A pervasive energy-efficient ECG monitoring approach for detecting abnormal cardiac situations - Archive ouverte HAL
Conference Papers Year : 2013

A pervasive energy-efficient ECG monitoring approach for detecting abnormal cardiac situations

Vinicius L. Bezerra
  • Function : Author
Liliam B. Leal
  • Function : Author
Marcus Vinicius Lemos
  • Function : Author
Carlos Giovanni Carvalho
  • Function : Author
José Filho
  • Function : Author

Abstract

Mobile and pervasive ECG monitoring systems require continuous connectivity with server-side ECG analyser for instantaneously detecting abnormal cardiac situations. Normally, these systems generate a large amount of data, resulting in a high energy expenditure with data transmission on pervasive ECG platform. In this context, data reduction mechanisms can be applied for saving transmission energy of pervasive ECG monitoring devices, maximizing the availability and confiability of ECG monitoring systems. This paper proposes an pervasive energy-efficient ECG monitoring approach for detecting abnormal cardiac situations for ubiquitous health systems. The data reduction approach based on error prediction maximize the life time of pervasive ECG monitoring device by gathering and reducing heart signal before sending it to server-side ECG analyzer application. Moreover, Pearson's Coefficient (correlation rate) is applied on the proposed data reduction approach, enhancing the quality of monitored heart signal.
Fichier principal
Vignette du fichier
VLB2013.pdf (737.94 Ko) Télécharger le fichier
Origin Files produced by the author(s)

Dates and versions

hal-00954931 , version 1 (25-02-2024)

Identifiers

Cite

Vinicius L. Bezerra, Liliam B. Leal, Marcus Vinicius Lemos, Carlos Giovanni Carvalho, José Filho, et al.. A pervasive energy-efficient ECG monitoring approach for detecting abnormal cardiac situations. 15th IEEE International Conference on e-Health Networking, Applications and Services (Healthcom 2013), Oct 2013, Lisbon, Portugal. pp.340--345, ⟨10.1109/HealthCom.2013.6720697⟩. ⟨hal-00954931⟩
241 View
12 Download

Altmetric

Share

More