IP Library › Granted Patent US 12,635,891
Granted Patent B2
US 12,635,891 · App. 18/474,713 · Granted May 26, 2026

Process and system for collecting, storing, analyzing and visualizing electrocardiographic data (ECG) in real time

Inventors: Marco Tulio Vilaca Castagna (Brumadinho, BR); Ilene Maria Guimaraes de Siqueira Castagna (Brumadinho, BR)
Assignee: Lótus Medicina Avançada
A61B5/0205A61B5/0022A61B5/6804A61B5/6823A61B5/6898A61B5/7225A61B5/7271A61B5/747A61B2505/01A61B2560/02A61B2560/0406A61B2560/0431A61B2560/0468A61B2562/0204A61B2562/043A61B2562/164A61B2562/221
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Quick Facts
Patent No.
US 12,635,891
App. No.
18/474,713
Granted
May 26, 2026
Kind
B2
Abstract

The present application refers to a process and a system for collecting, storing, analyzing and visualizing electrocardiographic (ECG) data collected by portable ECG device ( 100 ) with embedded wireless communication technology, additionally containing a portable ECG device ( 100 ), a hermetically sealed box ( 200 ) of medicines containing a lock system comprising a lock ( 220 ), a first device ( 310 ) to be accessed by the patient, a second device ( 320 ) to be accessed by the medical professional, a platform for graphical display of ECG data, and a remote data storage and processing central. The hardware board of the portable ECG device contains wireless communication technology, global positioning system (GPS), start button ( 141 ), rechargeable battery charging port, and an equipment configuration and programming port. The battery ( 120 ) is Li-Ion type, containing LEDs indicating device operation, and waiting for connection. The battery status is displayed on the app display. In one embodiment, an electrode ( 130 B) is positioned on the bottom cover ( 110 B) of the housing ( 110 A, 110 B, 110 C) of the ECG device ( 100 ).

Claims (76)

1 . Process for collecting, storing, analyzing and visualizing electrocardiographic (ECG) data collected by a portable ECG device ( 100 ) with embedded wireless communication technology, additionally containing at least one device with wireless communication technology, an airtight box ( 200 ) comprising medicines and at least one central data storage system ( 330 ), wherein it comprises

a portable ECG device ( 100 ), comprising

one electrode array ( 130 ),

a housing ( 110 A, 110 B, 110 c ),

a rechargeable battery ( 120 ) contained by the housing ( 110 A, 110 B, 110 C), and

a portable mini-ECG apparatus ( 140 ) contained by the housing ( 110 A, 110 B, 110 C), with a hardware board with embedded wireless communication technology, a global positioning system (GPS), a start button ( 141 ), a rechargeable battery charging port ( 120 ) and an equipment configuration and programming port;

a hermetically sealed box ( 200 ) of medicines containing a locking system;

a first device ( 310 ), accessed by a patient;

a second device ( 320 ), accessed by a doctor or expert;

a platform for graphical display of ECG data, wherein

the platform is accessed by the first device ( 310 ) in the form of at least one between an application, a website, and a web application (Web App), and

the platform is accessed by the second device ( 320 ) in the form of at least one between an application, a website, and a web application (Web App); and

a central ( 330 ) for remote data storage and processing.

2 . The process according to claim 1 , wherein it comprises an electrocardiographic signal analysis suite embedded in the hardware board, consisting of

at least one signal amplifier,

at least one high-pass filter, and

at least one microprocessor,

wherein the signal analysis set receives signals captured by the electrodes ( 130 ) and generates M signals through an algorithmic-numerical modeling,

the algorithm-numerical modeling being any one of LSTM (Long Short-Term Network), UTC (Universal Transformation Coefficient) and vectorized (Vector-Based) formulations, and

the M signals are generated according to a 12-lead ECG comparison (M=8), reaching up to 22 leads (M=18).

3 . The process according to claim 1 , wherein it comprises one electrocardiographic signal analysis set that is embedded in the first device ( 310 ), wherein

the electrocardiographic signal analysis suite is an integral part of the platform software for graphical display of the ECG, and it performs the functions of high-pass filter, signal amplifier and processing,

the signal analysis suite receives the signals captured by the electrodes ( 130 ) and generates M signals by means of the algorithmic-numerical modeling,

the algorithm-numerical modeling being any one of LSTM (Long Short-Term Network), UTC (Universal Transformation Coefficient) and vectorized (Vector-Based) formulations, and

the M signals are generated according to a 12-lead ECG comparison (M=8), which can reach 22 leads (M=18); and

the platform is accessed by the first device ( 310 ) in the form of at least one between an application (App) and a web application (Web App).

