Assistive game controller for artificial intelligence-enhanced telerehabilitation post-stroke

Grigore Burdea, Nam Kim, Kevin Polistico, Ashwin Kadaru, Namrata Grampurohit, Doru Roll, Frank Damiani

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

Off-the-shelf gaming technology is designed for young, fit, and motor intact individuals. Artificial intelligence (AI) has a role in making controllers and therapeutic games adaptable to the disabled. Post-stroke rehabilitation outcomes can be enhanced by gaming technology within the home to enable engaging telerehabilitation. BrightBrainer™ Grasp (BBG) is a novel therapeutic game controller designed to adapt to arm and hand impairments post-stroke. It mediates intensive arm reach, grasp and finger extension training and has the ability to track relevant outcomes. The newly designed controller uses BrightBrainer gamification system with AI technology to provide automatic adaptation, requiring minimal clinician input. This article describes the BBG design, hardware, force and movement detection and calibration, and its integration with the therapeutic games. The use of AI in adapting a library of custom therapeutic games is also described. Results of a usability study with healthy individuals and related design modifications are presented, with implications for future trials.

Original languageEnglish (US)
Pages (from-to)117-128
Number of pages12
JournalAssistive Technology
Volume33
Issue number3
DOIs
StatePublished - 2021
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Physical Therapy, Sports Therapy and Rehabilitation
  • Rehabilitation

Keywords

  • BrightBrainer
  • BrightBrainer Grasp
  • artificial intelligence
  • stroke
  • telerehabilitation
  • therapeutic games
  • usability evaluation

Fingerprint

Dive into the research topics of 'Assistive game controller for artificial intelligence-enhanced telerehabilitation post-stroke'. Together they form a unique fingerprint.

Cite this