Monitoring of cigarette smoking using wearable sensors and support vector machines.
Cigarette smoking is a serious risk factor for cancer, cardiovascular, and pulmonary diseases. Current methods of monitoring of cigarette smoking habits rely on various forms of self-report that are prone to errors and under reporting. This paper presents a first step in the development of a methodology for accurate and objective assessment of smoking using noninvasive wearable sensors (Personal Automatic Cigarette Tracker-PACT) by demonstrating feasibility of automatic recognition of smoke inhalations from signals arising from continuous monitoring of breathing and hand-to-mouth gestures by support vector machine classifiers. The performance of subject-dependent (individually calibrated) models was compared to performance of subject-independent (group) classification models. The models were trained and validated on a dataset collected from 20 subjects performing 12 different activities representative of everyday living (total duration 19.5 h or 21,411 breath cycles). Precision and recall were used as the accuracy metrics. Group models obtained 87% and 80% of average precision and recall, respectively. Individual models resulted in 90% of average precision and recall, indicating a significant presence of individual traits in signal patterns. These results suggest the feasibility of monitoring cigarette smoking by means of a wearable and noninvasive sensor system in free living conditions.
Department of Electrical and Computer Engineering, the University of Alabama, Tuscaloosa, AL 35487, USA. p.lopezmeyer@ua.edu
Paulo
P
Lopez-Meyer
Stephen
S
Tiffany
Yogendra
Y
Patil
Edward
E
Sazonov
D056044:Actigraphy / Q000295:instrumentation* / Q000379:methods; D000465:Algorithms; D003020:Clothing; D004867:Equipment Design; D019544:Equipment Failure Analysis; D005260:Female; D006801:Humans; D016247:Information Storage and Retrieval; D008297:Male; D018670:Monitoring, Ambulatory / Q000295:instrumentation*; D010992:Plethysmography, Impedance / Q000295:instrumentation* / Q000379:methods; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012907:Smoking; D060388:Support Vector Machine; D014159:Transducers; D055815:Young Adult