Biosignal processing and activity modeling for multimodal human activity recognition (2021)
Abstract / truncated to 115 words
This dissertation's primary goal was to systematically study human activity recognition and enhance its performance by advancing human activities' sequential modeling based on HMM-based machine learning. Driven by these purposes, this dissertation has the following major contributions: The proposal of our HAR research pipeline that guides the building of a robust wearable end-to-end HAR system and the implementation of the recording and recognition software Activity Signal Kit (ASK) according to the pipeline; Collecting several datasets of multimodal biosignals from over 25 subjects using the self-implemented ASK software and implementing an easy mechanism to segment and annotate the data; The comprehensive research on the offline HAR system based on the recorded datasets and the implementation of ...
human activity recognition – motion units – hidden markov models – pattern recognition – accelerometer – gyroscope – EMG – inertial sensors – wearables – wearable computing – feature selection – big data
Information
- Author
- Liu, Hui
- Institution
- University of Bremen
- Supervisors
- Publication Year
- 2021
- Upload Date
- Dec. 8, 2021
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