A Visualisation Driven Training for Vibrotactile Skin Reading

Research output: Contribution to journalArticlepeer-review

Abstract

Vibrotactile skin-reading effectively conveys rich information via vibrotactile patterns, which has gained attention due to recent advancements. However, training to recognize and associate vibrotactile patterns with their meaning is time-consuming and tedious. The conventional training methods use repetitive exposure of the vibrotactile stimuli along with visual and auditory cues of the corresponding symbol. This work proposes a novel visual-based training method to teach users the associations between semantic information and vibrotactile patterns. Our proposed visual explanation training is compared with the conventional training method in a study with 18 participants. Results show that participants achieve a better performance using the new visual explanation training when identifying single English alphabet characters. Moreover, the proposed training also incurred a significantly lower workload (NASA TLX) and was preferred by study participants. The proposed method is thus effective and offers a less stressful form of training users for skin reading.

Original languageEnglish
Pages (from-to)103-108
Number of pages6
JournalIEEE Transactions on Haptics
Volume15
Issue number1
DOIs
Publication statusPublished - 2022

Keywords

  • Actuators
  • Encoding
  • Skin
  • Task analysis
  • Testing
  • Training
  • Visualization
  • haptic display
  • training
  • information interfaces and representation (HCI) information technology and systems
  • technology
  • tactile communication
  • wearable computers
  • haptics
  • human haptics
  • tactile feedback
  • tactile display
  • computer systems organization
  • Computer system implementation
  • haptics technology
  • skin reading

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Computer Science Applications

Fingerprint

Dive into the research topics of 'A Visualisation Driven Training for Vibrotactile Skin Reading'. Together they form a unique fingerprint.

Cite this