Gigot Vincent, Van Wymelbeke Virginie, Laroche Davy, Mouillot Thomas, Jacquin-Piques Agnès, Rossé Matthieu, Tavan Michel, Brondel Laurent
Taste and Food Behavior Center (CSGA), UMR 6265 CNRS, UMR 1324 INRA, University of Burgundy, Dijon, France.
Department of Geriatrics, University Hospital of Dijon, Dijon, France.
Gait Posture. 2016 Jul;48:202-208. doi: 10.1016/j.gaitpost.2016.04.013. Epub 2016 Jun 7.
To accurately quantify the cost of physical activity and to evaluate the different components of energy expenditure in humans, it is necessary to evaluate external mechanical work (WEXT). Large platform systems surpass other currently used techniques. Here, we describe a calculation method for force-platforms to calculate long-term WEXT.
Each force-platform (2.46×1.60m and 3.80×2.48m) rests on 4 piezoelectric sensors. During long periods of recording, a drift in the speed of displacement of the center of mass (necessary to calculate WEXT) is generated. To suppress this drift, wavelet decomposition is used to low-pass filter the source signal. By using wavelet decomposition coefficients, the source signal can be recovered. To check the validity of WEXT calculations after signal processing, an oscillating pendulum system was first used; then, 10 healthy subjects performed a standardized exercise (squatting exercise). A medical application is also reported in eight Parkinsonian patients during the timed "get-up and go" test and compared with the same test in ten healthy subjects.
Values of WEXT with the oscillating pendulum showed that the system was accurate and reliable. During the squatting exercise, the average measured WEXT was 0.4% lower than theoretical work. WEXT and mechanical work efficiency during the "get-up and go" test in Parkinson's disease patients in comparison with that of healthy subjects were very coherent.
This method has numerous applications for studying physical activity and mechanical work efficiency in physiological and pathological conditions.