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Incorporating patient concerns into design requirements for IoMT-based systems: The fall detection case study
- Source :
- Health informatics journal. 27(1)
- Publication Year :
- 2021
-
Abstract
- Internet of Medical Things (IoMT) systems are envisioned to provide high-quality healthcare services to patients in the comfort of their home, utilizing cutting-edge Internet of Things (IoT) technologies and medical sensors. Patient comfort and willingness to participate in such efforts is a prominent factor for their adoption. As IoT technology has provided solutions for all technical issues, patient concerns are those that seem to restrict their wider adoption. To enhance patient awareness of the system properties and enhance their willingness to adopt IoMT solutions, this paper presents a novel methodology to integrate patient concerns in the design requirements of such systems. It comprises a number of straightforward steps that an IoMT designer can follow, starting from identifying patient concerns, incorporating them in system design requirements as criticalities, proceeding to system implementation and testing, and finally, verifying that it fulfills the concerns of the patients. To showcase the effectiveness of the proposed methodology, the paper applies it in the design and implementation of a fall detection system for elderly patients remotely monitored in their homes. The Author(s) 2021. The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The authors wish to acknowledge Qatar National Research Fund project EMBIoT (Proj. No. NPRP 9-114-2-055) project, under the auspices of which the work presented in this paper has been carried out. Scopus
- Subjects :
- Computer science
Internet of Things
model-based design
Health Informatics
02 engineering and technology
01 natural sciences
remote monitoring system
Health care
Model-based design
0202 electrical engineering, electronic engineering, information engineering
Humans
Implementation
Patient comfort
Aged
Monitoring, Physiologic
patient concerns
business.industry
010401 analytical chemistry
0104 chemical sciences
fall detection
Risk analysis (engineering)
restrict
Systems design
020201 artificial intelligence & image processing
The Internet
Accidental Falls
Fall detection
internet of medical things
business
Subjects
Details
- ISSN :
- 17412811
- Volume :
- 27
- Issue :
- 1
- Database :
- OpenAIRE
- Journal :
- Health informatics journal
- Accession number :
- edsair.doi.dedup.....9802961597cce40e63cc142a170cc4e1