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 click here 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 enough to prevent false negatives (type