/Neural markers of mid-air haptics for objective user testing & validation

Neural markers of mid-air haptics for objective user testing & validation

PhD - Gent | More than two weeks ago

Implementation of mid-air haptic sensor technology in new innovations (and user experiences), requires new methodologies and fundamental research on objective user metrics of mid-air haptic sensations.

Ultrasound technology can be used to equip smart systems with haptic feedback, giving the user a sense of touch. In the case of mid-air haptics, ultrasonic waves produce a local pressure field causing the user to ‘feel’ a light sensation without touching the object. Such applications require high pressures at low ultrasonic frequencies. Imec has been working on such technology for multiple years and sees opportunities for applications in which touchless and interactive screens are interesting (e.g. automotive and consumer applications).

 

This project is focused on expanding its methodological portfolio to this extent and conduct fundamental research on objective user metrics of mid-air haptic sensations. Previous research in the field of cognitive neuroscience has shown clear neural EEG markers of vibro-tactile stimulation in the somatosensory cortex of the brain, using steady-state somatosensory-evoked potentials oscillating with the same frequency as the vibro-tactile stimulations. In a preliminary study in which EEG signals were recorded while users experienced ultrasound tactile stimulation with the Ultraleap Stratos, a commercial ultrasound device, we saw similar neural markers for mid-air haptics (although much weaker than in vibro-tactile stimulation).

 

In this Imec PhD project, we would like to further explore these neural markers of mid-air haptics because we believe they could be used as objective user experience (UX) metrics when designing new ultrasound transducers within Imec. The PhD student with a background in cognitive neuroscience will do a series of EEG experiments in which the strongest marker and the conditions under which it appears, will be studied. 



Required background: Data science, neuropsychology

Type of work: 20% literature, 40% experimental, 40% data analysis and modeling

Supervisor: Lieven De Marez

Co-supervisor: Klaas Bombeke

Daily advisor: Klaas Bombeke

The reference code for this position is 2024-087. Mention this reference code on your application form.

Who we are
Accept marketing-cookies to view this content.
Cookie settings
imec's cleanroom
Accept marketing-cookies to view this content.
Cookie settings

Send this job to your email