US 12,311,959 B2
System and method for determining cognitive demand
Andrey Viktorovich Filimonov, Bogorodskiy rayon (RU); Anastasiya Sergeevna Filatova, Nizhegorodskaya oblast (RU); Evgeny Pavlovich Burashnikov, Nizhegorodskaya oblast (RU); Sergey Valeryevich Shishanov, Nizhny Novgorod (RU); Valeriya Alekseevna Demareva, Nizhny Novgorod (RU); Ivan Sergeevich Shishalov, Nizhegorodskaya oblast (RU); Anton Sergeevich Devyatkin, Nizhny Novgorod (RU); Mikhail Sergeevich Sotnikov, Nizhny Novgorod (RU); Anzhela Grigorevna Burova, Nizhny Novgorod (RU); Vladimir Vladimirovich Kilyazov, Nizhegorodskaya Oblast (RU); and Anastasiya Vladimirovna Bakhchina, Nizhegorodskaya oblast (RU)
Assigned to HARMAN BECKER AUTOMOTIVE SYSTEMS GMBH, Karlsbad (DE)
Appl. No. 18/044,882
Filed by Harman Becker Automotive Systems GmbH, Karlsbad-Ittersbach (DE)
PCT Filed Sep. 11, 2020, PCT No. PCT/RU2020/000478
§ 371(c)(1), (2) Date Mar. 10, 2023,
PCT Pub. No. WO2022/055383, PCT Pub. Date Mar. 17, 2022.
Prior Publication US 2023/0339479 A1, Oct. 26, 2023
Int. Cl. B60W 50/00 (2006.01); B60W 40/08 (2012.01); G06V 10/82 (2022.01); G06V 20/59 (2022.01); G06V 40/18 (2022.01)
CPC B60W 50/0098 (2013.01) [B60W 40/08 (2013.01); G06V 10/82 (2022.01); G06V 20/597 (2022.01); G06V 40/18 (2022.01); B60W 2420/403 (2013.01); B60W 2540/22 (2013.01); B60W 2540/221 (2020.02); B60W 2540/225 (2020.02)] 18 Claims
OG exemplary drawing
 
1. Computer-implemented method for determining a cognitive demand level of a user, the method comprising:
recording, as a first training data subset, one or more first biosignals of a user, wherein the first biosignals indicate that the user is occupied with at least one first task;
obtaining, as a second training data subset, information indicative of a cognitive demand that the user is experiencing;
supplying the first training data subset and the second training data subset to an artificial neural network as a training dataset;
training the artificial neural network on the training dataset to determine a cognitive demand level indicative of cognitive demand the user is experiencing;
recording one or more second biosignals of a user of a vehicle as an input dataset;
processing the input dataset by the trained artificial neural network to determine the cognitive demand level indicative of cognitive demand the user is experiencing;
converting the one or more biosignals, after recording the biosignals, into a continuous format indicative of a frequency and/or duration of events per time by applying a time window to the recorded biosignals, the time window being a sliding time window;
determining that the user is experiencing high cognitive demand, if the determined cognitive demand level exceeds a predefined threshold value within a predetermined period; and
determining that the user is not experiencing high cognitive demand, if the determined cognitive demand level is equal to or below the predefined threshold value within the predetermined period.