Characterization of Physical Activity in COPD Patients: Validation of a Robust Algorithm for Actigraphic Measurements in Living Situations

Abstract

We have developed robust embedded algorithms for the real-time classification of activity detected by our wearable inertial device. We collected 224 h of accelerometric signals from 28 subjects [22 suffering from chronic obstructive pulmonary disease (COPD)] to develop and then evaluate our algorithms. We describe the process for determining the most robust parameters of the algorithms. Our results with COPD patients show the feasibility of conducting real-time classification of their activities in everyday situations, with high fidelity.