A wearable stress monitoring device has been developed by Leti that enables customised recommendations to enhance stress-free travel and indicators for improving public transportation safety. Leti scientists will demonstrate this device, and a smartphone-based mobility observer developed in the Horizon 2020 Programme, at the 12th ITS European Conference in Strasbourg, France, 19th-22nd June.
The non-invasive stress monitor is a wristband device designed for truck and train drivers, airline pilots and travellers. It enables:
Using sensors typically integrated into wearable items, Leti’s stress monitor provides real time data fusion processing that automatically estimates each person's stress levels regardless of their activity level. It collects data with an embedded algorithm and several miniaturised sensors like accelerometers, photoplethysmography sensors and electrodermal activity sensors.
The databases for comparing results were built by Leti and the Laboratory of Psychology and NeuroCognition (LPNC) in Grenoble. The collected data is sent anonymously to the cloud where it can be used to improve both safety and comfort for users and, in some cases, for the general public.
For example, transit agencies can collect and analyse passengers’ comfort information and take appropriate actions to eliminate potential problems. If customers experience higher stress than usual while getting off at a specific bus station, e.g. at a dangerous intersection, the agencies could follow up that finding with a study to verify the cause and provide a remedy.
The biofeedback from pilots, truck drivers and train engineers also can be used to improve safety. After graduating from simulators to real equipment during training, wearing the device will signal stress levels and indicate they should return to the simulator for more practice on certain aspects of their complicated jobs.
“Leti researchers continue to pioneer affordable, innovative, smart solutions for users and operators in the global mobility market by fusing sensors, increasing device autonomy and developing crowd sensing functionality,” said Viviane Cattin, Signal for Sensor System Lab manager. “By generating and combining a broad range of data, the Bon Voyage project is offering two technologies for the transportation sector – both providers and travellers.”
The mobility observer differentiates between travel modes such as buses and motorbikes, trains and trams by preserving device autonomy. The goals are to automate such surveying and reduce costs for collecting and analysing data, and improve transportation access and services. The new connectivity features in the mobility observer enables officials to take into account a large amount of data vs. data collected on single individuals.