Geriatric Care Management System Powered by the IoT and Computer Vision Techniques
The digitalisation of geriatric care refers to the use of emerging technologies to manage and provide person-centered care to the elderly by collecting patients’ data electronically and using them to streamline the care process, which improves the overall quality, accuracy, and efficiency of healthc...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-04-01
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| Series: | Healthcare |
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| Online Access: | https://www.mdpi.com/2227-9032/11/8/1152 |
| _version_ | 1797605316198662144 |
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| author | Agne Paulauskaite-Taraseviciene Julius Siaulys Kristina Sutiene Titas Petravicius Skirmantas Navickas Marius Oliandra Andrius Rapalis Justinas Balciunas |
| author_facet | Agne Paulauskaite-Taraseviciene Julius Siaulys Kristina Sutiene Titas Petravicius Skirmantas Navickas Marius Oliandra Andrius Rapalis Justinas Balciunas |
| author_sort | Agne Paulauskaite-Taraseviciene |
| collection | DOAJ |
| description | The digitalisation of geriatric care refers to the use of emerging technologies to manage and provide person-centered care to the elderly by collecting patients’ data electronically and using them to streamline the care process, which improves the overall quality, accuracy, and efficiency of healthcare. In many countries, healthcare providers still rely on the manual measurement of bioparameters, inconsistent monitoring, and paper-based care plans to manage and deliver care to elderly patients. This can lead to a number of problems, including incomplete and inaccurate record-keeping, errors, and delays in identifying and resolving health problems. The purpose of this study is to develop a geriatric care management system that combines signals from various wearable sensors, noncontact measurement devices, and image recognition techniques to monitor and detect changes in the health status of a person. The system relies on deep learning algorithms and the Internet of Things (IoT) to identify the patient and their six most pertinent poses. In addition, the algorithm has been developed to monitor changes in the patient’s position over a longer period of time, which could be important for detecting health problems in a timely manner and taking appropriate measures. Finally, based on expert knowledge and a priori rules integrated in a decision tree-based model, the automated final decision on the status of nursing care plan is generated to support nursing staff. |
| first_indexed | 2024-03-11T04:59:19Z |
| format | Article |
| id | doaj.art-b70fd33253a847ad943e3a4f46a4409f |
| institution | Directory Open Access Journal |
| issn | 2227-9032 |
| language | English |
| last_indexed | 2024-03-11T04:59:19Z |
| publishDate | 2023-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Healthcare |
| spelling | doaj.art-b70fd33253a847ad943e3a4f46a4409f2023-11-17T19:27:15ZengMDPI AGHealthcare2227-90322023-04-01118115210.3390/healthcare11081152Geriatric Care Management System Powered by the IoT and Computer Vision TechniquesAgne Paulauskaite-Taraseviciene0Julius Siaulys1Kristina Sutiene2Titas Petravicius3Skirmantas Navickas4Marius Oliandra5Andrius Rapalis6Justinas Balciunas7Faculty of Informatics, Kaunas University of Technology, Studentu 50, 51368 Kaunas, LithuaniaFaculty of Informatics, Kaunas University of Technology, Studentu 50, 51368 Kaunas, LithuaniaDepartment of Mathematical Modeling, Kaunas University of Technology, Studentu 50, 51368 Kaunas, LithuaniaFaculty of Informatics, Kaunas University of Technology, Studentu 50, 51368 Kaunas, LithuaniaFaculty of Informatics, Kaunas University of Technology, Studentu 50, 51368 Kaunas, LithuaniaFaculty of Informatics, Kaunas University of Technology, Studentu 50, 51368 Kaunas, LithuaniaBiomedical Engineering Institute, Kaunas University of Technology, K. Barsausko 59, 51423 Kaunas, LithuaniaFaculty of Medicine, Vilnius University, Universiteto 3, 01513 Vilnius, LithuaniaThe digitalisation of geriatric care refers to the use of emerging technologies to manage and provide person-centered care to the elderly by collecting patients’ data electronically and using them to streamline the care process, which improves the overall quality, accuracy, and efficiency of healthcare. In many countries, healthcare providers still rely on the manual measurement of bioparameters, inconsistent monitoring, and paper-based care plans to manage and deliver care to elderly patients. This can lead to a number of problems, including incomplete and inaccurate record-keeping, errors, and delays in identifying and resolving health problems. The purpose of this study is to develop a geriatric care management system that combines signals from various wearable sensors, noncontact measurement devices, and image recognition techniques to monitor and detect changes in the health status of a person. The system relies on deep learning algorithms and the Internet of Things (IoT) to identify the patient and their six most pertinent poses. In addition, the algorithm has been developed to monitor changes in the patient’s position over a longer period of time, which could be important for detecting health problems in a timely manner and taking appropriate measures. Finally, based on expert knowledge and a priori rules integrated in a decision tree-based model, the automated final decision on the status of nursing care plan is generated to support nursing staff.https://www.mdpi.com/2227-9032/11/8/1152geriatric careIoTvital parametersposture recognitionimage recognitiondeep learning |
| spellingShingle | Agne Paulauskaite-Taraseviciene Julius Siaulys Kristina Sutiene Titas Petravicius Skirmantas Navickas Marius Oliandra Andrius Rapalis Justinas Balciunas Geriatric Care Management System Powered by the IoT and Computer Vision Techniques Healthcare geriatric care IoT vital parameters posture recognition image recognition deep learning |
| title | Geriatric Care Management System Powered by the IoT and Computer Vision Techniques |
| title_full | Geriatric Care Management System Powered by the IoT and Computer Vision Techniques |
| title_fullStr | Geriatric Care Management System Powered by the IoT and Computer Vision Techniques |
| title_full_unstemmed | Geriatric Care Management System Powered by the IoT and Computer Vision Techniques |
| title_short | Geriatric Care Management System Powered by the IoT and Computer Vision Techniques |
| title_sort | geriatric care management system powered by the iot and computer vision techniques |
| topic | geriatric care IoT vital parameters posture recognition image recognition deep learning |
| url | https://www.mdpi.com/2227-9032/11/8/1152 |
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