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Nunes T, Gaspar L, Faria JN, Portugal D, Lopes T, Fernandes P, Tavakoli M. Deployment and validation of a smart bed architecture for untethered patients with wireless biomonitoring stickers. Med Biol Eng Comput 2024:10.1007/s11517-024-03155-3. [PMID: 39037541 DOI: 10.1007/s11517-024-03155-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2024] [Accepted: 06/10/2024] [Indexed: 07/23/2024]
Abstract
Conventional patient monitoring in healthcare has limitations such as delayed identification of deteriorating conditions, disruptions to patient routines, and discomfort due to extensive wiring for bed-bound patients. To address these, we have recently developed an innovative IoT-based healthcare system for real-time wireless patient monitoring. This system includes a flexible epidermal patch that collects vital signs using low power electronics and transmits the data to IoT nodes in hospital beds. The nodes connect to a smart gateway that aggregates the information and interfaces with the hospital information system (HIS), facilitating the exchange of electronic health records (EHR) and enhancing access to patient vital signs for healthcare professionals. Our study validates the proposed smart bed architecture in a clinical setting, assessing its ability to meet healthcare personnel needs, patient comfort, and data transmission reliability. Technical performance assessment involves analyzing key performance indicators for communication across various interfaces, including the wearable device and the smart box, and the link between the gateway and the HIS. Also, a comparative analysis is conducted on data from our architecture and traditional hospital equipment. Usability evaluation involves questionnaires completed by patients and healthcare professionals. Results demonstrate the robustness of the architecture proposed, exhibiting reliable and efficient information flow, while offering significant improvements in patient monitoring over conventional wired methods, including unrestricted mobility and improved comfort to enhance healthcare delivery.
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Affiliation(s)
- Tânia Nunes
- Institute of Systems and Robotics, University of Coimbra, Coimbra, Portugal
| | - Luís Gaspar
- Institute of Systems and Robotics, University of Coimbra, Coimbra, Portugal
| | - José N Faria
- Institute of Systems and Robotics, University of Coimbra, Coimbra, Portugal
| | - David Portugal
- Institute of Systems and Robotics, University of Coimbra, Coimbra, Portugal.
| | - Telmo Lopes
- Institute of Systems and Robotics, University of Coimbra, Coimbra, Portugal
| | - Pedro Fernandes
- Institute of Systems and Robotics, University of Coimbra, Coimbra, Portugal
| | - Mahmoud Tavakoli
- Institute of Systems and Robotics, University of Coimbra, Coimbra, Portugal
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Jeyaraman N, Jeyaraman M, Yadav S, Ramasubramanian S, Balaji S, Muthu S, Lekha P C, Patro BP. Applications of Fog Computing in Healthcare. Cureus 2024; 16:e64263. [PMID: 39130982 PMCID: PMC11315376 DOI: 10.7759/cureus.64263] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/10/2024] [Indexed: 08/13/2024] Open
Abstract
Fog computing is a decentralized computing infrastructure that processes data at or near its source, reducing latency and bandwidth usage. This technology is gaining traction in healthcare due to its potential to enhance real-time data processing and decision-making capabilities in critical medical scenarios. A systematic review of existing literature on fog computing in healthcare was conducted. The review included searches in major databases such as PubMed, IEEE Xplore, Scopus, and Google Scholar. The search terms used were "fog computing in healthcare," "real-time diagnostics and fog computing," "continuous patient monitoring fog computing," "predictive analytics fog computing," "interoperability in fog computing healthcare," "scalability issues fog computing healthcare," and "security challenges fog computing healthcare." Articles published between 2010 and 2023 were considered. Inclusion criteria encompassed peer-reviewed articles, conference papers, and review articles focusing on the applications of fog computing in healthcare. Exclusion criteria were articles not available in English, those not related to healthcare applications, and those lacking empirical data. Data extraction focused on the applications of fog computing in real-time diagnostics, continuous monitoring, predictive analytics, and the identified challenges of interoperability, scalability, and security. Fog computing significantly enhances diagnostic capabilities by facilitating real-time data analysis, crucial for urgent diagnostics such as stroke detection, by processing data closer to its source. It also improves monitoring during surgeries by enabling real-time processing of vital signs and physiological parameters, thereby enhancing patient safety. In chronic disease management, continuous data collection and analysis through wearable devices allow for proactive disease management and timely adjustments to treatment plans. Additionally, fog computing supports telemedicine by enabling real-time communication between remote specialists and patients, thereby improving access to specialist care in underserved regions. Fog computing offers transformative potential in healthcare, improving diagnostic precision, patient monitoring, and personalized treatment. Addressing the challenges of interoperability, scalability, and security will be crucial for fully realizing the benefits of fog computing in healthcare, leading to a more connected and efficient healthcare environment.
