Literature DB >> 11029819

Motion pattern and posture: correctly assessed by calibrated accelerometers.

F Foerster1, J Fahrenberg.   

Abstract

Basic motion patterns and posture can be distinguished by multichannel accelerometry, as recently shown. A refinement of this method appeared to be desirable to further increase its effectiveness, especially to distinguish walking and climbing stairs, and body rotation during sleep. Recordings were made of 31 subjects, according to a standard protocol comprising 13 motions and postures. This recording was repeated three times with appropriate permutation. Five uni-axial sensors and three sites of placement (sternum with three axes, right and left thigh) were selected. A hierarchical classification strategy used a standard protocol (i.e., individual reference patterns) to distinguish subtypes of moving behaviors and posture. The analysis method of the actometer signals reliably detected 13 different postural and activity conditions (only 3.2% misclassifications). A minimum set of sensors can be found for a given application; for example, a two-sensor configuration would clearly suffice to differentiate between four basic classes (sitting, standing, lying, moving) in ambulatory monitoring.

Entities:  

Mesh:

Year:  2000        PMID: 11029819     DOI: 10.3758/bf03200815

Source DB:  PubMed          Journal:  Behav Res Methods Instrum Comput        ISSN: 0743-3808


  21 in total

1.  Detection of daily physical activities using a triaxial accelerometer.

Authors:  M J Mathie; A C F Coster; N H Lovell; B G Celler
Journal:  Med Biol Eng Comput       Date:  2003-05       Impact factor: 2.602

2.  Classification of basic daily movements using a triaxial accelerometer.

Authors:  M J Mathie; B G Celler; N H Lovell; A C F Coster
Journal:  Med Biol Eng Comput       Date:  2004-09       Impact factor: 2.602

3.  Analysis of head movements coupled with trunk drift in healthy subjects.

Authors:  S Miyaoka; H Hirano; I Ashida; Y Miyaoka; Y Yamada
Journal:  Med Biol Eng Comput       Date:  2005-05       Impact factor: 2.602

4.  Recommendations for ICT use in Alzheimer's disease assessment: Monaco CTAD Expert Meeting.

Authors:  P H Robert; A Konig; S Andrieu; F Bremond; I Chemin; P C Chung; J F Dartigues; B Dubois; G Feutren; R Guillemaud; P A Kenisberg; S Nave; B Vellas; F Verhey; J Yesavage; P Mallea
Journal:  J Nutr Health Aging       Date:  2013       Impact factor: 4.075

5.  Validation of a novel physical activity assessment device in morbidly obese females.

Authors:  Soyang Kwon; Mohammad Jamal; Gideon K D Zamba; Phyllis Stumbo; Isaac Samuel
Journal:  J Obes       Date:  2010-02-09

6.  Adaptive windowing for gait phase discrimination in Parkinsonian gait using 3-axis acceleration signals.

Authors:  Jonghee Han; Hyo Seon Jeon; Won Jin Yi; Beom Seok Jeon; Kwang Suk Park
Journal:  Med Biol Eng Comput       Date:  2009-08-20       Impact factor: 2.602

7.  Performance of Activity Classification Algorithms in Free-Living Older Adults.

Authors:  Jeffer Eidi Sasaki; Amanda M Hickey; John W Staudenmayer; Dinesh John; Jane A Kent; Patty S Freedson
Journal:  Med Sci Sports Exerc       Date:  2016-05       Impact factor: 5.411

8.  Automatic video monitoring system for assessment of Alzheimer's disease symptoms.

Authors:  R Romdhane; E Mulin; A Derreumeaux; N Zouba; J Piano; L Lee; I Leroi; P Mallea; R David; M Thonnat; F Bremond; P H Robert
Journal:  J Nutr Health Aging       Date:  2012-03       Impact factor: 4.075

9.  Impact of study design on development and evaluation of an activity-type classifier.

Authors:  Vincent T van Hees; Rajna Golubic; Ulf Ekelund; Søren Brage
Journal:  J Appl Physiol (1985)       Date:  2013-02-21

10.  Using hierarchical clustering methods to classify motor activities of COPD patients from wearable sensor data.

Authors:  Delsey M Sherrill; Marilyn L Moy; John J Reilly; Paolo Bonato
Journal:  J Neuroeng Rehabil       Date:  2005-06-29       Impact factor: 4.262

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