4 . The process according to claim 1 , wherein it comprises the steps of

attaching the electrode array ( 130 ) to the patient;

activating the ECG device ( 100 ) with the start button ( 141 );

collection and processing of electrocardiographic signals by the ECG device ( 100 );

collection of a geospatial positioning data by the GPS;

sending a data (D2) containing the processed signals and geospatial position to the first device ( 310 ) through at least one of BLE, Wi-Fi, 3G, 4G and 5G, in real time;

receiving the data (D2) by the first device ( 310 ) for storage, display and analysis by the platform accessed by the first device ( 310 ); and

sending the data (D2) to the remote data storage and processing central ( 330 ) through at least one of Wi-Fi, 3G, 4G, 5G, LAN, Ethernet, and other network connections.

5 . The process according to claim 1 , wherein it comprises the steps of

attaching the electrode array ( 130 ) to the patient;

activating the ECG device ( 100 ) with the start button ( 141 );

collection of electrocardiographic signals by the ECG device ( 100 );

collection of a geospatial positioning data by the GPS;

sending a data (D1) containing the electrocardiographic signals and geospatial position to the first device ( 310 ) through at least one of BLE, Wi-Fi, 3G, 4G and 5G, in real time;

receiving the data (D1) by the first device ( 310 ) for storage, display and analysis by the platform accessed by the first device ( 310 );

processing the electrocardiographic signals contained in the data (D1) received by the first device ( 310 ); and

sending a processed data (D2) to the central ( 330 ) for remote data storage and processing through at least one of Wi-Fi, 3G, 4G, 5G, LAN, Ethernet, and other network connections.

6 . The process according to the claim 5 , wherein it comprises an electrode ( 130 b ) of the electrode array ( 130 ) that is attached to the bottom cover ( 110 b ) of the portable ECG device ( 100 ).

7 . The process according to claim 1 , wherein the activation of the start button ( 141 ) is performed manually by the patient; or

remotely by the patient by sending a start button

activation signal ( 141 ) from the first device ( 310 ) to the ECG device ( 100 ) through at least one of BLE, Wi-Fi, 3G, 4G and 5G; or

remotely by the doctor or expert through the steps of

sending a start button activation signal ( 141 ) from the second device ( 320 ) to the remote data storage and processing central ( 330 ) through at least one of Wi-Fi, 3G, 4G, 5G, LAN, Ethernet and other network connections;

sending a start button activation signal ( 141 ) from the remote data storage and processing central ( 330 ) to the first device ( 310 ) through at least one of Wi-Fi, 3G, 4G, 5G, LAN, Ethernet, and other network connections; and

sending a start button activation signal ( 141 ) from the first device ( 310 ) to the ECG device ( 100 ) through at least one of BLE, Wi-Fi, 3G, 4G and 5G.

8 . The process according to claim 1 , wherein the remote data storage and processing central ( 330 ) analyzes the processed ECG data received in real time, wherein the analysis considers

a ECG data history from the patient that is present in the storage and processing central ( 330 ); and

a historical ECG data of public knowledge,

considering that the publicly known history is part of the database ( 330 ) from the storage and processing central, and

the public knowledge history includes ECG data from heart diseases, such as valve heart disease, hypertensive heart disease, ischemic heart disease, congenital heart disease, myocardial diseases, coronary artery disease, acute coronary syndromes, acute myocardial infarction, and ECG data from arrhythmias of the heart, such as tachycardia, bradycardia, sinus node disease, atrial fibrillation, extrasystole, fascicular block, atrioventricular block, ventricular arrhythmia, hereditary arrhythmia, and sudden death.

9 . The process according to claim 1 , wherein the analysis classifies the received ECG data, in real time, in which

data are classified by the doctor or expert after analyzing the ECG signals;

the doctor or expert issues a report with his medical opinion of an ECG result; and

a notification is forwarded to the patient, through the first device ( 310 ), informing a receipt of the report.

10 . The process according to claim 1 , wherein the doctor or expert analyzes the processed ECG data received after completion of reading, wherein the analysis considers symptoms indicated by the patient at the beginning of an ECG exam.

