IMU-Based Fitness Activity Recognition Using CNNs for Time Series Classification
Philipp Niklas Müller,
Alexander Josef Müller,
Philipp Achenbach
et al.
Abstract:Augmented reality (AR) provides an opportunity for mobile fitness applications to show users real-time feedback on their current fitness activity. For such applications, it is essential to accurately track the user’s current fitness activity using available mobile sensors, such as inertial measurement units (IMUs). Convolutional neural networks (CNNs) have been shown to produce strong results in different time series classification tasks, including the recognition of activities of daily living. However, fitnes… Show more
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