WEARABLE HEARTBEAT AND BREATHING WAVEFORM CONTINUOUS MONITORING SYSTEM

• US 20140350424A1
• Filed: 05/22/2014
• Published: 11/27/2014
• Est. Priority Date: 05/22/2013
• Status: Active Grant

• Current Assignee: Bayland Scientific Incorporated
• Original Assignee: Bayland Scientific, LLC
• Inventors: Zhou, Yuxin, Du, Xiaosong
• Granted Patent: US 10,531,809 B2
• Time in Patent Office: Days
• US Class Current: 600/523
• CPC Class Codes: A61B 2560/0412 Low-profile patch shaped housings
• CPC Class Codes: A61B 2562/0219 Inertial sensors, e.g. accelerometers, gyroscopes, tilt switches
• CPC Class Codes: A61B 5/02438 with portable devices, e.g. worn by the patient
• CPC Class Codes: A61B 5/02444 Details of sensor A61B5/02427 takes precedence
• CPC Class Codes: A61B 5/113 occurring during breathing
• CPC Class Codes: A61B 5/14551 for measuring blood gases
• CPC Class Codes: A61B 5/333 Recording apparatus specially adapted therefor
• CPC Class Codes: A61B 5/35 by template matching
• CPC Class Codes: A61B 5/6898 Portable consumer electronic devices, e.g. music players, telephones, tablet computers
• CPC Class Codes: A61B 5/7264 Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems neural networks per se G06N3/00; expert systems per se G06N5/00
• CPC Class Codes: A61B 7/003 Detecting lung or respiration noise
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems

Abstract

Apparatus and method are provided to collect and analyze heartbeat waveforms. In one novel aspect, the heartbeat waveforms are collected from wearable devices. In one embodiment, the wearable device collects heartbeat waveforms by attaching the device to the patient for a long period and sends the collected waveforms to a receiver through a wireless network. In another novel aspect, an application program is installed in a smart device to receive heartbeat waveforms from one or more wearable devices. The application program either relays the received waveform to a remote processing center or processes the data before sending. In another novel aspect, an analysis method compares received patient'"'"'s current heartbeat waveform with historic data. In one embodiment, the historic data are stored in a cloud-based database. In another novel aspect, the remote processing center is an open platform data center, which takes in certified third party inputs.

Claims

1. A method comprising:

obtaining one or more current heartbeat waveform inputs, wherein the one or more current heartbeat waveform inputs is associated with a user;

retrieving one or more past heartbeat waveform inputs, wherein the one or more past heartbeat waveform inputs are associated with the said user;

identifying changes associated with the said user by comparing the current one or more heartbeat waveform inputs with the one or more past heartbeat waveform inputs based on predefined comparison algorithms; and

generating a user report based on the identified changes associated with the said user based comparison report algorithms.

2. The method of claim 1 further comprises:

identifying disease similarities by comparing the current one or more heartbeat waveform inputs with one or more preconfigured disease patterns; and

generating a user report based on the identified similarities associated with the said user based similarity report algorithms.

3. The method of claim 1, wherein the current one or more heartbeat waveform inputs is obtained from a remote wearable device via a network connection.

4. The method of claim 1, wherein the current one or more heartbeat waveform inputs is obtained from a smart device via a network connection, and wherein the smart device obtains an original heartbeat waveform from a wearable device.

5. The method of claim 1, wherein the comparison algorithm involves applying an algorithm developed by a certified third party.

6. The method of claim 1, wherein the one or more past heartbeat waveform inputs is retrieved from a cloud-based database.

7. The method of claim 1, wherein the comparison algorithm involves:

retrieving or generating a computational cardiology model of the said user, wherein the computational cardiology model predicts a heartbeat waveform;

identifying differences between the current heartbeat waveform and predicted heartbeat waveform through the computational cardiology model;

adjusting parameters of the computational cardiology model to match the current heartbeat waveform; and

generating a comparison report based on the adjusted parameters.

11. The method of claim 1, further comprising:

identifying one or more invalid signal sections of the current one or more heartbeat waveform inputs based one a predefined validation algorithm wherein valid signal sections are identified by skipping the one or more invalid signal sections.

12. The method of claim 11, further comprising:

applying filter to the valid signal sections to filter out body noise and environmental noise.

13. The method of claim 1, further comprising:

characterizing the current one or more heartbeat waveform inputs based on a predefined characterization algorithm, wherein the characterizing extracts characterization parameters.

14. The method of claim 13, wherein the characterizing involves at least one of characterization comprising:

calculating a heartbeat rate, measuring heartbeat intervals, identifying irregular heartbeat intervals, and marking one or more identified irregular heartbeat intervals.

15. The method of claim 1, further comprising:

obtaining one or more movement waveform inputs, wherein each of the one or more movement waveform inputs associates with a corresponding current heartbeat waveform inputs, and wherein each movement waveform inputs indicates a movement status of the user.

16. The method of claim 15, wherein the movement status associated with the corresponding current heartbeat waveform is used in selecting a characterization algorithm, wherein the characterization algorithm applies to at least one of heartbeat characterizations comprising:

calculating a heartbeat rate, measuring heartbeat intervals, identifying irregular heartbeat intervals, and marking one or more identified irregular heartbeat intervals.

17. The method of claim 15, wherein the movement status associated with the corresponding current heartbeat waveform is used in selecting a proper past heartbeat waveform inputs to compare with the corresponding current heartbeat waveform.

8. A system comprising:

a database, wherein the database stores historic waveform information for a plurality of users and one or more disease diseases patterns;

a data processing center, wherein the data processing center is connected with a network interface that receives heartbeat waveform information from one or more remote devices, and wherein the data process center is configured to obtain one or more current heartbeat waveform inputs associated with a current user;

retrieve one or more past heartbeat waveform inputs that are associated with the said current user;

identifies changes associated with the said current user by comparing the one or more current heartbeat waveform inputs with the one or more past heartbeat waveform based on predefined comparison algorithms;

generating a current user report based on the identified changes associated with the said current user based on comparison report algorithms.

9. The system of claim 8, wherein the network interface receives waveform information from one or more wearable heartbeat waveform collecting devices.

10. The system of claim 8, wherein the network interface receives waveform information from one or more smart devices, and wherein the one or more smart devices receives original waveform information from one or more wearable heartbeat waveform collecting devices.

18. The system of claim 8, wherein the comparison algorithm is developed by a third party, and wherein the comparison algorithm is certified by the system before it is accepted by the system.

19. The system of claim 8, wherein the comparison algorithm involves:

retrieving or generating a computational cardiology model of the said current user, wherein the computational cardiology model predicts a heartbeat waveform;

identifying differences between the current heartbeat waveform and predicted heartbeat waveform through the computational cardiology model;

adjusting parameters of the computational cardiology model to match the current heartbeat waveform; and

generating a comparison report based on the adjusted parameters.

20. The system of claim 8, wherein the data processing center is configured to further obtain one or more movement waveform inputs, wherein each of the one or more movement waveform inputs associates with a corresponding current heartbeat waveform inputs, and wherein each movement waveform input indicates a movement status of the current user.