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

• Published in: IEEE journal of biomedical and health informatics Vol. 18; no. 4; pp. 1225 - 1231
• Main Authors: Perriot, Bruno, Argod, Jerome, Pepin, Jean-Louis, Noury, Norbert
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.07.2014; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Acceleration; Accelerometry; Actigraphy - instrumentation; Actigraphy - methods; Actimetry; Activities of Daily Living - classification; Adult; Aged; Algorithms; Biomedical monitoring; Bluetooth; body postures; body sensor network; chronic obstructive pulmonary disease (COPD) patients; Correlation; Feasibility Studies; Female; Humans; Legged locomotion; Male; Middle Aged; Monitoring; Monitoring, Ambulatory - instrumentation; Monitoring, Ambulatory - methods; Posture - physiology; Pulmonary Disease, Chronic Obstructive; ROC Curve; Sensors; Signal Processing, Computer-Assisted; Young Adult
• ISSN: 2168-2194; 2168-2208; 2168-2208
• DOI: 10.1109/JBHI.2013.2282617

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.