Methodology for Using Long-Term Accelerometry Monitoring to Describe Daily Activity Patterns in COPD

Abstract

We sought to develop procedures for computerized analysis of long-term, high-resolution activity monitoring data that allow accurate assessment of the time course of activity levels suitable for use in chronic obstructive pulmonary disease (COPD) patients. Twenty-two COPD patients utilizing long-term oxygen recruited from 5 sites of the COPD Clinical Research Network wore a triaxial accelerometer (RT3, Stayhealthy, Monrovia, CA) during waking hours over a14 day period. Computerized algorithms were composed allowing minute-by-minute activity data to be analyzed to determine, for each minute, whether the monitor was being worn. Temporal alignment allowed determination of average time course of activity level, expressed as average vector magnitude units (VMU, the vectorial sum of activity counts in three orthogonal directions) per minute, for each hour of the day. Mid-day activity was quantified as average VMU/minute between 10AM and 4PM for minutes the monitor was worn. Over the 14 day monitoring period, subjects wore the monitor an average of 11.4±3.0 hours·day−1. During midday hours, subjects wore the monitor 76.3% of the time and generated an average activity level of 112±55 VMU·min−1. Increase in precision of activity estimates with longer monitoring periods was demonstrated. This analysis scheme allows a detailed temporal pattern of activity to be defined from triaxial accelerometer recordings and has the potential to facilitate comparisons among subjects and between subject groups. This trial is registered at ClinicalTrials.gov (NCT00325754).

Assessing physical activity in the daily life of cystic fibrosis patients

“…This seems to indicate the initial skepticism of patients as regards the size and visibility of the sensor. The percentages were significantly lower than those reported by Hecht et al [18] for COPD.…”

“…To assess compliance we calculated the percentage of time over which each patient had used the sensor as defined by the algorithm proposed by Hecht et al [18] and described in Fig. 1.…”

“…1. For the RT3 sensor we used a threshold of 5 VMU [18], given the fact that this sensor produces noise under stationary conditions. For the GT1M sensor we defined a threshold of 0 activity counts, given its insensitivity to noise under stationary conditions.…”

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“…Reference [7] presented an algorithm for a minute-by-minute analysis of patients' activity level, based on data recorded using a single unit. The system was tested in 22 patients who were monitored over a period of 14 days.…”

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“…The RT3 records activity of the three orthogonal directions as vector magnitude units (VMU) in time intervals of 1 minute [20]. A previous version of this sensor has been used successfully in patients with COPD [21]. We synchronized the clock on each sensor with the clock of the same computer, which ensured synchronicity of the three sensors.…”