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Related Concept Videos

Brain Imaging01:14

Brain Imaging

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Brain imaging technologies provide critical insights into both the structure and function of the human brain, enabling medical professionals and researchers to diagnose, study, and treat neurological disorders or psychiatric disorders more effectively.
These technologies include computerized axial tomography (CAT or CT scans), positron-emission tomography (PET scans),  magnetic resonance imaging (MRI),  functional magnetic resonance imaging (fMRI), and Transcranial Magnetic...
824

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Related Experiment Video

Updated: Mar 6, 2026

Author Spotlight: Using Motor Imagery Brain-Computer Interface to Improve Motor and Cognitive Function in Stroke Patients
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Fun cube based brain gym cognitive function assessment system.

Tao Zhang1, Chung-Chih Lin2, Tsang-Chu Yu2

  • 1School of Electronic and Information Engineering, Tianjin University, Tianjin, China.

Computers in Biology and Medicine
|March 20, 2017
PubMed
Summary
This summary is machine-generated.

This study developed a fun cube (FC) based brain gym (BG) system for cognitive function assessment. The system accurately screens mild cognitive impairment in the elderly, showing high user acceptance and significant differences between groups.

Keywords:
Brain gymCognitive function impairmentFun cubeMultimediaWireless sensor network

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Area of Science:

  • Gerontology
  • Biomedical Engineering
  • Human-Computer Interaction

Background:

  • Mild cognitive impairment (MCI) poses a growing challenge for healthcare systems.
  • Traditional cognitive assessments can be time-consuming and lack engagement.
  • Developing innovative, accessible tools for early detection is crucial.

Purpose of the Study:

  • To design and develop an engaging Fun Cube (FC) based Brain Gym (BG) system for cognitive function assessment.
  • To utilize wireless sensor networks and multimedia technologies for data collection and analysis.
  • To assist caregivers in screening high-risk elderly individuals for MCI.

Main Methods:

  • Development of an interactive system with FCs, a workstation, and a BG information management system.
  • Integration of a feedback system for cognitive function analysis.
  • Evaluation through experiments involving 31 elderly subjects, comparing results with the Montreal Cognitive Assessment (MoCA).

Main Results:

  • The FC-based BG system demonstrated a strong correlation (Pearson's r=0.83) with MoCA scores.
  • Elderly subjects reported high acceptance (TAM2 score ≈ 6), finding the games engaging and the interface user-friendly.
  • Statistically significant differences were observed between control and MCI groups in game accuracy and completion time across various cognitive tasks.

Conclusions:

  • The developed FC-based BG system is a viable tool for cognitive function assessment in the elderly.
  • The system shows potential for early MCI screening, offering an engaging and user-friendly experience.
  • Further research can explore its integration into routine geriatric care and rehabilitation programs.