Literature DB >> 30047892

LIDAR Assist Spatial Sensing for the Visually Impaired and Performance Analysis.

Carolyn Ton, Abdelmalak Omar, Vitaliy Szedenko, Viet Hung Tran, Alina Aftab, Fabiana Perla, Michael J Bernstein, Yi Yang.   

Abstract

Echolocation enables people with impaired or no vision to comprehend the surrounding spatial information through the reflected sound. However, this technique often requires substantial training, and the accuracy of echolocation is subject to various conditions. Furthermore, the individuals who practice this sensing method must simultaneously generate the sound and process the received audio information. This paper proposes and evaluates a proof-of-concept light detection and ranging (LIDAR) assist spatial sensing (LASS) system, which intends to overcome these restrictions by obtaining the spatial information of the user's surroundings through a LIDAR sensor and translating the spatial information into the stereo sound of various pitches. The stereo sound of relative pitch represents the information regarding objects' angular orientation and horizontal distance, respectively, thus granting visually impaired users an enhanced spatial perception of his or her surrounding areas and potential obstacles. This paper is divided into two phases: Phase I is to engineer the hardware and software of the LASS system and Phase II focuses on the system efficacy study. The study, approved by the Penn State Institutional Review Board, included 18 student volunteers, who were recruited through the Penn State Department of Psychology Subject Pool. This paper demonstrates that the blindfolded individuals equipped with the LASS system are able to quantitatively identify the surrounding obstacles, differentiate their relative distance, and distinguish the angular location of multiple objects with minimal training.

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Year:  2018        PMID: 30047892     DOI: 10.1109/TNSRE.2018.2859800

Source DB:  PubMed          Journal:  IEEE Trans Neural Syst Rehabil Eng        ISSN: 1534-4320            Impact factor:   3.802


  2 in total

1.  Efficient Multi-Object Detection and Smart Navigation Using Artificial Intelligence for Visually Impaired People.

Authors:  Rakesh Chandra Joshi; Saumya Yadav; Malay Kishore Dutta; Carlos M Travieso-Gonzalez
Journal:  Entropy (Basel)       Date:  2020-08-27       Impact factor: 2.524

2.  Human Posture Detection Method Based on Wearable Devices.

Authors:  Xiaoou Li; Zhiyong Zhou; Jiajia Wu; Yichao Xiong
Journal:  J Healthc Eng       Date:  2021-03-24       Impact factor: 2.682

  2 in total

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