Flexible, wearable goose bump sensor paves way for emotion detectors

Measuring and quantifying human emotions is getting closer to reality as researchers in South Korea have developed a flexible detector which is able to measure goose bumps.

The tiny sensor can tell when the hairs on the back of your arm stand-up.

In the future, if we are able to record and understand a physical and emotional response to a stimulus, this can help to determine our experiences of music, games and everything we do.

In turn we would be able to measure the times of the day where our emotions change the most.

The sensor, which includes components that are just 1.2 micrometers thick, works in a very simple way as it detects goose bumps, or piloerection, by the deformation of sensor.

It was placed on the arm of a person then was able to detect the change in the skin’s state when a person grabbed some ice cubes.

The researchers at the Korea Advanced Institute of Science and Technology (KAIST) are still some distance away from the sensors being able to detect emotions but the research shows the potential exists to detect changes in our body that are caused by our surroundings.


The researchers think that we may one day treat our emotions like any other bimometric information that can be collected and analysed.

“We found that the height of the goose bump and the piloerection duration can be deduced by analysing obtained capacitance change trace,” explained Young-Ho Cho.

“In the future, human emotions will be regarded like any typical biometric information, including body temperature or blood pressure,” Cho said.

The scientists now hope to make the signal processing module and capacitance measurement system smaller so that it can be put on the skin with the sensor.


A previous flexible wearable sensor built by KAIST

The team of researchers at KAIST in South Korea built the 20mm x 20mm sensor using a conductive polymer called PEDOT:PSS for the capacitors. It is flexible compared to brittle metallic conductive materials.

The small capacitors were then embedded in a silicon substrate.

It isn’t the first piece of flexible wearable technology that KAIST scientists have been looking at.

Others at the organisation have made a tiny generator which is able to gather body heat and in future will be able to power wearable devices.

Featured image courtesy of MaryLane via Flickr/Creative Commons Licence 

Images two and three courtesy of KAIST 

Beyond social media: Face recognition software to diagnose genetic disorders

What if diagnosing rare genetic disorders was as easy as tagging photos on Facebook?

Researchers at Oxford University have created a computer program that uses photo software with face recognition capabilities, similar to those used on social media sites, to discern the likenesses in facial features of people who have the same genetic disorders.

The software can then compare a photograph of the patient to these prominent facial structures and generate a ranked list of possible disorders.

How can a mere photograph provide the basis for a diagnosis? Disorders such as Down’s syndrome, Angelman syndrome and Progeria are caused by genetic mutations that also affect the growth of the face and the cranium as a baby develops, allowing for recognition of characteristic facial features.

Doctors already use the analysis of facial features as part of the way they diagnose patients, but a computer program could reduce the room for error that comes with human judgment.

The computer program, an example of the newest machine learning technology, uses an algorithm that becomes better at knowing which facial features are pertinent to diagnosis with each photograph it processes. It can analyse faces despite differences in lighting, facial expression and photo quality.


Researchers are already noting the algorithm’s effectiveness. Photographs of people with the same disorder are automatically grouped together by the program.

Likewise, the program clusters patients whose facial features are similar but do not match any known diagnosis, a useful tool in the identification of new or extremely uncommon disorders.

The developers of the program foresee a future where face recognition technology aids in the quick diagnosis of a patient. Doctors will be able to snap a picture of the patient on their smartphone, run it through the program, and analyze the results.

One in 17 people have a genetic disorder, but most go undiagnosed. With this new technology, patients could be diagnosed from a younger age, receive treatment earlier and improve their quality of life.


The potential for consistency, speed and accuracy in diagnosis could also help shift research towards treatment and cures for these genetic disorders.

On social media, face recognition technology can seem nothing more than a handy feature that saves you a few minutes when tagging photos. However, innovative applications of the technology we use every day, like this photo software, could put us on track for a fuller understanding of conditions that affect millions of people.