2017
DOI: 10.7236/jiibc.2017.17.2.179
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Applying Hilbert-Huang Transform to Extract Essential Patterns from Hand Accelerometer Data

Abstract: Hand Accelerometers are widely used to detect human motion patterns in real-time. It is essential to reliably identify which type of activity is performed by human subjects. This rests on having accurate template of each activity. Many human activities are represented as a set of multiple time-series data from such sensors, which are mostly non-stationary and non-linear in nature. This requires a method which can effectively extract patterns from non-stationary and non-linear data. To achieve such a goal, we p… Show more

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