Demo Abstract: EMeasure: Using a Smart Device with Consumer-Grade Accelerometer as an Accurate Measuring Scale

Abstract

Calculating accurate distance from an accelerometer during motion involves integrating its raw data and it has been well-established that when the motion is imparted by humans, consumer-grade MEMS accelerometers are rendered unsuitable for this task due to their high error-profiles even for short-interval applications. This work presents 'EMeasure', a step towards addressing this problem with a completely sensor-agnostic and elegantly accurate error-mitigating model using temporal parameters for modeling the cumulated error in acceleration and velocity, yielding accurate distance. Inherent gravity is removed using a novel latency-free method using a gyroscope. The method has been tested on stand-alone MEMS sensor boards and multiple smart devices, in both phone and wrist-watch form factor with varied IMU sensor sets. Lengths up to 5 m have been measured with a mean measurement error of less than 3 cm. As a demo, we introduce EMeasure as an immensely useful and highly accurate length-measuring utility both on smartphones and smartwatches.