Go to:
Logótipo
Comuta visibilidade da coluna esquerda
Você está em: Start > Publications > View > Monitoring of bedridden patients: Development of a fall detection tool
Publication

Publications

Monitoring of bedridden patients: Development of a fall detection tool

Title
Monitoring of bedridden patients: Development of a fall detection tool
Type
Article in International Conference Proceedings Book
Year
2013
Authors
vilas-boas, m
(Author)
Other
The person does not belong to the institution. The person does not belong to the institution. The person does not belong to the institution. Without AUTHENTICUS Without ORCID
silva, p
(Author)
Other
The person does not belong to the institution. The person does not belong to the institution. The person does not belong to the institution. Without AUTHENTICUS Without ORCID
cunha, sr
(Author)
Other
The person does not belong to the institution. The person does not belong to the institution. The person does not belong to the institution. Without AUTHENTICUS Without ORCID
correia, mv
(Author)
FEUP
View Personal Page You do not have permissions to view the institutional email. Search for Participant Publications View Authenticus page View ORCID page
Conference proceedings International
Pages: 4742-4745
35th Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society (EMBC)
Osaka, JAPAN, JUL 03-07, 2013
Scientific classification
FOS: Engineering and technology > Environmental biotechnology
Other information
Authenticus ID: P-008-P6Y
Abstract (EN): Falls of patients are an important issue in hospitals nowadays; it causes severe injuries, increases hospitalization time and treatment costs. The detection of a fall, in time, provides faster rescue to the patient, preventing more serious injuries, as well as saving nursing time. The MovinSense (R) is an electronic device designed for monitoring patients to prevent pressure sores, and the main goal of this work was to develop a new tool for this device, with the purpose of detecting if the patient has fallen from the hospital bed, without changing any of the device's original features. Experiments for gathering data samples of inertial signals of falling from the bed were obtained using the device. For fall detection a sensitivity of 72% and specificity of 100% were reached. Another algorithm was developed to detect if the patient got out of his/her bed.
Language: English
Type (Professor's evaluation): Scientific
Contact: casousacardosovb@gmail.com; p.silva@tomorrow-options.com; sergio@fe.up.pt; mcorreia@fe.up.pt
No. of pages: 4
Documents
We could not find any documents associated to the publication.
Recommend this page Top
Copyright 1996-2025 © Faculdade de Direito da Universidade do Porto  I Terms and Conditions  I Acessibility  I Index A-Z
Page created on: 2025-08-10 at 14:41:30 | Privacy Policy | Personal Data Protection Policy | Whistleblowing