Literature DB >> 15990066

A description of an accelerometer-based mobility monitoring technique.

G M Lyons1, K M Culhane, D Hilton, P A Grace, D Lyons.   

Abstract

Accurate monitoring of the mobility status of older adults, over the long-term, is important in rehabilitation medicine, as regular physical activity is central to maintaining both physical and mental health, as well as evaluating quality of life. This technical note describes an accelerometer-based mobility monitoring technique, which can distinguish between static and dynamic activities and can detect the basic postures of sitting, standing and lying. The technique allows thresholds for these postures to be set and two different posture threshold methods are described: mid-point and "best estimate". Preliminary results from using these methods are presented. This preliminary evaluation of the technique was carried out over the long-term (>29 h) in an uncontrolled environment and the method used to carry out the evaluation is described in detail. The two different posture thresholding methods were tested on long-term mobility data from one older adult subject. The subject did not have to follow a specific activity protocol during the recording period (4 days) and was shadowed by an observer in order to evaluate the accuracy of this technique. The monitoring hardware consisted of two accelerometer devices, one on the trunk and the other on the thigh and a pocket-sized ambulatory data-logger. Applying 'best estimate' thresholding, as opposed to mid-point thresholding, improved sitting detection accuracy by 18%, to 93% and lying detection accuracy by 5%, to 84%. Thus, based on these preliminary data, an accurate mobility monitoring system for older adults is described and it was observed that the actual posture threshold limits applied have a high impact on the mobility monitoring system's accuracy and are particularly important for accurately detecting postures when used over the long-term, in an uncontrolled environment.

Mesh:

Year:  2005        PMID: 15990066     DOI: 10.1016/j.medengphy.2004.11.006

Source DB:  PubMed          Journal:  Med Eng Phys        ISSN: 1350-4533            Impact factor:   2.242


  24 in total

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2.  The validation of a novel activity monitor in the measurement of posture and motion during everyday activities.

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3.  Posture and movement classification: the comparison of tri-axial accelerometer numbers and anatomical placement.

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4.  Validity of using tri-axial accelerometers to measure human movement - Part I: Posture and movement detection.

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Journal:  Med Eng Phys       Date:  2013-07-27       Impact factor: 2.242

5.  Local dynamic stability associated with load carrying.

Authors:  Jian Liu; Thurmon E Lockhart
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Review 6.  A review of accelerometry-based wearable motion detectors for physical activity monitoring.

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Journal:  Sensors (Basel)       Date:  2010-08-20       Impact factor: 3.576

7.  Accuracy of a custom physical activity and knee angle measurement sensor system for patients with neuromuscular disorders and gait abnormalities.

Authors:  Frank Feldhege; Anett Mau-Moeller; Tobias Lindner; Albert Hein; Andreas Markschies; Uwe Klaus Zettl; Rainer Bader
Journal:  Sensors (Basel)       Date:  2015-05-06       Impact factor: 3.576

8.  Auto detection and segmentation of physical activities during a Timed-Up-and-Go (TUG) task in healthy older adults using multiple inertial sensors.

Authors:  Hung P Nguyen; Fouaz Ayachi; Catherine Lavigne-Pelletier; Margaux Blamoutier; Fariborz Rahimi; Patrick Boissy; Mandar Jog; Christian Duval
Journal:  J Neuroeng Rehabil       Date:  2015-04-11       Impact factor: 4.262

9.  Validation and Reliability of a Classification Method to Measure the Time Spent Performing Different Activities.

Authors:  Marie-Ève Riou; François Rioux; Gilles Lamothe; Éric Doucet
Journal:  PLoS One       Date:  2015-06-08       Impact factor: 3.240

10.  Quasi-real time estimation of angular kinematics using single-axis accelerometers.

Authors:  Alessio Caroselli; Fabio Bagalà; Angelo Cappello
Journal:  Sensors (Basel)       Date:  2013-01-15       Impact factor: 3.576

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