Characterization of physical activity in COPD patients: validation of a robust algorithm for actigraphic measurements in living situations.
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.
Bruno
B
Perriot
Jerome
J
Argod
Jean-Louis
JL
Pepin
Norbert
N
Noury
D061725:Accelerometry; D056044:Actigraphy / Q000295:instrumentation / Q000379:methods*; D000203:Activities of Daily Living / Q000145:classification*; D000328:Adult; D000368:Aged; D000465:Algorithms; D005240:Feasibility Studies; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D018670:Monitoring, Ambulatory / Q000295:instrumentation / Q000379:methods*; D011187:Posture / Q000502:physiology; D029424:Pulmonary Disease, Chronic Obstructive; D012372:ROC Curve; D012815:Signal Processing, Computer-Assisted; D055815:Young Adult