Literature DB >> 11591066

Measuring daily behavior using ambulatory accelerometry: the Activity Monitor.

J B Bussmann1, W L Martens, J H Tulen, F C Schasfoort, H J van den Berg-Emons, H J Stam.   

Abstract

Advanced ambulatory systems that measure aspects of overt human behavior during normal daily life have become feasible, owing to developments in data recording and sensor technology. One such instrument is the Activity Monitor (AM). This paper provides a technical description of the AM and information about its validity and current applications. The AM is based on ambulatory accelerometry, the aim of which is to assess postures and motions for long-term (> 24-h) measurement periods during normal daily life. Accelerometers are attached to the thighs, trunk, and lower arms, and signals are continuously stored in a digital portable recorder. In the postmeasurement analysis, postures and motions are detected by means of custom-made software programs. Validity studies performed on different populations showed high agreement scores between the computerized and automatic AM output and the visually analyzed video recordings. The AM has so far been applied in rehabilitation, psychophysiology, and cardiology but has many possibilities in behavioral research.

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Year:  2001        PMID: 11591066     DOI: 10.3758/bf03195388

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


  57 in total

1.  Ambulatory measurement of upper limb usage and mobility-related activities during normal daily life with an upper limb-activity monitor: a feasibility study.

Authors:  F C Schasfoort; J B J Bussmann; H J Stam
Journal:  Med Biol Eng Comput       Date:  2002-03       Impact factor: 2.602

2.  Recognition of physical activities in overweight Hispanic youth using KNOWME Networks.

Authors:  B Adar Emken; Ming Li; Gautam Thatte; Sangwon Lee; Murali Annavaram; Urbashi Mitra; Shrikanth Narayanan; Donna Spruijt-Metz
Journal:  J Phys Act Health       Date:  2011-05-11

3.  Accelerometer's position independent physical activity recognition system for long-term activity monitoring in the elderly.

Authors:  Adil Mehmood Khan; Young-Koo Lee; Sungyoung Lee; Tae-Seong Kim
Journal:  Med Biol Eng Comput       Date:  2010-11-04       Impact factor: 2.602

4.  Analysis and decomposition of accelerometric signals of trunk and thigh obtained during the sit-to-stand movement.

Authors:  W G M Janssen; J B J Bussmann; H L D Horemans; H J Stam
Journal:  Med Biol Eng Comput       Date:  2005-03       Impact factor: 2.602

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

Authors:  P M Grant; C G Ryan; W W Tigbe; M H Granat
Journal:  Br J Sports Med       Date:  2006-09-15       Impact factor: 13.800

6.  People With Aneurysmal Subarachnoid Hemorrhage Have Low Physical Fitness and Can Be Predisposed to Inactive and Sedentary Lifestyles.

Authors:  Wouter J Harmsen; Ladbon Khajeh; Gerard M Ribbers; Majanka H Heijenbrok-Kal; Emiel Sneekes; Fop van Kooten; Sebastian Neggers; Rita J van den Berg-Emons
Journal:  Phys Ther       Date:  2019-07-01

7.  Normalization and extraction of interpretable metrics from raw accelerometry data.

Authors:  Jiawei Bai; Bing He; Haochang Shou; Vadim Zipunnikov; Thomas A Glass; Ciprian M Crainiceanu
Journal:  Biostatistics       Date:  2013-09-01       Impact factor: 5.899

8.  Classification of human physical activity based on raw accelerometry data via spherical coordinate transformation.

Authors:  Michał Kos; Małgorzata Bogdan; Nancy W Glynn; Jaroslaw Harezlak
Journal:  Stat Med       Date:  2020-06-01       Impact factor: 2.373

9.  Objective and Self-Reported Physical Activity Measures and Their Association With Depression and Satisfaction With Life in Persons With Spinal Cord Injury.

Authors:  Sara J Mulroy; Patricia E Hatchett; Valerie J Eberly; Lisa Lighthall Haubert; Sandy Conners; JoAnne Gronley; Eric Garshick; Philip S Requejo
Journal:  Arch Phys Med Rehabil       Date:  2016-04-22       Impact factor: 3.966

10.  Movement prediction using accelerometers in a human population.

Authors:  Luo Xiao; Bing He; Annemarie Koster; Paolo Caserotti; Brittney Lange-Maia; Nancy W Glynn; Tamara B Harris; Ciprian M Crainiceanu
Journal:  Biometrics       Date:  2015-08-19       Impact factor: 2.571

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