A generalizable orientation-invariant framework for eating episode detection from wrist accelerometers with an acc2gyro module for acc-only settings, externally validated on CAD, Capture-24, and Physio-ED datasets with F1 scores of 0.751, 0.592, and 0.793.
Top-down detection of eating episodes by analyzing large windows of wrist motion using a convolutional neural network,
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Generalizable framework of eating episode detection on free-living wrist-worn wearable data
A generalizable orientation-invariant framework for eating episode detection from wrist accelerometers with an acc2gyro module for acc-only settings, externally validated on CAD, Capture-24, and Physio-ED datasets with F1 scores of 0.751, 0.592, and 0.793.