4 main postures); with the SVM algorithm achieving an accuracy of 65.18% in K-Fold validation; marking a significant improvement over previous studies; particularly regarding the number of postures considered. Comparisons with previous studies that used pressure sensors placed both under and on top of the mattress show that this approach achieves comparable accuracy to other methods; surpassing them with some algorithms and achieving the highest average accuracy. In conclusion; using sensors under the mattress is an effective and less invasive alternative for posture classification. © 2024 by the authors;
D O I：
10.3390/info15120763
中图分类号：
学科分类号：
摘要：
引用
收藏
相关论文
共 50 条
  • [21] On Bed Posture Recognition with Pressure Sensor Array System
    Sun, Qingquan
    Gonzalez, Eli
    Sun, Yu
    2016 IEEE SENSORS, 2016,
  • [22] Effective Posture Classification Using Statistically Significant Data From Flexible Pressure Sensors
    Yoon, Jungeun
    Moon, Aekyeung
    Son, Seung Woo
    IEEE Journal on Flexible Electronics, 2024, 3 (05): : 173 - 180
  • [23] Non-Contact Capacitive Ballistocardiogram Measurements Using In-Bed Fabric-Sheet Electrode for Blood Pressure Estimation
    Sakajiri, Yuichiro
    Nakamura, Hajime
    Ueno, Akinori
    2019 41ST ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC), 2019, : 1155 - 1158
  • [24] Sleep position classification with a compact pressure textile sensor mattress using convolutional neural networks
    Breuss, Alexander
    Gnarra, Oriella
    Fujs, Manuel
    Schmidt, Markus
    Riener, Robert
    BIOMEDICAL SIGNAL PROCESSING AND CONTROL, 2024, 90
  • [25] Analysis and Comparison of Sleeping Posture Classification Methods using Pressure Sensitive Bed System
    Hsia, C. C.
    Liou, K. J.
    Aung, A. P. W.
    Foo, V
    Huang, W.
    Biswas, J.
    2009 ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOLS 1-20, 2009, : 6131 - +
  • [26] Textile-Based Pressure Sensing Matrix for In-Bed Monitoring of Subject Sleeping Posture and Breathing Activity
    Carbonaro, Nicola
    Laurino, Marco
    Arcarisi, Lucia
    Menicucci, Danilo
    Gemignani, Angelo
    Tognetti, Alessandro
    APPLIED SCIENCES-BASEL, 2021, 11 (06):
  • [27] Identification of Nocturnal Movements During Sleep using the Non-Contact Under Mattress Bed Sensor
    Walsh, Lorcan
    Moloney, Eddie
    McLoone, Sean
    2011 ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC), 2011, : 1660 - 1663
  • [28] Classification of Human Posture on Bed Using Machine Learning
    Sawada, Kenta
    Nakasho, Kazuhisa
    Wasaki, Katsumi
    Shimoi, Nobuhiro
    2022 IEEE INTERNATIONAL CONFERENCE ON CONSUMER ELECTRONICS - TAIWAN, IEEE ICCE-TW 2022, 2022, : 547 - 548
  • [29] Design and Modeling of a Textile Pressure Sensor for Sitting Posture Classification
    Meyer, Jan
    Arnrich, Bert
    Schumm, Johannes
    Troester, Gerhard
    IEEE SENSORS JOURNAL, 2010, 10 (08) : 1391 - 1398
  • [30] Remote Recognition of In-Bed Postures Using a Thermopile Array Sensor With Machine Learning
    Chen, Zhangjie
    Wang, Ya
    IEEE SENSORS JOURNAL, 2021, 21 (09) : 10428 - 10436
12345