TY  - JOUR
PY  - 2013//
TI  - Improvement of acoustic fall detection using Kinect depth sensing
JO  - Conference proceedings - IEEE engineering in medicine and biology society
A1  - Li, Yun
A1  - Banerjee, Tanvi
A1  - Popescu, Mihail
A1  - Skubic, Marjorie
SP  - 6736
EP  - 6739
VL  - 2013
IS  - 
N2  - The latest acoustic fall detection system (acoustic FADE) has achieved encouraging results on real-world dataset. However, the acoustic FADE device is difficult to be deployed in real environment due to its large size. In addition, the estimation accuracy of sound source localization (SSL) and direction of arrival (DOA) becomes much lower in multi-interference environment, which will potentially result in the distortion of the source signal using beamforming (BF). Microsoft Kinect is used in this paper to address these issues by measuring source position using the depth sensor. We employ robust minimum variance distortionless response (MVDR) adaptive BF (ABF) to take advantage of well-estimated source position for acoustic FADE. A significant reduction of false alarms and improvement of detection rate are both achieved using the proposed fusion strategy on real-world data.<p />  <p>Language: en</p>
LA  - en
SN  - 1557-170X
UR  - http://dx.doi.org/10.1109/EMBC.2013.6611102
ID  - ref1
ER  -