Human Bipedal Locomotion-based Indoor Location Tracking using Fiber-Optic Sensors

With the aim of promoting independent living and aging well, indoor location tracking has been a research focus in the area of Ambient Assisted Living (AAL) environment. In particular, there has been growing interest in object tracking using fiber-optic sensors due to the advantage of data-efficient, low-computational-cost and non-intrusive. However, the current research on object tracking with fiber-optic sensors confronts several critical challenges, such as increasing the sensing efficiency and limitations of unnatural walking manner. To address these challenges, in this paper, a compressive floor pressure sensing approach is proposed based on human bipedal locomotion(HBL) characteristics. Specifically, to retain the natural characteristic of HBL, the spatio-temporal representation of HBL locations is expressed as a three-state vector by dividing the monitoring area into an 8-neighbour-grid structured environment. The spatial sparsity of HBL locations is then incorporated into compressive sensing mechanism for efficiency enhancement. More specifically, a Triplet Measurement Vector and Dynamic Uniquely Decipherable (TMV-DUD) encoding scheme is used to form the compressive sensing matrix. A prototype system of compressive floor pressure sensing is developed for indoor location tracking within 36 grids using only 5 sensors. The prototype experimental results demonstrate the effectiveness of the proposed compressive tracking approach.