Distance Measurement with Smartphone using Acceleration Model of Hand Movement

The method of double integration, of the acceleration signals; was used in this paper to obtain the displacement position of a device. Although, it evolved from measuring a plain slide of an object to find its position by detecting signals from the step movements (called gait analysis), measuring distance for a slow translation still has no viable solution. This paper proposed a novel method of modeling the behavior of a person’s hand movement using double integration to get the distance of displacement instead of using raw acceleration. The method also made use of the hand movement model in order to self-calibrate its acceleration without doing any additional steps and utilized genetic algorithm to generate the hand’s movement model. The raw acceleration of the hand’s movement calibrated initially using acceleration-time graph analysis, and also uses the modified version of peak detection based on a moving average to obtain the constraints for genetic algorithm. The fitness function was determined by the least error value of the hand’s movement models’ equation compared to the raw acceleration value. Although, the obtained experiment results showed the method was able to provide satisfactory accuracy in finding displacement, some conditions had to be met in order to determine the correct hand’s movement model.