1. A portable non-contact electrocardiography (ECG) measuring system for automatic detection of cardiac arrhythmia, the system comprising: a signal acquisition module (102) configured to detect and record an input cardiac signals from a user, wherein said signal acquisition module (102) comprises a plurality of contactless electrocardiography (ECG) electrodes with a first contactless electrode being a reference electrode (106) and a second and a third contact electrodes (104) are configured to receive said input cardiac signals from said user, wherein said reference electrode (106) is configured to eliminate noise extracted during detecting and recording said signals from said second and third electrodes (104); a signal processing and conduction module (108) operatively coupled to said signal acquisition module (102) and configured to receive said detected and recorded cardiac signal from said signal acquisition module (102), wherein said signal processing and conduction module (108) comprises an instrumentation amplifier (110) which is configured to amplify said received input signal and transmit said amplified signal to a notch filter (112) which is configured to filter said amplified signal within a first threshold range of frequency and attenuates said amplified signal above said first threshold frequency, wherein said filtered signals are transmitted to an analog to digital converter (114) which is configured to convert said transmitted signals from said notch filter (112) into an electrocardiography (ECG) signal of a defined frequency band and amplitude; a data acquisition module (116) operatively coupled to said processing and conduction module (108) and configured to receive said electrocardiography (ECG) signal of a defined frequency band and amplitude, wherein said data acquisition module (116) comprises a storage unit (118) which is configured to store said received ECG signal; and a user interface module (122) communicatively coupled to said data acquisition module (116) via a communication channel (120), wherein said user interface module (122) comprises a smart electronic gadget with a display screen and is configured to receive in real-time said ECG signals from said data acquisition module (116), wherein said user continuously monitors said ECG signals detected and recorded from said user via said plurality of electrodes (104).

2. The system as claimed in claim 1, wherein said system further comprises: an IoT interface wirelessly communicating with said data acquisition module and said user interface module, wherein said IoT interface comprises a web-based cloud interface which is configured to receive continuously said electrocardiography (ECG) signal of a defined frequency band and amplitude in real-time, wherein said IoT interface is configured to store said received ECG signals in a cloud-based storage for a specific period of time in order to be retrieved from said user interface.

3. The system as claimed in claim 1, wherein said signal conduction module further comprises: an operational amplifier of a specific impedance configured to amplify said cardiac signals received from said signal acquisition module, and an ultra- low bias current with active bootstrapping and a common mode voltage feedback circuit.

4. The system as claimed in claim 1, wherein said system further comprise: at least two- polymer based flexible dry non-contact ECG electrodes placed over a chest of said user in order to record bio-potential on the said user’s surface.

5. The system as claimed in claim 1, wherein the system further comprises: at least three or more sensing electrodes configured to be placed in a seat belt or a chair or an arm in order to detect and record signals from said user, wherein said recorded signals are configured to be multiplexed with a number of differential signal input combinations.

6. The system as claimed in claim 1, wherein said signal processing and conduction module is configured to acquire said ECG signals in a range of 0.05 to 120 Hz, and wherein said recorded ECG signals are directly transmitted and stored on said user interface module of said user, wherein said user interface includes smart phones having access to Bluetooth and/or web connectivity.

7. The system as claimed in claim 1, wherein said system further comprises: a fabric including a sensor pad comprising an array of contactless ECG electrodes; a signal processor operatively connected to said sensor pad and adapted to receive contactless ECG signals from said contactless ECG electrodes.

8. The system as claimed in claim 1, wherein said system further comprises: a time-frequency based wavelet transform interface configured to receive and analyze said detected signals from said contactless electrodes, wherein said analyzed signals are configured to be classified through artificial neural networks, in order to identify cardiac activity, wherein said classified signals are configured to be transmitted wirelessly to a cardiologist for interpretation.

9. The system as claimed in claim 1, wherein said system further comprises: a main on/off button configured to turn said system in ON and/or OFF condition, wherein when said main on/off button is turned in ON condition, said system searches for said user interface module through a Bluetooth connection of said user interface, wherein when said Bluetooth connection of said user interface is turned off, said system automatically turns in OFF condition.

