Literature DB >> 12529483

Measurement of human daily physical activity.

Kuan Zhang1, Patricia Werner, Ming Sun, F Xavier Pi-Sunyer, Carol N Boozer.   

Abstract

OBJECTIVES: To validate a new device, Intelligent Device for Energy Expenditure and Activity (IDEEA), for the measurement of duration, frequency, and intensity of various types of human physical activity (PA). RESEARCH METHODS AND PROCEDURES: The ability of IDEEA to identify and quantify 32 types of PA, including the most common daily exercise and nonexercise PA, was tested in 76 subjects: Subjects included males (N = 33) and females (N = 43) ranging in age from 13 to 72 years with a mean body mass index (BMI) of 24.7 kg/m(2) (range: 18.4 to 41.0) [43 females: 13 to 72 years old and BMI 18.4 to approximately 41.0 kg/m(2) (mean = 24.7 kg/m(2)); 33 males: 15 to approximately 72 years old and BMI 21.0 to approximately 38.4 kg/m(2) (mean = 25.9 kg/m(2))]. Postures, limb movements, and jumping were tested using a timed protocol of specific activities. Walking and running were tested using a 60-meter track, on which subjects walked and ran at 6 self-selected speeds. Stair climbing and descending were tested by timing subjects who climbed and descended a flight of stairs at two different speeds.
RESULTS: Correct identification rates averaged 98.9% for posture and limb movement type and 98.5% for gait type. Pooled correlation between predicted and actual speeds of walking and running was high (r = 0.986, p <or= 0.0001). DISCUSSION: IDEEA accurately measured duration, frequency, type, and intensity of a variety of daily PAs.

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Year:  2003        PMID: 12529483     DOI: 10.1038/oby.2003.7

Source DB:  PubMed          Journal:  Obes Res        ISSN: 1071-7323


  56 in total

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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.  The effect of social desirability and social approval on self-reports of physical activity.

Authors:  Swann Arp Adams; Charles E Matthews; Cara B Ebbeling; Charity G Moore; Joan E Cunningham; Jeanette Fulton; James R Hebert
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4.  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

5.  Amount of time spent in sedentary behaviors in the United States, 2003-2004.

Authors:  Charles E Matthews; Kong Y Chen; Patty S Freedson; Maciej S Buchowski; Bettina M Beech; Russell R Pate; Richard P Troiano
Journal:  Am J Epidemiol       Date:  2008-02-25       Impact factor: 4.897

6.  Support vector machine for classification of walking conditions using miniature kinematic sensors.

Authors:  Hong-Yin Lau; Kai-Yu Tong; Hailong Zhu
Journal:  Med Biol Eng Comput       Date:  2008-03-18       Impact factor: 2.602

Review 7.  Assessment of physical activity: a critical appraisal.

Authors:  Klaas R Westerterp
Journal:  Eur J Appl Physiol       Date:  2009-02-11       Impact factor: 3.078

8.  Evaluation of the ability of three physical activity monitors to predict weight change and estimate energy expenditure.

Authors:  John B Correa; John W Apolzan; Desti N Shepard; Daniel P Heil; Jennifer C Rood; Corby K Martin
Journal:  Appl Physiol Nutr Metab       Date:  2016-03-14       Impact factor: 2.665

9.  Comparison of energy expenditure in adolescents when playing new generation and sedentary computer games: cross sectional study.

Authors:  Lee Graves; Gareth Stratton; N D Ridgers; N T Cable
Journal:  BMJ       Date:  2007-12-22

10.  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
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