INTRODUCTION: The GENEA shows high accuracy for classification of sedentary, household, walking, and running activities when sampling at 80 Hz on three axes. It is not known whether it is possible to decrease this sampling frequency and/or the number of axes without detriment to classification accuracy. The purpose of this study was to compare the classification rate of activities on the basis of data from a single axis, two axes, and three axes, with sampling rates ranging from 5 to 80 Hz. METHODS: Sixty participants (age, 49.4 yr (6.5 yr); BMI, 24.6 kg·m (3.4 kg·m)) completed 10-12 semistructured activities in the laboratory and outdoor environment while wearing a GENEA accelerometer on the right wrist. We analyzed data from single axis, dual axes, and three axes at sampling rates of 5, 10, 20, 40, and 80 Hz. Mathematical models based on features extracted from mean, SD, fast Fourier transform, and wavelet decomposition were built, which combined one of the numbers of axes with one of the sampling rates to classify activities into sedentary, household, walking, and running. RESULTS: Classification accuracy was high irrespective of the number of axes for data collected at 80 Hz (96.93% ± 0.97%), 40 Hz (97.4% ± 0.73%), 20 Hz (96.86% ± 1.12%), and 10 Hz (97.01% ± 1.01%) but dropped for data collected at 5 Hz (94.98% ± 1.36%). CONCLUSION: Sampling frequencies >10 Hz and/or more than one axis of measurement were not associated with greater classification accuracy. Lower sampling rates and measurement of a single axis would result in a lower data load, longer battery life, and higher efficiency of data processing. Further research should investigate whether a lower sampling rate and a single axis affects classification accuracy when considering a wider range of activities.
INTRODUCTION: The GENEA shows high accuracy for classification of sedentary, household, walking, and running activities when sampling at 80 Hz on three axes. It is not known whether it is possible to decrease this sampling frequency and/or the number of axes without detriment to classification accuracy. The purpose of this study was to compare the classification rate of activities on the basis of data from a single axis, two axes, and three axes, with sampling rates ranging from 5 to 80 Hz. METHODS: Sixty participants (age, 49.4 yr (6.5 yr); BMI, 24.6 kg·m (3.4 kg·m)) completed 10-12 semistructured activities in the laboratory and outdoor environment while wearing a GENEA accelerometer on the right wrist. We analyzed data from single axis, dual axes, and three axes at sampling rates of 5, 10, 20, 40, and 80 Hz. Mathematical models based on features extracted from mean, SD, fast Fourier transform, and wavelet decomposition were built, which combined one of the numbers of axes with one of the sampling rates to classify activities into sedentary, household, walking, and running. RESULTS: Classification accuracy was high irrespective of the number of axes for data collected at 80 Hz (96.93% ± 0.97%), 40 Hz (97.4% ± 0.73%), 20 Hz (96.86% ± 1.12%), and 10 Hz (97.01% ± 1.01%) but dropped for data collected at 5 Hz (94.98% ± 1.36%). CONCLUSION: Sampling frequencies >10 Hz and/or more than one axis of measurement were not associated with greater classification accuracy. Lower sampling rates and measurement of a single axis would result in a lower data load, longer battery life, and higher efficiency of data processing. Further research should investigate whether a lower sampling rate and a single axis affects classification accuracy when considering a wider range of activities.
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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
Authors: Séverine Sabia; Vincent T van Hees; Martin J Shipley; Michael I Trenell; Gareth Hagger-Johnson; Alexis Elbaz; Mika Kivimaki; Archana Singh-Manoux Journal: Am J Epidemiol Date: 2014-02-04 Impact factor: 4.897
Authors: Seung Won Lee; Jee-Seon Shim; Bo Mi Song; Ho Jae Lee; Hye Yoon Bae; Ji Hye Park; Hye Rin Choi; Jae Won Yang; Ji Eun Heo; So Mi Jemma Cho; Ga Bin Lee; Diana Huanan Hidalgo; Tae-Hoon Kim; Kyung Soo Chung; Hyeon Chang Kim Journal: Epidemiol Health Date: 2018-11-29
Authors: Scott R Small; Garrett S Bullock; Sara Khalid; Karen Barker; Marialena Trivella; Andrew James Price Journal: BMJ Open Date: 2019-12-29 Impact factor: 2.692
Authors: Leo D Westbury; Richard M Dodds; Holly E Syddall; Alicja M Baczynska; Sarah C Shaw; Elaine M Dennison; Helen C Roberts; Avan Aihie Sayer; Cyrus Cooper; Harnish P Patel Journal: Calcif Tissue Int Date: 2018-03-27 Impact factor: 4.333