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Cited by 534Non-Invasive Vital Sign MonitoringWireless Body Area NetworksWireless Sensor Networks for Data Analysis

Remote patient monitoring: a comprehensive study

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Malasinghe, Lakmini P., Ramzan, Naeem, Dahal, Keshav·2019·Journal of Ambient Intelligence and Humanized Computing
DOI 10.1007/s12652-017-0598-x
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Abstract

Healthcare is a field that is rapidly developing in technology and services. A recent development in this area is remote monitoring of patients which has many advantages in a fast aging world population with increasing health complications. With relatively simple applications to monitor patients inside hospital rooms, the technology has developed to the extent that the patient can be allowed normal daily activities at home while still being monitored with the use of modern communication and sensor technologies. Sensors for monitoring essential vital signs such as electrocardiogram reading, heart rate, respiration rate, blood pressure, temperature, blood glucose levels and neural system activity are available today. Range of remote healthcare varies from monitoring chronically ill patients, elders, premature children to victims of accidents. These new technologies can monitor patients based on the illness or based on the situation. The technology varies from sensors attached to body to ambient sensors attached to the environment and new breakthroughs show contactless monitoring which requires only the patient to be present within a few meters from the sensor. Fall detection systems and applications to monitor chronical ill patients have already become familiar to many. This study provides a review of the recent advances in remote healthcare and monitoring in both with-contact and contactless methods. With the review, the authors discuss some issues available in most systems. The paper also includes some directions for future research.

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  • Existing work has explored how AI may empower healthcare work for providers, focusing on Clinical Decision Support Systems (CDSS) and clinical practices, highlighting how AI may assist human experts throughout medical diagnosis and treatments.

    “Existing work has explored how AI may empower healthcare work for providers, focusing on Clinical Decision Support Systems (CDSS) and clinical practices, highlighting how AI may assist human experts throughout medical diagnosis and treatments [41,73,76,115,127].”

    From Talk2Care: An LLM-based Voice Assistant for Communication between Healthcare Providers and Older Adults (2024) · cites this paper as [76]

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Cited by

Sorted by citations

Authors
Malasinghe, L. P., Ramzan, N., & Dahal, K.
Affiliations
University of the West of Scotland (GB)
Corresponding author
  • Malasinghe, Lakmini P.
  • Ramzan, Naeem
  • Dahal, Keshav
ORCID
Venue
Journal of Ambient Intelligence and Humanized Computing
Publisher
Springer Science and Business Media LLC
Published
2017-10-26
Volume
10
Issue
1
Pages
57-76
ISSN
  • 1868-5137 (ISSN-L)
  • 1868-5145
DOI
10.1007/s12652-017-0598-x
OpenAlex
W2766863773
Cited by
534
References
5
Citations by year
2026: 26 · 2025: 73 · 2024: 85 · 2023: 113 · 2022: 92 · 2021: 70 · 2020: 45 · 2019: 22 · 2018: 8
FWCI
9.24
Type
journal article
Language
en
Open access
Licence
Locations
  • Journal of Ambient Intelligence and Humanized Computing (publishedVersion, cc-by)
  • The UWS Academic Portal (University of the West of Scotland) (publishedVersion, cc-by)
Funders
Erasmus Mundus Action 2 - SmartLink Project (Strand I - Call for Proposals EACEA/18/13)
Topics
  • Physical Sciences › Engineering › Biomedical Engineering › Non-Invasive Vital Sign Monitoring
  • Physical Sciences › Engineering › Biomedical Engineering › Wireless Body Area Networks
  • Physical Sciences › Computer Science › Computer Networks and Communications › Wireless Sensor Networks for Data Analysis
Keywords
remote patient monitoring, remote care, vital signs monitoring, wearable sensors, non-contact sensing, ambient sensors, fall detection, elderly care, preterm infants, electrocardiogram, blood glucose monitoring, neural activity monitoring

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