US 12,446,847 B2
Lung sound analysis system
Masao Higuchi, Tokyo (JP); Mitsuru Noma, Tokyo (JP); Reishi Kondo, Tokyo (JP); and Yumi Arai, Tokyo (JP)
Assigned to NEC CORPORATION, Tokyo (JP)
Appl. No. 18/020,390
Filed by NEC Corporation, Tokyo (JP)
PCT Filed Aug. 25, 2020, PCT No. PCT/JP2020/032055
§ 371(c)(1), (2) Date Feb. 8, 2023,
PCT Pub. No. WO2022/044127, PCT Pub. Date Mar. 3, 2022.
Prior Publication US 2023/0284998 A1, Sep. 14, 2023
This patent is subject to a terminal disclaimer.
Int. Cl. A61B 7/00 (2006.01); A61B 5/087 (2006.01); A61B 7/04 (2006.01); G16H 50/20 (2018.01)
CPC A61B 7/003 (2013.01) [A61B 5/087 (2013.01); A61B 7/04 (2013.01); G16H 50/20 (2018.01)] 13 Claims
OG exemplary drawing
 
1. A lung sound analysis device comprising:
a memory containing program instructions; and
a processor coupled to the memory, wherein the processor is configured to execute the program instructions to:
acquire time-series acoustic signals including lung sounds of a subject who is a heart failure patient;
determine a pause phase of breathing of the subject;
divide the time-series acoustic signals into time-series acoustic signals in a period of the pause phase of the subject and time-series acoustic signals in a period other than the pause phase, according to a result of the determination;
calculate an index value representing quality of the time-series acoustic signals in the period other than the pause phase, from intensity of the time-series acoustic signals in the period of the pause phase and intensity of the time-series acoustic signals in the period other than the pause phase after the division;
give warning based on the calculated index value;
input the lung sounds of the subject into a first normal model trained using only lung sound data without lung sound abnormalities of the subject;
acquire a probability that the lung sounds of the subject are abnormal from the first normal model;
determine that the lung sounds of the subject are abnormal lung sounds based on the probability exceeding a first threshold; and
determine that the lung sounds of the subject are normal lung sounds based on the probability being equal to or less than the first threshold.