10. A method of operating a portable non-contact electrocardiography (ECG) measuring system for automatic detection of cardiac arrhythmia, the method comprising steps: detecting and recording an input cardiac signals from a user by a plurality of contactless electrocardiography (ECG) electrodes into a signal acquisition module, wherein said signal acquisition module comprises said plurality of contactless electrocardiography (ECG) electrodes with a first contactless electrode being a reference electrode and a second and a third contact electrodes are configured to receive said input cardiac signals from said user, wherein said reference electrode is configured to eliminate noise extracted during detecting and recording said signals from said second and third electrodes; transmitting said recorded input signals to a signal processing and conduction module operatively coupled to said signal acquisition module, wherein said signal processing and conduction module comprises an instrumentation amplifier which is configured to: amplify said received input signal by said instrumentation amplifier and transmitting said amplified signal to a notch filter which is configured to: filter said amplified signal within a first threshold range of frequency and attenuates said amplified signal above said first threshold frequency, wherein said filtered signals are transmitted to an analog to digital converter which is configured to: convert said transmitted signals from said notch filter into an electrocardiography (ECG) signal of a defined frequency band and amplitude; storing said received electrocardiography (ECG) signal of a defined frequency band and amplitude to a data acquisition module operatively coupled to said processing and conduction module, wherein said data acquisition module comprises a storage unit which is configured to store said received ECG signal; monitoring continuously said electrocardiography (ECG) signal of a defined frequency band and amplitude on a user interface module communicatively coupled to said data acquisition module via a communication channel, wherein said user interface module comprises a smart electronic gadget with a display screen and is configured to receive in real-time said ECG signals from said data acquisition module, wherein said user continuously monitors said ECG signals detected and recorded from said user via said plurality of electrodes.

Description:BRIEF DESCRIPTION OF DRAWINGS
[21] These and other features, aspects, and advantages of the present invention will become better understood when the following detailed description is read with reference to the accompanying drawings in which like characters represent like parts throughout the drawings, wherein:
[22] Figure 1 illustrates a block diagram of components installed in a portable non-contact electrocardiography (ECG) measuring system for automatic detection of cardiac arrhythmia.
[23] Figure 2 illustrates flowchart of steps involved in operating a portable non-contact electrocardiography (ECG) measuring system for automatic detection of cardiac arrhythmia.
[24] Figure 3 illustrates an exploded perspective view of recording and processing of real time ECG signal from patient’s body.
[25] Figure 4 illustrates a side view of placement of three modules, including real time ECG recording and processing, hardware co-design and IoT.
[26] Figure 5 illustrates an implementation of three phases of ECG signals processing, including pre-processing, feature extraction and classification.
[27] Figure 6 illustrates a perspective view of pre-processing stage as a part of software implementation of the present invention.
[28] Figure 7 illustrates ECG feature extraction and optimization stage by the application of wavelet transform on de-noised ECG signal.
[29] Figure 8 illustrates perspective view of classification of ECG arrhythmias using artificial neural network on the basis of extracted and optimized wavelet-based input ECG features.
[30] Figure 9 illustrates an example of side profile view of hardware/software co-design part of the device and Bluetooth module to transmit analyzed ECG signal wirelessly anywhere.
[31] Further, skilled artisans will appreciate that elements in the drawings are illustrated for simplicity and may not have been necessarily been drawn to scale. For example, the flow charts illustrate the method in terms of the most prominent steps involved to help to improve understanding of aspects of the present invention. Furthermore, in terms of the construction of the device, one or more components of the device may have been represented in the drawings by conventional symbols, and the drawings may show only those specific details that are pertinent to understanding the embodiments of the present invention so as not to obscure the drawings with details that will be readily apparent to those of ordinary skill in the art having benefit of the description herein.