11 . The process according to claim 10 , wherein the storage and processing central ( 330 ) forwards an emergency notification to both the doctor or expert and the patient in case of a report indicating risk of death, of permanent or of intermittent damage to the patient, in which

the emergency notification is forwarded to the doctor or expert, and

the notification is forwarded through one between an in-app notification and a push notification, and

the notification contains at least the geospatial location of the patient and the identified heart disease or anomaly;

the emergency notification is forwarded to the patient through a medium between in-app notification and push notification;

an emergency medical center is automatically contacted, in which

the medical center is selected by the geospatial location of the patient; and

the emergency notification is forwarded to at least one emergency contact pre-registered by the patient, in which

the emergency notification contains at least the geospatial location of the patient and the contact of the contacted emergency medical center.

12 . The process according to claim 1 , wherein the analysis classifies a received ECG data in real time, in which

data are classified by the doctor or expert after analyzing the ECG signals;

the doctor or expert issues a report with his medical opinion of an ECG result;

a notification is forwarded to the patient, through the first device ( 310 ), informing a receipt of the report and notifying a dosage of a medication to be taken by the patient; and

the doctor or expert remotely releases an opening of the hermetically closed box ( 200 ).

13 . The process according to claim 12 , wherein the doctor or expert remotely releases a locking system of the hermetically sealed box ( 200 ) so that the patient has access to a drug dosage that is specific to his/her condition diagnosed by the system.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Sep 26, 2023
From: CASTAGNA, ILENE MARIA GUIMARAES DE SIQUEIRA; CASTAGNA, MARCO TULIO VILACA
To: LÓTUS MEDICINA AVANÇADA
Reel/Frame 065032/0277 →
Priority Claims (1)
BR 102016025939-8 · Nov 7, 2016 · national
Continuity (2)
Continuation In Part 16347777
Related Publication 20240016395A1 · Jan 18, 2024
References Cited (33)
US 4288006A · Clover, Jr. · 1981 [cited by applicant]
US 6304797B1 · Shusterman · 2001 [cited by applicant]
US 6970731B1 · Jayaraman et al. · 2005 [cited by applicant]
US 7412281B2 · Shen et al. · 2008 [cited by applicant]
US 9282893B2 · Longinotti-Buitoni · 2016 [cited by applicant]
US 9569588B2 · Lowe · 2017 [cited by applicant]
US 9569592B2 · Heffron · 2017 [cited by applicant]
US 9662030B2 · Thng · 2017 [cited by applicant]
US 10123741B2 · Wang et al. · 2018 [cited by applicant]
US 20070219454A1 · Guzzetta et al. · 2007 [cited by applicant]
US 20120158074A1 · Hall · 2012 [cited by applicant]
US 20130254966A1 · Pattison · 2013 [cited by applicant]
US 20130281815A1 · Varadan · 2013 [cited by applicant]
US 20140070957A1 · Longinotti-Buitoni · 2014 [cited by applicant]
US 20140278475A1 · Tran · 2014 [cited by applicant]
US 20140364779A1 · Oestreich · 2014 [cited by applicant]
US 20150272464A1 · Armoundas et al. · 2015 [cited by applicant]
US 20160066809A1 · Chebiyyam · 2016 [cited by applicant]
US 20160095527A1 · Thng et al. · 2016 [cited by applicant]
US 20160287480A1 · Hancock et al. · 2016 [cited by applicant]
BR 1320210183704E2 · 2022 [cited by applicant]
CN 102940488A · 2013 [cited by applicant]
KR 20090123963A · 2009 [cited by applicant]
KR 20100126107A · 2010 [cited by applicant]
WO 8902246A1 · 1989 [cited by applicant]
WO 2005034743A1 · 2006 [cited by applicant]
WO 2008116822A2 · 2008 [cited by applicant]
WO 2012088398A2 · 2012 [cited by applicant]
WO 2015179015A1 · 2015 [cited by applicant]
Hsu et al., “Design of a Wearable 12-Lead Noncontact Electrocardiogram Monitoring System”, Sensors, Mar. 28, 2019 (13 pages). [cited by applicant]
Shao et al., “AWearable Electrocardiogram Telemonitoring System for Atrial Fibrillation Detection”, Sensors, Jan. 22, 2020 (16 pages). [cited by applicant]
Geng Yang et al., “A Health-IoT Platform Based on the Integration of Intelligent Packaging, Unobtrusive Bio-Sensor and Intelligent Medicine Box”, IEEE Transactions on Industrial Informatics, pp. 2180-2191, Nov. 2014. [cited by applicant]
Upkar Varshney, “Wireless Medication Management System: Design and Performance Evaluation”, Department of Computer Information Systems Georgia State University, 2011 (8 pages). [cited by applicant]