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Artificial Intelligence-Enabled Caregiving Walking Stick Powered by Ultra-Low-Frequency Human Motion

  • Xinge Guo
  • , Tianyiyi He
  • , Zixuan Zhang
  • , Anxin Luo
  • , Fei Wang*
  • , Eldwin J. Ng
  • , Yao Zhu
  • , Huicong Liu
  • , Chengkuo Lee*
  • *Corresponding author for this work
  • National University of Singapore
  • Agency for Science, Technology and Research, Singapore
  • Southern University of Science and Technology
  • Soochow University

Research output: Contribution to journalArticlepeer-review

Abstract

The increasing population of the elderly and motion-impaired people brings a huge challenge to our social system. However, the walking stick as their essential tool has rarely been investigated into its potential capabilities beyond basic physical support, such as activity monitoring, tracing, and accident alert. Here, we report a walking stick powered by ultra-low-frequency human motion and equipped with deep-learning-enabled advanced sensing features to provide a healthcare-monitoring platform for motion-impaired users. A linear-to-rotary structure is designed to achieve highly efficient energy harvesting from the linear motion of a walking stick with ultralow frequency. Besides, two kinds of self-powered triboelectric sensors are proposed and integrated to extract the motion features of the walking stick. Augmented sensing functionalities with high accuracies have been enabled by deep-learning-based data analysis, including identity recognition, disability evaluation, and motion status distinguishing. Furthermore, a self-sustainable Internet of Things (IoT) system with global positioning system tracing and environmental temperature and humidity amenity sensing functions is obtained. Combined with the aforementioned functionalities, this walking stick is demonstrated in various usage scenarios as a caregiver for real-time well-being status and activity monitoring. The caregiving walking stick shows the potential of being an intelligent aid for motion-impaired users to help them live life with adequate autonomy and safety.

Original languageEnglish
Pages (from-to)19054-19069
Number of pages16
JournalACS Nano
Volume15
Issue number12
DOIs
StatePublished - 28 Dec 2021
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • artificial intelligence
  • energy harvesting
  • Internet of Things
  • triboelectric
  • walking stick

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