title: Classifying work rate from heart rate measurements using an adaptive neuro-fuzzy inference system.
abstract: In a new approach based on adaptive neuro-fuzzy inference systems (ANFIS), field heart rate (HR) measurements were used to classify work rate into four categories: very light, light, moderate, and heavy. Inter-participant variability (physiological and physical differences) was considered. Twenty-eight participants performed Meyer and Flenghi's step-test and a maximal treadmill test, during which heart rate and oxygen consumption (VO2) were measured. Results indicated that heart rate monitoring (HR, HRmax, and HRrest) and body weight are significant variables for classifying work rate. The ANFIS classifier showed superior sensitivity, specificity, and accuracy compared to current practice using established work rate categories based on percent heart rate reserve (%HRR). The ANFIS classifier showed an overall 29.6% difference in classification accuracy and a good balance between sensitivity (90.7%) and specificity (95.2%) on average. With its ease of implementation and variable measurement, the ANFIS classifier shows potential for widespread use by practitioners for work rate assessment.
authors: Department of Systems Engineering, King Fahd University of Petroleum & Minerals, Dhahran, Saudi Arabia. Electronic address: akolus@kfupm.edu.sa.
authors: Ahmet
authors: A
authors: Kolus
authors: Department of Mathematics and Industrial Engineering, Polytechnique Montréal, Montréal, Canada.
authors: Daniel
authors: D
authors: Imbeau
authors: Department of Mathematics and Industrial Engineering, Polytechnique Montréal, Montréal, Canada.
authors: Philippe-Antoine
authors: PA
authors: Dubé
authors: Direction de la recherche forestière, Ministère des Forêts, de la Faune et des Parcs, Québec, Canada.
authors: Denise
authors: D
authors: Dubeau
mesh_terms: D000328:Adult; D001835:Body Weight; D004734:Energy Metabolism / Q000502:physiology; D017143:Fuzzy Logic; D064368:Healthy Volunteers; D006339:Heart Rate / Q000502:physiology*; D006801:Humans; D008297:Male; D008875:Middle Aged; D009043:Motor Activity / Q000502:physiology; D016571:Neural Networks, Computer; D015588:Observer Variation; D010101:Oxygen Consumption / Q000502:physiology; D005082:Physical Exertion; D012680:Sensitivity and Specificity; D013647:Task Performance and Analysis; D014937:Work / Q000502:physiology*; D055815:Young Adult
keywords: Adaptive neuro-fuzzy inference system (ANFIS); Heart rate; Work rate