Individual Fitness Program Based on Heart Rate Reflecting Lactate Threshold

Various measurements, such as VO2max, lactate threshold, and maximum heart rate, are employed to optimize training performance. This research proposes a simple method for estimating the lactate threshold which needs a heart rate monitor and a smartphone. The heart rate variations during exercise reflect the cardiovascular fitness of the individual, and are used to predict oxygen consumption (VO), energy expenditure (EE) and respiratory exchange ratio (RER). PURPOSE: To develop the personal training solution based on the heart rate as the indicator of user’s aerobic capability and exercise performance using a wearable smart gear METHODS: In each of subjects aged between 19 and 59 (male: n=56, female: n=57) performed the proposed simple protocol based on the 10 meter shuttle run test and a graded exercise test on a treadmill as golden reference. Heart rate, blood lactate concentration and pulmonary gas exchange were concurrently acquired for determining estimation formulas of lactate threshold and performance indexes for each subject. RESULTS: Correlation analyses have been performed for the data collected during the 10-m shuttle run test and incremental exercise test. The linear regression model showed that the heart rate at lactate threshold was significantly correlated with the inflection point of blood lactate concentration (male: r = 0.75, p < .05; female: r = 0.83, p < .05). The estimation model’s adjusted R2’s for male group (p < .001) and for female group (p < .001) are 0.6 and 0.5 respectively. In addition, the heart rate during aerobic exercise correlated with EE (adjusted R2=0.81, P<.001) and RER (adjusted R2= 0.68, P<.001). Measures of heart rate were positively and significantly correlated VO (adjusted R2 = 0.83, p <.001). These results validated the accumulated heart rate are closely correlated with metabolic responses to individual training program. CONCLUSIONS: Healthcare and fitness is one of the popular categories in mobile application market nowadays. In particular, the ones that connect to external sensors such as heart rate monitor, pedometer, calorie-tracker and so on are dominating the market share. We believe that the performance indexes derived from the accumulated heart rate will more motivate users and will improve the effectiveness of the exercise.