Hannu Kinnunen

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— Automatic recognition of activities using time series data collected from exercise can facilitate development of applications that motivate people to exercise more frequently and actively. This article presents a method for recognizing nine different everyday sport activities, such as running, walking, aerobics and Nordic walking, using only(More)
—The study concentrates on tracking swimming exercises based on the data of 3D accelerometer and shows that human activities can be tracked accurately using low sampling rates. The tracking of swimming exercise is done in three phases: first the swimming style and turns are recognized, secondly the number of strokes are counted and thirdly the intensity of(More)
This paper introduces a novel algorithm for estimating energy expenditure during physical activity. The estimation is based on acceleration data measured from a wrist-worn accelerometer. Simultaneous measurements of acceleration and oxygen consumption using a biaxial accelerometer and a breath gas analyzer were made during four different activities:(More)
This article presents an approach to estimating exercise energy expenditure based on acceleration measurements from a wrist-worn biaxial sensor. The method uses the linear mixed model that makes it possible to model both between-subject and within-subject variation in energy expenditure. More precisely, a random-intercepts model is used. The variance and(More)
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