US 12,367,979 B2
Method and apparatus for determining dementia risk factors using deep learning
Dong Won Yang, Seoul (KR); Sang Yun Kim, Seongnam-si (KR); Kee Hyung Park, Incheon (KR); Jee Hyang Jeong, Seoul (KR); Seong Hye Choi, Incheon (KR); Yun Jeong Hong, Uijeongbu-si (KR); and Min Jeong Wang, Seongnam-si (KR)
Assigned to THE CATHOLIC UNIVERSITY OF KOREA INDUSTRY-ACADEMIC COOPERATION FOUNDATION, Seoul (KR); Min Jeong Wang, Seongnam-si (KR); GIL MEDICAL CENTER, Incheon (KR); and Inha University Research and Business Foundation, Incheon (KR)
Filed by THE CATHOLIC UNIVERSITY OF KOREA INDUSTRY—ACADEMIC COOPERATION FOUNDATION, Seoul (KR); GIL MEDICAL CENTER, Incheon (KR); Inha University Research and Business Foundation, Incheon (KR); and Min Jeong Wang, Seongnam-si (KR)
Filed on Jul. 21, 2021, as Appl. No. 17/381,564.
Prior Publication US 2023/0023432 A1, Jan. 26, 2023
Int. Cl. G16H 50/20 (2018.01); A61B 5/00 (2006.01); G06N 3/08 (2023.01); G16H 10/60 (2018.01); G16H 15/00 (2018.01)
CPC G16H 50/20 (2018.01) [A61B 5/4088 (2013.01); G06N 3/08 (2013.01); G16H 10/60 (2018.01); G16H 15/00 (2018.01)] 1 Claim
OG exemplary drawing
 
1. A system for determining dementia risk factors, comprising:
a server comprising an artificial neural network (ANN), a transmitter of the server, a receiver of the server, a processor of the server, a memory of the server communicatively coupled to the processor of the server and storing instructions operable when executed by the processor of the server to perform a predetermined function and automatically determining the dementia risk factors with a biometric information and a dementia related information, wherein
the dementia related information comprises a first dementia related information, a second dementia related information, a third dementia related information and a fourth dementia related information, and
the ANN is implemented as an application specific integrated circuit (ASIC);
a wearable device comprising a transmitter of the wearable device, a receiver of the wearable device, an acceleration sensor, a motion sensor, a processor of the wearable device, a memory of the wearable device communicatively coupled to the processor of the wearable device and storing instructions operable when executed by the processor of the wearable device to perform a predetermined function, automatically measuring the biometric information including consumed calories, a spent activity time, a sleep duration, a type of sleep for each sleep time, a heart rate, a number of steps, a walking distance and a number of exercises and communicating with a plurality of Internet of Things (IoT) devices;
the plurality of Internet of Things (IoT) devices, each of the plurality of IoT devices comprising a processor of the IoT devices, a memory of the IoT devices communicatively coupled to the processor of the IoT devices and storing instructions operable when executed by the processor of the IoT devices to perform a predetermined function, a transmitter and a receiver and automatically communicate with the server and the wearable device, wherein:
the plurality of IoT devices comprises a first IoT device, a second IoT device and a third IoT device;
the first IoT device is a device that is fixed at a predetermined location, operated based on a IoT cloud, automatically receives a signal from the wearable device and transmits data to the server and the second and third IoT devices through the IoT cloud;
the second IoT device is a device with a power of a predetermined level which is lower than a power of the first and third IoT devices; and
the third IoT device is a device that is installed in an indoor space and automatically measures a temperature, a humidity, an air pollution level and an illuminance of an indoor environment of a wearer of the wearable device, wherein the third IoT device further automatically measures an information of a start time and an end time of a workday and the sleep duration of the wearer of the wearable device via a connection to the wearable device and automatically transmits the information of the start time and the end time to the server;
a computed tomography (CT) scanner measuring the first dementia related information;
a magnetic resonance imaging (MRI) scanner measuring the second dementia related information;
an electroencephalogram (EEG) recorder measuring the third dementia related information;
an amyloid positron emission tomography (PET) scanner measuring a fourth dementia related information; and
a blood biomarker measuring the fifth dementia related information.