Cited by 423Non-Invasive Vital Sign MonitoringContext-Aware Activity Recognition SystemsWireless Body Area Networks

Wearable Sensors and Systems

Open access
Bonato, Paolo·2010·IEEE Engineering in Medicine and Biology Magazine

Abstract

It is now more than 50 years since the time when clinical monitoring of individuals in the home and community settings was first envisioned. Until recently, technologies to enable such vision were lacking. However, wearable sensors and systems developed over the past decade have provided the tools to finally implement and deploy technology with the capabilities required by researchers in the field of patients' home monitoring. As discussed, potential applications of these technologies include the early diagnosis of diseases such as congestive heart failure, the prevention of chronic conditions such as diabetes, improved clinical management of neurodegenerative conditions such as Parkinson's disease, and the ability to promptly respond to emergency situations such as seizures in patients with epilepsy and cardiac arrest in subjects undergoing cardiovascular monitoring. Current research efforts are now focused on the development of more complex systems for home monitoring of individuals with a variety of preclinical and clinical conditions. Recent research on the clinical assessment of wearable technology promises to deliver methodologies that are expected to lead to clinical adoption within the next five to ten years. In particular, combining home robots and wearable technology is likely to be a key step toward achieving the goal of effectively monitoring patients in the home. These efforts to merge home robots and wearable technology are expected to enable a new generation of complex systems with the ability to monitor subjects' status, facilitate the administration of interventions, and provide an invaluable tool to respond to emergency situations.

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Research works printed but not linked: 4

  1. P. F. Binkley, ''The next era of examination and management of the patient with car- diovascular disease,'' IEEE Eng. Med. Biol. Mag., vol. 22, pp. 23-24, May-June 2003.
  2. K. Lorincz, B. R. Chen, G. W. Challen, A. R. Chowdhury, S. Patel, P. Bonato, and M. Welsh, ''Mercury: A wearable sensor network platform for high-fidelity motion analysis,'' in Proc. 7th ACM Conf. Embedded Networked Sensor Systems (SenSys'09), Berkeley, CA, 2009, pp. 183-196.
  3. N. L. Keijsers, M. W. Horstink, J. J. Van Hilten, J. I. Hoff, and C. C. Gielen, ''Detection and assessment of the severity of levodopa-induced dyskinesia in patients with Parkinson's disease by neural networks,'' Mov. Disord., vol. 15, pp. 1104-1111, Nov. 2000.
  4. M. Baechlin, M. Plotnik, D. Roggen, I. Meidan, J. Hausdorff, N. Giladi, and G. Troester, ''Assistive cueing, context awareness, freezing of gait, Parkinson's dis- ease, personal health assistant,'' IEEE Trans. Inf. Technol. Biomed., to be published.

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Authors
Bonato, P.
Affiliations
Harvard University (US)
Corresponding author
Bonato, Paolo
Venue
IEEE Engineering in Medicine and Biology Magazine
Published
2010-05
Volume
29
Issue
3
Pages
25-36
ISSN
0739-5175 (ISSN-L)
OpenAlex
W2032802664
Cited by
423
References
66
Citations by year
2026: 22 · 2025: 30 · 2024: 26 · 2023: 15 · 2022: 29 · 2021: 25 · 2020: 29 · 2019: 13 · 2018: 31 · 2017: 29 · 2016: 40 · 2015: 36 · 2014: 38 · 2013: 22 · 2012: 23
FWCI
11.35
Type
journal article
Language
en
Open access
Locations
  • IEEE Engineering in Medicine and Biology Magazine (publishedVersion)
  • PubMed (publishedVersion)
  • DSpace@MIT (Massachusetts Institute of Technology) (submittedVersion, cc-by-nc)
Topics
  • Physical Sciences › Engineering › Biomedical Engineering › Non-Invasive Vital Sign Monitoring
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Context-Aware Activity Recognition Systems
  • Physical Sciences › Engineering › Biomedical Engineering › Wireless Body Area Networks
Keywords
wearable sensors, home monitoring, remote patient monitoring, home robots, congestive heart failure, diabetes prevention, Parkinson's disease, epilepsy, cardiac arrest, cardiovascular monitoring, emergency response
MeSH terms
Clothing, Diagnosis, Computer-Assisted, Equipment Design, Signal Processing, Computer-Assisted, Telemedicine, Monitoring, Ambulatory

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