Advances in Automation Technologies for Lower-extremity Neurorehabilitation

A Review and Future Challenges

Wenhao Deng, Ioannis Papavasileiou, Zhi Qiao, Wenlong Zhang, Kam Yiu Lam, Han Song

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

The world is experiencing an unprecedented, enduring, and pervasive aging process. With more people who need walking assistance, the demand for lower-extremity gait rehabilitation has increased rapidly over the years. The current clinical gait rehabilitative training requires heavy involvement of both medical doctors and physical therapists and thus are labor-intensive, subjective and expensive. To address these problems, advanced automation techniques, especially along with the proliferation of smart sensing and actuation devices and big data analytics platforms, have been introduced into this field to make the gait rehabilitation convenient, efficient, and personalized. This survey paper provides a comprehensive review on recent technological advances in wearable sensors, biofeedback devices and assistive robots. Empowered by the emerging networking and computing technologies in the big data era, these devices are interconnected into smart and connected rehabilitation systems to provide non-intrusive and continuous monitoring of physical and neurological conditions of the patients, perform complex gait analysis and diagnosis, and allow real-time decision making, biofeedback, and control of assistive robots. For each technology category, a detailed comparison among the existing solutions is provided. A thorough discussion is presented on remaining open problems and future directions to further improve the safety, efficiency and usability of the technologies.

Original languageEnglish (US)
JournalIEEE Reviews in Biomedical Engineering
DOIs
StateAccepted/In press - May 3 2018
Externally publishedYes

Fingerprint

Patient rehabilitation
Biofeedback
Automation
Robots
Gait analysis
Aging of materials
Decision making
Personnel
Monitoring
Big data
Wearable sensors

Keywords

  • assistive robots
  • big data analytics platforms
  • biofeedback
  • disease diagnosis and analysis
  • gait quantification
  • Lower-extremity neurorehabilitation
  • wearable sensors

ASJC Scopus subject areas

  • Biomedical Engineering

Cite this

Advances in Automation Technologies for Lower-extremity Neurorehabilitation : A Review and Future Challenges. / Deng, Wenhao; Papavasileiou, Ioannis; Qiao, Zhi; Zhang, Wenlong; Lam, Kam Yiu; Song, Han.

In: IEEE Reviews in Biomedical Engineering, 03.05.2018.

Research output: Contribution to journalArticle

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