Health monitoring in the home of the future
Abstract
We discuss health monitoring as a potential application field for wearable sensors. We present some usage models for health monitoring and discuss the technical requirements for the health-monitoring system based on wearable and ambient sensors, which measure health-related data in daily environments of the users or patients. The presentation is by no means complete, but it aims to give an idea of the system-level issues to be considered for real applications. The technology in this area is rapidly developing, and without doubt we will evidence emergence of these applications in the coming years in the market.
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Long-term and continuous monitoring of vital signs is particularly important in early diagnosis of diseases, management of chronic diseases, and timely response to life-threatening situations.
“Long-term and continuous monitoring of vital signs is particularly important in early diagnosis of diseases, management of chronic diseases such as diabetes, asthma, hypertension, and severe obesity, and timely response to life-threatening situations such as seizure and cardiac arrest.[2,3]”
From Nanomaterial-Enabled Wearable Sensors for Healthcare (2018) · cites this paper as [2]
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A Batteryless Motion-Adaptive Heartbeat Detection System-on-Chip Powered by Human Body Heat
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Local Dynamic Stability Assessment of Motion Impaired Elderly Using Electronic Textile Pants
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FROM IMAGING NETWORKS TO BEHAVIOR PROFILING: UBIQUITOUS SENSING FOR MANAGED HOMECARE OF THE ELDERLY
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An algorithm for the automatic detection of health conditions
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A design model for building occupancy detection using sensor fusion
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An Integrated Healthcare System for Personalized Chronic Disease Care in Home–Hospital Environments
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Smart medication management system and multiple interventions for medication adherence
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Wearable sensor data fusion for remote health assessment and fall detection
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Ambient intelligence, ethics and privacy
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- Authors
- Korhonen, I., Parkka, J., & Van Gils, M.
- Affiliations
- Tampere University of Technology (FI)
- ORCID
- Korhonen, I.
- Venue
- IEEE Engineering in Medicine and Biology Magazine
- Published
- 2003-05
- Volume
- 22
- Issue
- 3
- Pages
- 66-73
- ISSN
- 0739-5175 (ISSN-L)
- OpenAlex
- W2058709726
- Cited by
- 486
- References
- 18
- Citations by year
- 2026: 2 · 2025: 12 · 2024: 10 · 2023: 10 · 2022: 21 · 2021: 24 · 2020: 9 · 2019: 19 · 2018: 18 · 2017: 28 · 2016: 21 · 2015: 23 · 2014: 30 · 2013: 35 · 2012: 28
- FWCI
- 19.58
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- IEEE Engineering in Medicine and Biology Magazine (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Context-Aware Activity Recognition Systems
- Physical Sciences › Engineering › Biomedical Engineering › Non-Invasive Vital Sign Monitoring
- Physical Sciences › Computer Science › Computer Networks and Communications › Wireless Sensor Networks for Data Analysis
- Keywords
- health monitoring, wearable sensors, ambient sensors, home health care, usage models, health data acquisition, system-level requirements
- MeSH terms
- Activities of Daily Living, Clothing, Diagnosis, Computer-Assisted, Humans, Miniaturization, Therapy, Computer-Assisted, Transducers, Telemedicine, Home Care Services, Hospital-Based, Monitoring, Ambulatory
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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