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Affiliation(s)
- Naveen Jeyaraman
- Orthopaedics, ACS Medical College and Hospital, Dr. MGR Educational and Research Institute, Chennai, IND
| | - Madhan Jeyaraman
- Clinical Research, Virginia Tech India, Dr. MGR Educational and Research Institute, Chennai, IND
- Orthopaedics, ACS Medical College and Hospital, Dr. MGR Educational and Research Institute, Chennai, IND
| | - Sankalp Yadav
- Medicine, Shri Madan Lal Khurana Chest Clinic, New Delhi, IND
| | | | - Sangeetha Balaji
- Orthopaedics, Government Medical College, Omandurar Government Estate, Chennai, IND
| | - Sathish Muthu
- Orthopaedics and Traumatology, Orthopaedic Research Group, Coimbatore, IND
- Biotechnology, Karpagam Academy of Higher Education, Coimbatore, IND
- Orthopaedics, Government Medical College, Karur, IND
| | - Chithra Lekha P
- Clinical Research, Virginia Tech India, Dr. MGR Educational and Research Institute, Chennai, IND
| | - Bishnu P Patro
- Orthopaedics, All India Institute of Medical Sciences, Bhubaneswar, IND
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Akbari O, Dehghan M, Tirgari B. Development and Validation of the Nurses' Spiritual Sensitivity Scale in Southeastern Iran. JOURNAL OF RELIGION AND HEALTH 2023; 62:3529-3545. [PMID: 37005973 DOI: 10.1007/s10943-023-01805-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 03/21/2023] [Indexed: 06/19/2023]
Abstract
Spiritual sensitivity refers to awareness and perception of the attitudes and feelings of others and helps nurses to recognize and take responsibility for the spiritual values and needs of patients. The dimensions of spiritual sensitivity remain unknown as there is no comprehensive and standardized scale for assessing nurses' spiritual sensitivity; therefore, the current research aimed to design and validate the nurses' spiritual sensitivity scale. We conducted this exploratory sequential study using eight stages suggested by DeVellis (2016) when developing the scale. We conducted this study among Iranian nurses from March 2021 to October 2022. Results suggested a 20-item scale with two components (nurses' professional spiritual sensitivity and nurses' internal spiritual sensitivity) that explained 57.62% of the total variance extracted. We were able to confirm convergent validity based on an acceptable correlation between the nurses' spiritual sensitivity scale and the King's spiritual intelligence scale (r = 0.66), which showed good stability (cronbach's alpha coefficient = 0.927, omega coefficient = 0.923, and icc = 0.937). Spiritual sensitivity in nurses is difficult to evaluate. Considering the acceptability of the psychometric properties of the "Nurses' spiritual sensitivity" scale, this scale can be used in clinical environments to evaluate nurses' spiritual sensitivity. Therefore, it is suggested that managers and policy makers should consider developing related guidelines to help nurses to become more spiritually sensitive and also to meet the spiritual needs of patients. We suggest further studies to confirm the study results in the nursing community.
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Affiliation(s)
- Omolbanin Akbari
- Department of Nursing, School of Nursing and Midwifery, Zahedan University of Medical Sciences, Zahedan, Iran
| | - Mahlagha Dehghan
- Department of Critical Care Nursing, Razi Faculty of Nursing and Midwifery, Kerman University of Medical Sciences, Kerman, Iran.
| | - Batool Tirgari
- Nursing Research Center, Kerman University of Medical Sciences, Kerman, Iran.
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Gangl C, Krychtiuk K. Digital health-high tech or high touch? Wien Med Wochenschr 2023; 173:115-124. [PMID: 36602630 PMCID: PMC9813878 DOI: 10.1007/s10354-022-00991-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2022] [Accepted: 11/07/2022] [Indexed: 01/06/2023]
Abstract
Digital transformation in medicine refers to the implementation of information technology-driven developments in the healthcare system and their impact on the way we teach, share, and practice medicine. We would like to provide an overview of current developments and opportunities but also of the risks of digital transformation in medicine. Therefore, we examine the possibilities wearables and digital biomarkers provide for early detection and monitoring of diseases and discuss the potential of artificial intelligence applications in medicine. Furthermore, we outline new opportunities offered by telemedicine applications and digital therapeutics, discuss the aspects of social media in healthcare, and provide an outlook on "Health 4.0."
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Affiliation(s)
- Clemens Gangl
- Department of Internal Medicine II, Division of Cardiology, Medical University of Vienna, Währinger Gürtel 18–20, 1090 Vienna, Austria
| | - Konstantin Krychtiuk
- Department of Internal Medicine II, Division of Cardiology, Medical University of Vienna, Währinger Gürtel 18–20, 1090 Vienna, Austria
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Sheikh Sofla M, Haghi Kashani M, Mahdipour E, Faghih Mirzaee R. Towards effective offloading mechanisms in fog computing. MULTIMEDIA TOOLS AND APPLICATIONS 2021; 81:1997-2042. [PMID: 34690529 PMCID: PMC8526054 DOI: 10.1007/s11042-021-11423-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/02/2020] [Revised: 02/06/2021] [Accepted: 08/10/2021] [Indexed: 06/13/2023]
Abstract
Fog computing is considered a formidable next-generation complement to cloud computing. Nowadays, in light of the dramatic rise in the number of IoT devices, several problems have been raised in cloud architectures. By introducing fog computing as a mediate layer between the user devices and the cloud, one can extend cloud computing's processing and storage capability. Offloading can be utilized as a mechanism that transfers computations, data, and energy consumption from the resource-limited user devices to resource-rich fog/cloud layers to achieve an optimal experience in the quality of applications and improve the system performance. This paper provides a systematic and comprehensive study to evaluate fog offloading mechanisms' current and recent works. Each selected paper's pros and cons are explored and analyzed to state and address the present potentialities and issues of offloading mechanisms in a fog environment efficiently. We classify offloading mechanisms in a fog system into four groups, including computation-based, energy-based, storage-based, and hybrid approaches. Furthermore, this paper explores offloading metrics, applied algorithms, and evaluation methods related to the chosen offloading mechanisms in fog systems. Additionally, the open challenges and future trends derived from the reviewed studies are discussed.
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Affiliation(s)
- Maryam Sheikh Sofla
- Department of Computer Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran
| | - Mostafa Haghi Kashani
- Department of Computer Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran
| | - Ebrahim Mahdipour
- Department of Computer Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran
| | - Reza Faghih Mirzaee
- Department of Computer Engineering, Shahr-e-Qods Branch, Islamic Azad University, Tehran, Iran
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