Measuring daily behavior using ambulatory accelerometry: The Activity Monitor

By J. Bussmann, W. Martens, J. Tulen, F. Schasfoort, H. Berg-Emons, H. Stam. Behavoir research methods, instruments & computers, 2001

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Machine Learning Methods for Classifying Human Physical Activity from On-Body Accelerometers (2010, background): “In this sense extensive handcrafting of classifier parameters is believed to be detrimental for achieving good generalisation properties of the classifier itself [46].”
The technology of accelerometry-based activity monitors: current and future. (2005, background): “The target application for many of these prototype PA monitors, which have been tested primarily in small research labs in Europe, was rehabilitation in patients with leg amputation, back surgery, and chronic heart failure; although some “able-bodied” subjects were sometimes used as controls, the nu”
Activity Recognition from Accelerometer Data (2005, neutral): “Bussmann et al. 2001).”
Activity identification using body-mounted sensors—a review of classification techniques (2009, methodology): “A similar approach was used by Bussmann et al (2001) who defined a 21 dimensional feature space using data derived features from three different accelerometers,.”
Activity Recognition from User-Annotated Acceleration Data (2004, background): “Activity recognition has been performed on acceleration data collected from the hip (e.g. [17, 19]) and from multiple locations on the body (e.g. [5, 14]).”