A smart health monitoring technology

Carl Chalmers*, William Hurst, Michael Mackay, Paul Fergus

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference paperAcademicpeer-review

3 Citations (Scopus)

Abstract

With the implementation of the Advanced Metering Infrastructure (AMI), comes the opportunity to gain valuable insights into an individual’s daily habits, patterns and routines. A vital part of the AMI is the smart meter. It enables the monitoring of a consumer’s electricity usage with a high degree of accuracy. Each device reports and records a consumer’s energy usage readings at regular intervals. This facilitates the identification of emerging abnormal behaviours and trends, which can provide operative monitoring for people living alone with various health conditions. Through profiling, the detection of sudden changes in behaviour is made possible, based on the daily activities a patient is expected to undertake during a 24-h period. As such, this paper presents the development of a system which detects accurately the granular differences in energy usage which are the result of a change in an individual’s health state. Such a process provides accurate monitoring for people living with self-limiting conditions and enables an early intervention practice (EIP) when a patient’s condition is deteriorating. The results in this paper focus on one particular behavioural trend, the detection of sleep disturbances; which is related to various illnesses, such as depression and Alzheimer’s. The results demonstrate that it is possible to detect sleep pattern changes to an accuracy of 95.96% with 0.943 for sensitivity, 0.975 for specificity and an overall error of 0.040 when using the VPC Neural Network classifier. This type of behavioral detection can be used to provide a partial assessment of a patient’s wellbeing.

Original languageEnglish
Title of host publicationIntelligent Computing Theories and Application - 12th International Conference, ICIC 2016, Proceedings
EditorsPrashan Premaratne, De-Shuang Huang, Vitoantonio Bevilacqua
PublisherSpringer Verlag
Pages832-842
Number of pages11
ISBN (Print)9783319422909
DOIs
Publication statusPublished - 2016
Externally publishedYes
Event12th International Conference on Intelligent Computing Theories and Application, ICIC 2016 - Lanzhou, China
Duration: 2 Aug 20165 Aug 2016

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9771
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference12th International Conference on Intelligent Computing Theories and Application, ICIC 2016
CountryChina
CityLanzhou
Period2/08/165/08/16

Keywords

  • Activates of daily living
  • Advanced metering infrastructure
  • Assistive technologies
  • Customer access devices
  • Early intervention practice
  • Profiling
  • Smart grids
  • Smart meters

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