Influence of the Antenna Orientation on WiFi-Based Fall Detection Systems
The growing elderly population living independently demands remote systems for health monitoring. Falls are considered recurring fatal events and therefore have become a global health problem. Fall detection systems based on WiFi radio frequency signals still have limitations due to the difficulty o...
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doaj-1b04225dd1484dc7b7b00ed5a22dd3bd2021-08-06T15:31:31ZengMDPI AGSensors1424-82202021-07-01215121512110.3390/s21155121Influence of the Antenna Orientation on WiFi-Based Fall Detection SystemsJorge D. Cardenas0Carlos A. Gutierrez1Ruth Aguilar-Ponce2Facultad de Ciencias, Universidad Autónoma de San Luis Potosí, Av. Chapultepec 1570, Privadas del Pedregal, San Luis Potosí C.P. 78295, MexicoFacultad de Ciencias, Universidad Autónoma de San Luis Potosí, Av. Chapultepec 1570, Privadas del Pedregal, San Luis Potosí C.P. 78295, MexicoFacultad de Ciencias, Universidad Autónoma de San Luis Potosí, Av. Chapultepec 1570, Privadas del Pedregal, San Luis Potosí C.P. 78295, MexicoThe growing elderly population living independently demands remote systems for health monitoring. Falls are considered recurring fatal events and therefore have become a global health problem. Fall detection systems based on WiFi radio frequency signals still have limitations due to the difficulty of differentiating the features of a fall from other similar activities. Additionally, the antenna orientation has not been taking into account as an influencing factor of classification performance. Therefore, we present in this paper an analysis of the classification performance in relation to the antenna orientation and the effects related to polarization and radiation pattern. Furthermore, the implementation of a device-free fall detection platform to collect empirical data on falls is shown. The platform measures the Doppler spectrum of a probe signal to extract the Doppler signatures generated by human movement and whose features can be used to identify falling events. The system explores two antenna polarization: horizontal and vertical. The accuracy reached by horizontal polarization is 92% with a false negative rate of 8%. Vertical polarization achieved 50% accuracy and false negatives rate.https://www.mdpi.com/1424-8220/21/15/5121fall detectiondevice-freeDoppler signaturespolarizationWiFi |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Jorge D. Cardenas Carlos A. Gutierrez Ruth Aguilar-Ponce |
spellingShingle |
Jorge D. Cardenas Carlos A. Gutierrez Ruth Aguilar-Ponce Influence of the Antenna Orientation on WiFi-Based Fall Detection Systems Sensors fall detection device-free Doppler signatures polarization WiFi |
author_facet |
Jorge D. Cardenas Carlos A. Gutierrez Ruth Aguilar-Ponce |
author_sort |
Jorge D. Cardenas |
title |
Influence of the Antenna Orientation on WiFi-Based Fall Detection Systems |
title_short |
Influence of the Antenna Orientation on WiFi-Based Fall Detection Systems |
title_full |
Influence of the Antenna Orientation on WiFi-Based Fall Detection Systems |
title_fullStr |
Influence of the Antenna Orientation on WiFi-Based Fall Detection Systems |
title_full_unstemmed |
Influence of the Antenna Orientation on WiFi-Based Fall Detection Systems |
title_sort |
influence of the antenna orientation on wifi-based fall detection systems |
publisher |
MDPI AG |
series |
Sensors |
issn |
1424-8220 |
publishDate |
2021-07-01 |
description |
The growing elderly population living independently demands remote systems for health monitoring. Falls are considered recurring fatal events and therefore have become a global health problem. Fall detection systems based on WiFi radio frequency signals still have limitations due to the difficulty of differentiating the features of a fall from other similar activities. Additionally, the antenna orientation has not been taking into account as an influencing factor of classification performance. Therefore, we present in this paper an analysis of the classification performance in relation to the antenna orientation and the effects related to polarization and radiation pattern. Furthermore, the implementation of a device-free fall detection platform to collect empirical data on falls is shown. The platform measures the Doppler spectrum of a probe signal to extract the Doppler signatures generated by human movement and whose features can be used to identify falling events. The system explores two antenna polarization: horizontal and vertical. The accuracy reached by horizontal polarization is 92% with a false negative rate of 8%. Vertical polarization achieved 50% accuracy and false negatives rate. |
topic |
fall detection device-free Doppler signatures polarization WiFi |
url |
https://www.mdpi.com/1424-8220/21/15/5121 |
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