The Survey of Automatic Following Methods of Lower Limb Rehabilitation Robot based on Multi-Source Information Fusion

Feng Wei, Zhaohui Luo, Dongnan Su, Jipeng Wu, Delong Yang, Peng Shang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

For some patients with lower limb mobility, lower limb rehabilitation technology could effectively assist patients to walk and reduce their difficulties in the process of moving. The following method applied to the robot can also provide support to the patient in time when the patient encounters an unexpected situation. In this paper we mainly introduced the development of following methods and two novel following approaches we are focused on. The first one is autonomous following method with piezoresistive films, the second one is robust following method with UWB and high-precision gyroscope. Then we discussed the probability of research about gait detection with EEG in rehabilitation robot.

Original languageEnglish
Title of host publication2022 4th International Conference on Communications, Information System and Computer Engineering, CISCE 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages554-557
Number of pages4
ISBN (Electronic)9781665498487
DOIs
StatePublished - 2022
Externally publishedYes
Event4th International Conference on Communications, Information System and Computer Engineering, CISCE 2022 - Shenzhen, China
Duration: 27 May 202229 May 2022

Publication series

Name2022 4th International Conference on Communications, Information System and Computer Engineering, CISCE 2022

Conference

Conference4th International Conference on Communications, Information System and Computer Engineering, CISCE 2022
Country/TerritoryChina
CityShenzhen
Period27/05/2229/05/22

Keywords

  • following method
  • gait detection
  • high-precision gyroscope
  • lower limb rehabilitation
  • UWB

Fingerprint

Dive into the research topics of 'The Survey of Automatic Following Methods of Lower Limb Rehabilitation Robot based on Multi-Source Information Fusion'. Together they form a unique fingerprint.

Cite this