Abstruct-Rehabilitation treatment may be improved by objective analysis of activities of daily living. For this reason, the feasibility of distinguishing several static and dynamic activities (standing, sitting, lying, walking, ascending stairs, descending stairs, cycling) using a small set of two or three uniaxial accelerometers mounted on the body was investigated. The accelerometer signals can be measured with a portable data acquisition system, which potentially makes it possible to perform online detection of static and dynamic activities in the home environment. However, the procedures described in this paper have yet to be evaluated in the home environment. Experiments were conducted on ten healthy subjects, with accelerometers mounted on several positions and orientations on the body, performing static and dynamic activities according to a fixed protocol. Specifically, accelerometers on the sternum and thigh were evaluated. These accelerometers were oriented in the sagittal plane, perpendicular to the long axis of the segment (tangential), or along this axis (radial). First, discrimination between the static or dynamic character of activities was investigated. This appeared to be feasible using an rms-detector applied on the signal of one sensor tangentially mounted on the thigh. Second, the distinction between static activities was investigated. Standing, sitting, lying supine, on a side and prone could be distinguished by observing the static signals of two accelerometers, one mounted tangentially on the thigh, and the second mounted radially on the sternum. Third, the distinction between the cyclical dynamic activities walking, stair ascent, stair descent and cycling was investigated. The discriminating potentials of several features of the accelerometer signals were assessed: the mean value, the standard deviation, the cycle time and the morphology. Signal morphology was expressed by the maximal cross-correlation coefficients with template signals for the different dynamic activities. The mean signal values and signal morphology of accelerometers mounted tangentially on the thigh and the sternum appeared to contribute to the discrimination of dynamic activities with varying detection performances. The standard deviation of the signal and the cycle time were primarily related to the speed of the dynamic activities, and did not contribute to the discrimination of the activities. Therefore, discrimination of dynamic activities on the basis of the combined evaluation of the mean signal value and signal morphology is proposed.

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BackgroundPhysical function is a crucial factor in the prevention and treatment of health conditions in older adults and is usually measured objectively with physical performance tests and/or physical activity monitoring.ObjectiveTo examine whether 1) physical performance (PP) and physical activity (PA) constitute separate domains of physical function; 2) differentiation of PA classes is more informative than overall PA.DesignCross-sectional study to explore the relationships within and among PP and PA measures.MethodsIn 49 older participants (83±7 years; M±SD), performance-based tests were conducted and PA was measured for one week. Activity monitor data were reduced in terms of duration, periods, and mean duration of periods of lying, sitting, standing and locomotion. The relation between and within PP scores and PA outcomes were analysed using rank order correlation and factor analysis.ResultsFactor structure after varimax rotation revealed two orthogonal factors explaining 78% of the variance in the data: one comprising all PA variables and one comprising all PP variables. PP scores correlated moderately with PA in daily life. Differentiation of activity types and quantification of their duration, intensity and frequency of occurrence provided stronger associations with PP, as compared to a single measure of acceleration expressing overall PA.LimitationsFor independent validation, the conclusions about the validity of the presented conceptual framework and its clinical implications need to be confirmed in other studies.ConclusionsPP and PA represent associated but separate domains of physical function, suggesting that an improvement of PP does not automatically imply an increase of PA, i.e. a change to a more active lifestyle. Differentiation of activity classes in the analysis of PA provides more insights into PA and its association with PP than using a single overall measure of acceleration.

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