US 12,336,840 B2
Voice-based monitoring and alerting for remote decompensated heart failure detection
Marcus Hott, Berlin (DE); and Oliver Piepenstock, Berlin (DE)
Assigned to Noah Labs GmbH, Berlin (DE)
Filed by Noah Labs UG (haftungsbeschraenkt), Berlin (DE)
Filed on Nov. 28, 2023, as Appl. No. 18/520,875.
Claims priority of provisional application 63/524,375, filed on Jun. 30, 2023.
Prior Publication US 2025/0000445 A1, Jan. 2, 2025
Int. Cl. A61B 5/02 (2006.01); A61B 5/00 (2006.01); A61B 7/00 (2006.01); G16H 50/20 (2018.01); G10L 15/02 (2006.01); G10L 25/51 (2013.01)
CPC A61B 5/4803 (2013.01) [A61B 5/02 (2013.01); A61B 5/6898 (2013.01); A61B 5/7267 (2013.01); A61B 5/7275 (2013.01); A61B 5/746 (2013.01); A61B 7/00 (2013.01); G16H 50/20 (2018.01); G10L 15/02 (2013.01); G10L 25/51 (2013.01)] 9 Claims
OG exemplary drawing
 
5. A detecting and alerting method for detecting onset of decompensated heart failure in remotely-located human subjects and automatically generating electronic intervention alerts based on detected onset, the detecting and alerting method comprising:
receiving digitized voice samples of remotely-located human subjects;
using a computing instance, performing operations comprising:
(i) executing a first machine learning model trained on voice samples from a population to detect at least one feature in speech or voice characteristics that is a sign of onset of decompensated heart failure,
(ii) executing a second machine learning model that analyzes changes in acoustic features of received voice samples from a remotely-located human subject over time,
(iii) blending a first output from the first machine learning model based on voice samples received from the remotely-located human subject with a second output from the second machine learning model based on the received voice samples from the remotely-located human subject,
(iv) detecting onset of decompensated heart failure in the remotely-located human subject based on the blended first and second output, and
(v) generating a detection signal upon detecting onset of decompensated heart failure in the remotely-located human subject; and
automatically generating an electronic alert in response to the computing instance generating the detection signal, the electronic alert suggesting that the remotely-located human subject exhibits signs of onset of decompensated heart failure.