A novel algorithm to detect non-wear time from raw accelerometer data using deep convolutional neural networks
Abstract To date, non-wear detection algorithms commonly employ a 30, 60, or even 90 mins interval or window in which acceleration values need to be below a threshold value. A major drawback of such intervals is that they need to be long enough to prevent false positives (type I errors), while short...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Publishing Group
2021-04-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-021-87757-z |