Wearable Stress Sensor Monitors Transportation Efficiency

Release time:2017-07-19
source:Sally Ward-Foxton

The French research institute CEA-Leti has developed two new tools intended to provide data on modes of transportation. This includes a wearable stress monitor, in the form of a wristband worn by transport users, and a smartphone app which detects which mode of transportation the person is using and estimates the environmental impact of the user’s decisions.

The stress sensor is the world’s first to be validated both in the laboratory and in real-life experiments, based on proven and reliable experimental protocols, said Stéphanie Riché, head of the Sensors and Systems Lab at CEA-Leti.

"Stress monitoring project announcements are flourishing this last year, but monitoring stress levels with wearable devices is very challenging," Riché said. "The key point is to setup the experimental protocols in a reliable and reproducible manner."

The new stress monitor uses a combination of accelerometer, galvanic skin response and heart rate information to estimate how stressed the user is. The CEA-Leti research focused on signal processing (it is sensor hardware agnostic) and on generating new indicators to track stress levels in real life conditions.

CEA-Leti's Mobility Observer app could be used to educate users on the environmental impact of their transport choices.
CEA-Leti’s Mobility Observer app could be used to educate users on the environmental impact of their transport choices.

Since acquiring reliable biometrics when someone is on the move is extremely difficult, CEA-Leti also researched the characterization of existing wearable sensors in real usage conditions, in order to exclude erroneous or irrelevant data. The researchers also produced a reference database of signals acquired in the laboratory using the well-known Trier Social Stress Test. Based on this database, machine learning algorithms classify different levels of stress.

"We have observed that in advanced society, stressful situations are increasing. We wanted to see how our methodology in terms of signal processing could be leveraged to bring technological ways to help to tackle this new societal problem," Riché said.

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