The 2008 Physical Activity Guidelines for Americans recommends that all adults perform muscle-strengthening exercises to work all of the major muscle groups of the body on at least two days per week, in addition to aerobic activity. Studies using objective methods of monitoring physical activity have focused primarily on the assessment of aerobic activity. To date, a method for assessing resistance training (RT) exercises has not been developed using a wrist worn activity monitor. Purpose: The purpose of this study was to examine the use of a wrist-worn, tri-axial accelerometer-based activity monitor for classifying upper- and lower-body dumbbell RT exercises. Methods: Sixty participants performed 10 repetitions each of 12 different upper and lower body dynamic dumbbell exercises. Algorithms for classifying the exercises were developed using two different methods: support vector machine (SVM) and cosine similarity. Confusion matrices were developed for each method and inter-method reliability were assessed using Cohen's kappa. A repeated measures ANOVA was used to compare the predicted repetitions, identified from the largest acceleration peaks, with the actual repetitions. Results: The results indicated that SVM and cosine similarity accurately classified the 12 different RT exercises 78% and 85% of the time, respectively. Both methods struggled to correctly differentiate bench press vs shoulder press and squat vs walking lunges. Repetition estimates were not significantly different for 8 of the 12 exercises. For the four exercises that were significantly different, the differences amounts to less than 10%. Conclusion: This study demonstrated that RT exercises can be accurately classified using a single activity monitor worn on the wrist. (C) 2016 American College of Sports Medicine
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