NONLINEAR ANALYSIS OF PHYSICAL ACTIVITY PATTERNS TO DISCRMINATE CHRONIC DISEASE STATES

Abstract

INTRODUCTION Daily physical activity is an essential feature of human behavior related to the health status, the functional capacity and the quality of life. A common way to assess physical activity is to measure the quantity of body movement. Notwithstanding the importance of quantitative assessment it does however ignore important features of dynamics of human physical activities. We postulated that under normal healthy conditions the spontaneous physical activity is characterized by a complex temporal organization. A disorder such as chronic pain changes this pattern which becomes more random. Fractal analysis (FA) that estimate self-similarity or temporal long-range correlations, was used to quantify the pattern of physical activity. The derived fractal metrics were able to discriminate physical activity patterns generated from healthy and chronic pain conditions.