In this paper, for the first time the design of a HW module to eliminate the effect of the gravity acceleration from data acquired from inertial sensors is presented. A new 'hardware friendly' algorithm has been derived from the Rodrigues' rotation formula, which can be implemented in a more compact iterative structure. By exploiting 32-bit floating-point arithmetic, the design is able to combine high accuracy and low power requirements needed by any intelligent Human Activity Recognition system, based on artificial neural networks. Synthesis with 65 nm CMOS std cells returns a power dissipation below 2 μ W and an area of about 0.05 mm2, Results are the current state-of-the-art for this kind of system and they are very promising for the future integration in smart sensors for wearable applications.
Low-power Design of a Gravity Rotation Module for HAR Systems Based on Inertial Sensors
DE VITA, ANTONIO
;LICCIARDO, Gian Domenico;DI BENEDETTO, Luigi;
2018
Abstract
In this paper, for the first time the design of a HW module to eliminate the effect of the gravity acceleration from data acquired from inertial sensors is presented. A new 'hardware friendly' algorithm has been derived from the Rodrigues' rotation formula, which can be implemented in a more compact iterative structure. By exploiting 32-bit floating-point arithmetic, the design is able to combine high accuracy and low power requirements needed by any intelligent Human Activity Recognition system, based on artificial neural networks. Synthesis with 65 nm CMOS std cells returns a power dissipation below 2 μ W and an area of about 0.05 mm2, Results are the current state-of-the-art for this kind of system and they are very promising for the future integration in smart sensors for wearable applications.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
