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EP4422499
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EP About this file: EP4422499
| EP4422499 - ELECTROCARDIOGRAM WAVE SEGMENTATION USING MACHINE LEARNING [Right-click to bookmark this link] | Status | Grant of patent is intended Status updated on 02.04.2026 Database last updated on 08.04.2026 | |
| Former | Examination is in progress Status updated on 29.05.2025 | ||
| Former | Request for examination was made Status updated on 02.08.2024 | ||
| Former | The international publication has been made Status updated on 05.05.2023 | ||
| Former | unknown Status updated on 22.11.2022 | Most recent event Tooltip | 02.04.2026 | New entry: Communication of intention to grant a patent | Applicant(s) | For all designated states Boston Scientific Cardiac Diagnostics, Inc. 2900, 37th Street NW, Building 003 Rochester, MN 55901 / US | [2024/36] | Inventor(s) | 01 /
TEPLITZKY, Benjamin A. Rochester, Minnesota 55901 / US | [2024/36] | Representative(s) | Pfenning, Meinig & Partner mbB Patent- und Rechtsanwälte Joachimsthaler Straße 10-12 10719 Berlin / DE | [2024/36] | Application number, filing date | 22802400.6 | 26.10.2022 | [2024/36] | WO2022US47809 | Priority number, date | US202163272961P | 28.10.2021 Original published format: US 202163272961 P | [2024/36] | Filing language | EN | Procedural language | EN | Publication | Type: | A1 Application with search report | No.: | WO2023076331 | Date: | 04.05.2023 | Language: | EN | [2023/18] | Type: | A1 Application with search report | No.: | EP4422499 | Date: | 04.09.2024 | Language: | EN | The application published by WIPO in one of the EPO official languages on 04.05.2023 takes the place of the publication of the European patent application. | [2024/36] | Search report(s) | International search report - published on: | EP | 04.05.2023 | Classification | IPC: | A61B5/318 | [2024/36] | CPC: |
A61B5/318 (EP);
G16H40/63 (US);
A61B5/349 (US);
A61B5/7203 (US)
| Designated contracting states | AL, AT, BE, BG, CH, CY, CZ, DE, DK, EE, ES, FI, FR, GB, GR, HR, HU, IE, IS, IT, LI, LT, LU, LV, MC, ME, MK, MT, NL, NO, PL, PT, RO, RS, SE, SI, SK, SM, TR [2024/36] | Title | German: | ELEKTROKARDIOGRAMMWELLENSEGMENTIERUNG UNTER VERWENDUNG VON MASCHINENLERNEN | [2024/36] | English: | ELECTROCARDIOGRAM WAVE SEGMENTATION USING MACHINE LEARNING | [2024/36] | French: | SEGMENTATION D'ONDE D'ÉLECTROCARDIOGRAMME À L'AIDE D'UN APPRENTISSAGE AUTOMATIQUE | [2024/36] | Entry into regional phase | 25.04.2024 | National basic fee paid | 25.04.2024 | Designation fee(s) paid | 25.04.2024 | Examination fee paid | Examination procedure | 25.04.2024 | Examination requested [2024/36] | 25.04.2024 | Date on which the examining division has become responsible | 31.10.2024 | Amendment by applicant (claims and/or description) | 02.06.2025 | Despatch of a communication from the examining division (Time limit: M04) | 02.10.2025 | Reply to a communication from the examining division | 02.04.2026 | Communication of intention to grant the patent | Fees paid | Renewal fee | 22.10.2024 | Renewal fee patent year 03 | 22.10.2025 | Renewal fee patent year 04 |
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| Responsibility for the accuracy, completeness or quality of the data displayed under the link provided lies entirely with the Unified Patent Court. | Cited in | International search | [XI] US2009069703 (TAKLA GEORGE et al.) [X] 1,8 * paragraph [0003] - paragraph [0024] * * paragraph [0047] - paragraph [0084] * * figures 1-16 *[I] 2-7,9-14 | [A] US2019216350 (SULLIVAN ADAM et al.) [A] 1-14 * paragraph [0103] - paragraph [0124] * * paragraph [0311] - paragraph [0392] * * figures 1-17 * | [A] US2020305799 (CAO JUN et al.) [A] 1-14 * paragraph [0007] - paragraph [0046] * * paragraph [0075] - paragraph [0146] * * figures 1,2 * | [A] US2014187988 (ONG MARCUS ENG HOCK et al.) [A] 1-14 * paragraph [0005] - paragraph [0012] * * paragraph [0053] - paragraph [0064] * * paragraph [0138] - paragraph [0176] * * paragraph [0247] - paragraph [0273] * * pages 1-14 * | [A] US2020357517 (HADDAD TAREK D et al.) [A] 1-14 * paragraph [0005] - paragraph [0009] * * paragraph [0081] - paragraph [0087] * * figures 1-9 * | [A] QINGXUE ZHANG ET AL: "A novel machine learning-enabled framework for instantaneous heart rate monitoring from motion-artifact-corrupted electrocardiogram signals", PHYSIOLOGICAL MEASUREMENT, INSTITUTE OF PHYSICS PUBLISHING, BRISTOL, GB, vol. 37, no. 11, 28 September 2016 (2016-09-28), pages 1945 - 1967, XP020310127, ISSN: 0967-3334, [retrieved on 20160928], DOI: 10.1088/0967-3334/37/11/1945 [A] 1-14 * abstract * DOI: http://dx.doi.org/10.1088/0967-3334/37/11/1945 |