ACUTE Lab
Sensory substitution research
KEMAR mannequin in anechoic chamber
Room acoustics simulation
Prosthetic feedback mannequin
Attention and foraging research
Sound of Vision sensory substitution device
ICT 2018 Sound of Vision Award
ACoUstic and Tactile Engineering · University of Iceland

We decode
the senses —
and put them
to work.

Vibrotactile interfaces. Spatial audio. Room acoustics.
Research that bridges perception science and engineering.

Engineering at the boundary of human perception

ACUTE is an interdisciplinary research group at the University of Iceland. We sit at the intersection of human perception science, engineering design, and applied acoustics.

We collaborate with prosthetics manufacturer Össur ehf., spatial audio company Treble Technologies, and clinicians at Landspítali — National University Hospital. Funded by RANNÍS, NordForsk, and the European Union.

Six interconnected themes

Vibrotactile Perception
01

Vibrotactile Perception

Mapping the frequency, amplitude, and spatial limits of touch on the forearm and wrist.

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Prosthetic Haptic Feedback
02

Prosthetic Haptic Feedback

Vibrotactile sleeves that restore proprioception for transfemoral amputees.

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Sensory Substitution
03

Sensory Substitution

Devices that translate sound and vision into touch for visually and hearing-impaired users.

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Spatial Audio & HRTFs
04

Spatial Audio & HRTFs

Synthetic pinna models and machine learning to personalise 3D sound.

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Room Acoustics Simulation
05

Room Acoustics Simulation

Structure-preserving model reduction achieving 100× speedup in wave simulation.

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Attention, Foraging & Haptic Illusions
06

Attention, Foraging & Haptic Illusions

Cross-modal foraging, visual synchrony effects, and haptic illusions.

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93%Sequential vibrotactile pattern recognition accuracy on forearm 72.4%Sequential vs 42.7% simultaneous accuracy for prosthetic joint feedback ~93%Ceiling accuracy at 240 ms signal duration for prosthetic feedback 92–98%Peak short-pattern accuracy at 300 ms interstimulus interval 95%Vibrotactile discrimination accuracy near wrist & elbow anchors 34 dBIndividual variation range in wrist vibrotactile thresholds 200 HzPeak wrist sensitivity frequency (inner/glabrous skin) 50 dBDynamic range available in the 50–300 Hz band at the inner wrist 30Participants in wrist threshold study across 25–1,000 Hz 14Braille-like patterns tested on a 2×3 actuator forearm array 6Actuators in the forearm vibrotactile display array 4Prosthetic joint positions encoded by the forearm feedback system 826 MPeople worldwide with some form of vision impairment 100×Speedup of reduced-order model vs full-order in room acoustics 3.5×Speedup of the new FOM formulation vs conventional approach 1,513Spatial positions in the Viking HRTF Dataset 20Pinnae in the Viking HRTF dataset 48Individual HRTFs used to train sound-localization AI ~20°Localization error — matching human hearing 3.54%ML prediction error for personalized HRTFs 15Anthropometric parameters used to predict personalized HRTFs 3.3%Pinna notch prediction error — half of prior methods 1,036HRTF measurement positions for synthetic pinna validation 0.25 mmScanner precision for synthetic pinna replication Faster foraging with cross-modal synchrony cues 6×6Grid foraging paradigm with 36 rotating items d = 1.62Effect size for cross-modal cue advantage in foraging 1,800Trials across intensity order illusion experiments 16Participants per experiment in the intensity order illusion study 93%Sequential vibrotactile pattern recognition accuracy on forearm 72.4%Sequential vs 42.7% simultaneous accuracy for prosthetic joint feedback ~93%Ceiling accuracy at 240 ms signal duration for prosthetic feedback 92–98%Peak short-pattern accuracy at 300 ms interstimulus interval 95%Vibrotactile discrimination accuracy near wrist & elbow anchors 34 dBIndividual variation range in wrist vibrotactile thresholds 200 HzPeak wrist sensitivity frequency (inner/glabrous skin) 50 dBDynamic range available in the 50–300 Hz band at the inner wrist 30Participants in wrist threshold study across 25–1,000 Hz 14Braille-like patterns tested on a 2×3 actuator forearm array 6Actuators in the forearm vibrotactile display array 4Prosthetic joint positions encoded by the forearm feedback system 826 MPeople worldwide with some form of vision impairment 100×Speedup of reduced-order model vs full-order in room acoustics 3.5×Speedup of the new FOM formulation vs conventional approach 1,513Spatial positions in the Viking HRTF Dataset 20Pinnae in the Viking HRTF dataset 48Individual HRTFs used to train sound-localization AI ~20°Localization error — matching human hearing 3.54%ML prediction error for personalized HRTFs 15Anthropometric parameters used to predict personalized HRTFs 3.3%Pinna notch prediction error — half of prior methods 1,036HRTF measurement positions for synthetic pinna validation 0.25 mmScanner precision for synthetic pinna replication Faster foraging with cross-modal synchrony cues 6×6Grid foraging paradigm with 36 rotating items d = 1.62Effect size for cross-modal cue advantage in foraging 1,800Trials across intensity order illusion experiments 16Participants per experiment in the intensity order illusion study
Haptic interfaces

Designing touch that speaks

Sequential vibrotactile patterns achieve 93% recognition accuracy on the forearm — nearly four times the 26% seen with simultaneous stimulation. This finding shapes the core programming logic of every wearable device we build.

Yeganeh et al. · Applied Sciences 2024 Read the paper →
Spatial audio

Your ear, rebuilt in silicone

We 3D-scan real pinnae, alter one geometric feature at a time, cast them in silicone, and measure their acoustic fingerprint. This controlled methodology lets us isolate exactly which part of your ear shape determines where you hear sound coming from.

Sumner, Riedel & Unnthorsson · Cogent Engineering 2025 Read the paper →
Room acoustics

100× faster, equally accurate

Our structure-preserving model order reduction compresses the wave equation into a low-dimensional form that runs 100 times faster than a full simulation — without sacrificing stability at complex material boundaries. Built with Treble Technologies.

Bonthu et al. · Int. J. Numerical Methods in Engineering 2026 Read the paper →

Our team

Rúnar Unnþórsson
Rúnar Unnþórsson
Principal Investigator
Árni Kristjánsson
Árni Kristjánsson
Principal Investigator
Ivan Makarov
Ivan Makarov
Postdoctoral Researcher
Nashmin Yeganeh
Nashmin Yeganeh
PhD Candidate
Mohammadmahdi Karimi
Mohammadmahdi Karimi
PhD Candidate
Jonas Karlberg
Jonas Karlberg
PhD Candidate
Satish Kumar Bonthu
Satish Kumar Bonthu
PhD Candidate
Mohammad Karimi
Mohammad Karimi
PhD Candidate
Hafliði Ásgeirsson
Hafliði Ásgeirsson
Lab Manager
Stefanos Vasilakis
Stefanos Vasilakis
R&D Engineer
Emma Shannon
Emma Shannon
E-textiles & Wearables Design

Partners & funders

Research partners
Industry partners
Funders