Description

Cut-points for mean amplitude deviation (MAD) that can be used for any accelerometer brand were determined from adults wearing three monitors at the hip participating in walking and running. Sensitivity (98.3-100%) and specificity (96.9-100%) are reported.

Development/Validation

Sample: 21 (4 males) healthy adults, 42±11 years of age

Setting: Inside track

Activities: Overground/self-paced walking and running, stationary

Criterion: Activity type

Accelerometer(s): Hookie AM13, ActiGraph GT3X, and GulfCoast X6-1A on hip

Validation approach: Comparison to criterion

Phase Designation

(What's this?)

This model is in Phase 2.

Instructions

While the authors compare several features derived from the accelerometers, they conclude that MAD performed the best and thus, only present results from this metric. Calculate MAD (mg) as the mean distance of data points about the mean where n is the number of samples in the epoch, ri is the ith resultant sample within the epoch and r(bar) is the mean resultant value of the epoch. This can also be done in R using a package like acc or GGIR. In this paper, they used an epoch of 5.1 s (Hookie), 4.3 s (ActiGraph), or 6.4 s (GulfCoast).

Each epoch can they be classified using the cut-points, which can be used with any accelerometer model. Activities were divided into five distinct intensity classes; sedentary behaviors (class 0), slow walking (class 1), normal walking (class 2), brisk walking (class 3), and jogging and running (class 4). Limit 1 separates the intensity class 0 from class 1, limit 2 the class 1 from class 2, limit 3 the class 3 from class 2 and limit 4 the class 4 from class 3.

Source Information

Vähä‐Ypyä, H., Vasankari, T., Husu, P., Suni, J., & Sievänen, H. (2015). A universal, accurate intensity‐based classification of different physical activities using raw data of accelerometer. Clinical Physiology and Functional Imaging, 35(1), 64-70. https://doi.org/10.1111/cpf.12127 Link to Paper

Corresponding author: Henri Vähä‐Ypyä, henri.vaha-ypya@uta.fi

Contact

Kimberly Clevenger at accelerometerrepository@gmail.com