Repository logo

Infoscience

  • English
  • French
Log In
Logo EPFL, École polytechnique fédérale de Lausanne

Infoscience

  • English
  • French
Log In
  1. Home
  2. Academic and Research Output
  3. Conferences, Workshops, Symposiums, and Seminars
  4. Effectiveness of different sensing modalities in predicting targets of reaching movements
 
conference paper not in proceedings

Effectiveness of different sensing modalities in predicting targets of reaching movements

Novak, Domen
•
Omlin, Ximena
•
Lein-Hess, Rebecca
Show more
2013
35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2013)

Human motion recognition is essential for many biomedical applications, but few studies compare the abilities of multiple sensing modalities. This paper thus evaluates the effectiveness of different modalities when predicting targets of human reaching movements. Electroencephalography, electrooculography, camera-based eye tracking, electromyography, hand tracking and the user’s preferences are used to make predictions at different points in time. Prediction accuracies are calculated based on data from 10 subjects in within-subject crossvalidation. Results show that electroencephalography can make predictions before limb motion onset, but its accuracy decreases as the number of potential targets increases. Electromyography and hand tracking give high accuracy, but only after motion onset. Eye tracking is robust and gives high accuracy at limb motion onset. Combining multiple modalities can increase accuracy, though not always. While many studies have evaluated individual sensing modalities, this study provides quantitative data on many modalities at different points of time in a single setting. The information could help biomedical engineers choose the most appropriate equipment for a particular application.

  • Files
  • Details
  • Metrics
Loading...
Thumbnail Image
Name

EMBC13_0258_FI.pdf

Access type

openaccess

Size

554.27 KB

Format

Adobe PDF

Checksum (MD5)

0034a6e7c2c67797aa263ac680f3eb96

Logo EPFL, École polytechnique fédérale de Lausanne
  • Contact
  • infoscience@epfl.ch

  • Follow us on Facebook
  • Follow us on Instagram
  • Follow us on LinkedIn
  • Follow us on X
  • Follow us on Youtube
AccessibilityLegal noticePrivacy policyCookie settingsEnd User AgreementGet helpFeedback

Infoscience is a service managed and provided by the Library and IT Services of EPFL. © EPFL, tous droits réservés