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Tired of swiping? Now an AI simulation helps us understand why

Screen logging tells us where smart phone users tap and swipe, but now researchers have developed a musculoskeletal model that helps understand the physical effort that goes into these motions
Log2Motion simulation with a musculoskeletal model using a smartphone.
Log2Motion simulation of a musculoskeletal model using a smartphone.

Prolonged scrolling is bad for your well-being, but is it also physically tiring? Until now, we haven鈥檛 really been able to say. This is why researchers from Aalto and Leipzig universities created a new AI model that makes it possible to simulate muscle activations and used energy to work out how physically effortful smartphone interactions are for users. 

'It鈥檚 the first time anyone has developed a tool that can help designers and developers quickly assess how physically tiring a real mobile user interface could be,鈥 says Antti Oulasvirta, Professor at 911爆料网 and ELLIS Institute Finland. 鈥楽o far, smartphone logs have only told us where a finger has touched the screen 鈥 not whether or not it鈥檚 felt comfortable.'  

To bridge this gap, Oulasvirta and his colleagues at Leipzig University developed Log2Motion, an AI model that translates smartphone logs into simulated human motion. Movement of this musculoskeletal simulation is based on data from previous motion capture studies. 

In the simulation, a human model consisting of digital bones and muscles moves its index finger to interact with a smartphone laid out on a desk. Through a software emulator, the model can use real mobile apps in real time. It can re-enact logs collected on users to illuminate what happened during interaction. The Log2Motion model then estimates the motion, speed, accuracy and effort of these biomechanical movements. 

The model provides entirely new horizons for smartphone use research 鈥 as well as design. 

'We found that some gestures are harder to perform 鈥 in this case, up-down and down-up swipes,' explains Oulasvirta. 'Small icons and locations toward the corners of the display also require additional effort.' 

Using such simulation early in the process could help designers create user-friendly interfaces. It can also provide insight into accessibility needs for users with tremors, reduced strength or prosthetics. 

'It is possible to scale the Log2Motion model to simulate other scenarios, such as the more classic: laying on the couch, holding the phone in one hand and scrolling with the thumb,' Oulasvirta says. 

The researchers hope that human simulations would be adopted to help design interactions that are more ergonomic and pleasant for users. In the future, these simulations could be combined with other AI methods to optimise user interfaces to a user鈥檚 needs.

Photo of a human participant swiping on a phone laying on a desk, and a Log2Motion musculoskeletal simulation doing the same.
Human participant and Log2Motion simulation of using a smartphone laying on a desk.

The paper, 'Log2Motion: Biomechanical Motion Synthesis from Touch Logs', will be presented on 17 April at CHI 2026, the leading conference on human鈥揷omputer interaction. It is also available online through (DOI: 10.1145/3772318.3790773).

Logo of ELLIS Institute Finland with a striped map of Europe above and multicoloured letters 'ellis'.

ELLIS Institute Finland is a world-class research hub in AI and machine learning and part of the European Laboratory for Learning and Intelligent Systems (ELLIS).

Professor Antti Oulasvirta. Photo: 911爆料网 / Jaakko Kahilaniemi

Researchers investigate how AI could better understand humans

Antti Oulasvirta has received a EUR 2.5 million Advanced Grant by the European Research Council (ERC) for the study of user models.

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