@article{ref1,
title="A Kalman filter to estimate altitude change during a fall",
journal="Conference proceedings - IEEE engineering in medicine and biology society",
year="2016",
author="Stevens, Michael C. and Lu, Wei and Wang, Changhong and Redmond, Stephen J. and Lovell, Nigel H. and Stevens, Michael C. and Wei Lu,  and Changhong Wang,  and Redmond, Stephen J. and Lovell, Nigel H. and Wang, Changhong and Lu, Wei and Redmond, Stephen J. and Lovell, Nigel H. and Stevens, Michael C.",
volume="2016",
number="",
pages="5889-5892",
abstract="Barometers have been incorporated into fall detectors in order to enhance the accuracy of fall detection algorithms, however they are power-hungry devices. We present an offline evaluation of a Kalman filter (KF) for estimating the pressure change during a fall that enables low-power operation of the barometer. The KF takes advantage of the fact that a semi-permeable air membrane on a waterproof fall detector enclosure causes a delay in the equilibrium between internal and external enclosure pressure, and this delay enables the barometer to be switched off until a free-fall is detected. We assessed the KF using data obtained from simulated falls and activities of daily living. The KF was able to differentiate between fall and non-fall activities, with the average measured pressure change during a fall of 8 Pa best determined using a delay in pressure equalization of 20 seconds. The KF detected a change in altitude faster than a simple moving average filter (MAF), reaching 66% of its final value before the MAF was able to initialize.<p /> <p>Language: en</p>",
language="en",
issn="1557-170X",
doi="10.1109/EMBC.2016.7592068",
url="http://dx.doi.org/10.1109/EMBC.2016.7592068"
}