You may want to watch your step when you enter an airport.
Everyone walks slightly differently and scientists are developing technology that identifies criminals by looking at their gait.
This system – which is a type behavioural biometric – could soon work in airports just like fingerprinting and eye-scanning technology.
This non-intrusive technique, which uses pressure pads built into the floor of an airport, is around 99.3 per cent accurate at identifying people.
The way people walk could be used as identification at the airport instead of fingerprinting and eye-scanning, according to scientists (stock image)
Physical biometrics, such as fingerprints, facial recognition and retinal scans, are currently more commonly used for security purposes.
However, behavioural biometrics – which include things like how you walk, your voice and your signature – are able to capture unique things about a person’s behaviour and movement.
Researchers from the University of Manchester and the Universidad Autónoma de Madrid in Spain have created a system that looks at a person’s gait rather than the footprint shape itself.
To create the AI system researchers collected the largest footstep database in history, containing nearly 20,000 footstep signals from 127 different individuals.
The study, published in the journal IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), found that monitoring these movements could be used to accurately identify people.
‘Each human has approximately 24 different factors and movements when walking, resulting in every individual person having a unique, singular walking pattern’, said lead researcher Mr Omar Costilla Reyes from Manchester’s School of School of Electrical and Electronic Engineering.
‘Therefore monitoring these movements can be used, like a fingerprint or retinal scan, to recognise and clearly identify or verify an individual’.
Researchers tested their data in real-world security scenarios, including airport security checkpoints, the workplace and home environment.
To create the AI system researchers collected the largest footstep database in history, containing nearly 20,000 footstep signals from 127 different individuals (stock image)
To compile the samples and dataset the team used floor-only sensors and high-resolution cameras.
‘Focusing on non-intrusive gait recognition by monitoring the force exerted on the floor during a footstep is very challenging’, said Mr Reyes.
‘That’s because distinguishing between the subtle variations from person to person is extremely difficult to define manually, that is why we had to come up with a novel AI system to solve this challenge from a new perspective’, he said.
Other applications for the technology include smart steps that could recognise neuro-degeneration.
This is another area that Mr Reyes intends to advance his research with footstep recognition.
‘The research is also being developed to address the healthcare problem of markers for cognitive decline and onset of mental illness, by using raw footstep data from a wide-area floor sensor deployable in smart dwellings’, he said.
‘Human movement can be a novel biomarker of cognitive decline, which can be explored like never before with novel AI systems’.