Fall Detection in Mobile Applications

new:Dosch Probability Density Model

Today, a reliable Fall Detection integrated in Telecommunication Mobiles is not available, at least not with necessary quality and trustworthiness. Fall Detection as always-on-function must not reduce the battery’s standby time and must be executable with moderate processor performance and memory. The classics as KFD (Kernel-Fisher-Discriminates) which use extraction of properties via Hilbert space are by far to complex and computational intensive for being integrated in the limited available environment of a mobile device. Moreover KFD discriminates do not deliver reliable verdicts “fall detected” in the face of diversity of falls Wanted: Mathematical model and its numeric algorithm which can be integrated in mobile devices (DECT, GSM/LTE) with Ultra Low Power consumption, but even so can work and detect “falls” reliably.

The recently developed DPDM (Dosch Probability Density Model) method can be such candidate. DPDM has been integrated into DECT device DA1432 indPendant™ and subject to numerous field trials.


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