Detection of Physical Activity Types Using Triaxial Accelerometers

Abstract

The developed method for detecting physical activity types showed a high sensitivity and specificity for sitting, standing, walking, running, walking stairs, and cycling in a standardized setting and for sitting posture during free living.

Does aerobic exercise improve or impair cardiorespiratory fitness and health among cleaners? A cluster randomized controlled trial

“…Secondary outcomes are 4-months changes in relative aerobic workload (%HRR), RHR in beats-per-minute (bpm), SHR (bpm), and resting systolic BP (mmHg). Only HR measurements with beat error of ≤50% were included to meet the data quality criteria set by Skotte and colleagues (51).…”

Prolonged sitting at work is associated with a favorable time course of low-back pain among blue-collar workers: a prospective study in the DPhacto cohort

“…com), directly mounted on the skin at the front of the right thigh (at the right thigh medial between the iliac crest and the upper border of the patella) and at the back at T1-T2 level by adhesives (17,35,36). If the data from the accelerometer mounted at the back did not fulfill the quality criterion, data from the hip accelerometer were used (below the upper point of the iliac crest at the right side).…”

“…The accelerometers were initialized and data was downloaded using the Actilife software (version 5.5). Accelerometer signals were low-pass filtered at 5 Hz using a fourth-order Butterworth filter and then split up in 2-second windows with 50% overlap, and then analyzed in the customized software called Acti4 (36). Non-wear periods were classified based on the following criteria: (i) the participant registered non-wear in the diary, (ii) the Acti4 detected periods >90 minutes with zero acceleration, and (iii) missing data and/or artefacts were visually detected.…”

Does objectively measured daily duration of forward bending predict development and aggravation of low-back pain? A prospective study

“…The Acti4 software has been validated in a number of studies of movement of the arm and upper body, and step count and frequency in walking and running in semi-standardized settings. All studies were evaluated with high sensitivity of ≥95% and specificity ≥93% for detecting physical activity types and body postures (25)(26)(27). Furthermore, a number of studies (28) have validated the software for various activity types, eg, sitting, standing and walking, in free-living conditions.…”

“…For all further analyses, a custom-made MatLab-based software [Acti4, The National Research Centre for the Working Environment, Copenhagen, Denmark (25)] was used to determine physical activity types, body postures and inclination of the trunk. The Acti4 software is described in details elsewhere (25). The Acti4 software has been validated in a number of studies of movement of the arm and upper body, and step count and frequency in walking and running in semi-standardized settings.…”