Motion analysis in delirium: A discrete approach in determining physical activity for the purpose of delirium motoric subtyping

Alan Godfrey*, Richard Conway, Maeve Leonard, David Meagher, Gearóid M. Ólaighin

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

22 Citations (Scopus)

Abstract

The purpose of this study was to determine the use and feasibility of accelerometry-based monitoring and to examine a discrete multi-resolution signal analysis technique to determine motoric subtypes in patients with DSM-IV delirium. Forty consecutive patients receiving palliative care (23 male, 17 female, mean age ± standard deviation 68.4 ± 11.9 years) were assessed using 24-h accelerometer-based monitoring. The total amount of time spent per activity of sitting/lying, standing and stepping were calculated. This was achieved through the multilevel decomposition and reconstruction of the accelerometer signals by means of the discrete wavelet transform. Both the reconstructed approximations and details of the discrete transform were used for motoric subtyping. This was compared to a validated activity monitor for validation purposes. Demographic and clinical data per patient were also collected. Of the 40 patients selected for accelerometry, complete 24-h readings were available for 34 patients and analyses were confined to this group. Of the 34 patients included, 25 met criteria for DSM-IV delirium while 9 were non-delirious comparison subjects with equivalent medical diagnoses receiving treatment in the same setting. It was concluded that accelerometry-based measurement of a delirious cohort within a palliative setting is both a reliable and feasible method of continuous monitoring. Of the activities performed by the patients, periods of standing proved to be the most discriminatory in determining between each subtype.

Original languageEnglish
Pages (from-to)101-110
Number of pages10
JournalMedical Engineering and Physics
Volume32
Issue number2
DOIs
Publication statusPublished - 1 Mar 2010
Externally publishedYes

Keywords

  • Accelerometer
  • Activity
  • Delirium
  • Discrete wavelet transform
  • Motoric subtyping

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