DETAILED DESCRIPTION OF THE INVENTION
[32] For the purpose of promoting an understanding of the principles of the invention, reference will now be made to the embodiment illustrated in the drawings and specific language will be used to describe the same. It will nevertheless be understood that no limitation of the scope of the invention is thereby intended, such alterations and further modifications in the illustrated system, and such further applications of the principles of the invention as illustrated therein being contemplated as would normally occur to one skilled in the art to which the invention relates.
[33] It will be understood by those skilled in the art that the foregoing general description and the following detailed description are exemplary and explanatory of the invention and are not intended to be restrictive thereof.
[34] Reference throughout this specification to “an aspect”, “another aspect” or similar language means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the present invention. Thus, appearances of the phrase “in an embodiment”, “in another embodiment” and similar language throughout this specification may, but do not necessarily, all refer to the same embodiment.
[35] The terms "comprises", "comprising", or any other variations thereof, are intended to cover a non-exclusive inclusion, such that a process or method that comprises a list of steps does not include only those steps but may include other steps not expressly listed or inherent to such process or method. Similarly, one or more devices or sub-systems or elements or structures or components proceeded by "comprises...a" does not, without more constraints, preclude the existence of other devices or other sub-systems or other elements or other structures or other components or additional devices or additional sub-systems or additional elements or additional structures or additional components.
[36] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. The system, methods, and examples provided herein are illustrative only and not intended to be limiting.
[37] Embodiments of the present invention will be described below in detail with reference to the accompanying drawings.
[38] The system used a smaller number of Non-Contact and flexible ECG electrodes, to detect any abnormality or disturbance in Cardiac cycle. The effectiveness of the proposed system is that, the patient come to know any perturbation in cardiac activity instantly and report to concerned doctor wirelessly.
[39] Figure 1 illustrates a block diagram of components installed in a portable non-contact electrocardiography (ECG) measuring system for automatic detection of cardiac arrhythmia. The portable non-contact electrocardiography (ECG) measuring system for automatic detection of cardiac arrhythmia is disclosed as follows.
[40] A signal acquisition module (102) is configured to detect and record an input cardiac signals from a user, wherein said signal acquisition module comprises a plurality of contactless electrocardiography (ECG) electrodes (104) with a first contactless electrode being a reference electrode (106) and a second and a third contact electrodes (104) are configured to receive said input cardiac signals from said user, wherein said reference electrode (106) is configured to eliminate noise extracted during detecting and recording said signals from said second and third electrodes (104).
[41] A signal processing and conduction module (108) is operatively coupled to said signal acquisition module (102) and configured to receive said detected and recorded cardiac signal from said signal acquisition module (102), wherein said signal processing and conduction module (108) comprises an instrumentation amplifier (110) which is configured to amplify said received input signal and transmit said amplified signal to a notch filter (112) which is configured to filter said amplified signal within a first threshold range of frequency and attenuates said amplified signal above said first threshold frequency, wherein said filtered signals are transmitted to an analog to digital converter (114) which is configured to convert said transmitted signals from said notch filter (112) into an electrocardiography (ECG) signal of a defined frequency band and amplitude.
[42] A data acquisition module (116) is operatively coupled to said processing and conduction module (108) and configured to receive said electrocardiography (ECG) signal of a defined frequency band and amplitude, wherein said data acquisition module (116) comprises a storage unit (118) which is configured to store said received ECG signal.
[43] A user interface module (122) is communicatively coupled to said data acquisition module (116) via a communication channel (120), wherein said user interface module (122) comprises a smart electronic gadget with a display screen and is configured to receive in real-time said ECG signals from said data acquisition module (116), wherein said user continuously monitors said ECG signals detected and recorded from said user via said plurality of electrodes (104).
[44] Figure 2 illustrates flowchart of steps involved in operating a portable non-contact electrocardiography (ECG) measuring system for automatic detection of cardiac arrhythmia. The method of operating a portable non-contact electrocardiography (ECG) measuring system for automatic detection of cardiac arrhythmia includes steps described follows.
[45] The step (202) states detecting and recording an input cardiac signals from a user by a plurality of contactless electrocardiography (ECG) electrodes into a signal acquisition module, wherein said signal acquisition module comprises said plurality of contactless electrocardiography (ECG) electrodes with a first contactless electrode being a reference electrode and a second and a third contact electrodes are configured to receive said input cardiac signals from said user, wherein said reference electrode is configured to eliminate noise extracted during detecting and recording said signals from said second and third electrodes.
[46] The step (204) involves transmitting said recorded input signals to a signal processing and conduction module operatively coupled to said
signal acquisition module, wherein said signal processing and conduction module comprises an instrumentation amplifier which is configured to: step (206) which involves amplify said received input signal by said instrumentation amplifier and transmitting said amplified signal to a notch filter which is configured to: step (208) which involves filter said amplified signal within a first threshold range of frequency and attenuates said amplified signal above said first threshold frequency, wherein said filtered signals are transmitted to an analog to digital converter which is configured to: step (210) stating convert said transmitted signals from said notch filter into an electrocardiography (ECG) signal of a defined frequency band and amplitude.
[47] The further step (212) involves storing said received electrocardiography (ECG) signal of a defined frequency band and amplitude to a data acquisition module operatively coupled to said processing and conduction module, wherein said data acquisition module comprises a storage unit which is configured to store said received ECG signal.
[48] The final step (216) states monitoring continuously said electrocardiography (ECG) signal of a defined frequency band and amplitude on a user interface module communicatively coupled to said data acquisition module via a communication channel, wherein said user interface module comprises a smart electronic gadget with a display screen and is configured to receive in real-time said ECG signals from said data acquisition module, wherein said user continuously monitors said ECG signals detected and recorded from said user via said plurality of electrodes.
[49] Figure 3 illustrates an exploded perspective view of recording and processing of real time ECG signal from patient’s body (302). The figure depicts an exploded perspective view of the elements that may comprise of two- polymer based flexible dry non-contact ECG electrodes (306), on the chest of patient to record bio-potential on the body surface according to various embodiments of the present invention. These sets of electrodes are substitute of modified lead II in gel based 12-lead conventional ECG method which is chest lead where maximum signal strength is obtained. Each of the elements in acquiring of ECG signals of 0.05-120Hz is configured on signal conditioning circuit on PCB. Capacitive coupling, filtering, common mode noise cancellation, high input impedance amplifier and analog to digital converter are the basic elements used in design interface and signal conditioning circuit. Recorded ECG signal is stored in patient’s mobile (308). On the basis of extracted ECG features from recorded signal, the designed W-ANN architecture is embedded in specs holder shaped device with powered on and Bluetooth module, and transmit it wirelessly (304), in the network. Or, it may be sent to the physician (310), for signal interpretation.
[50] Figure 4 illustrates a side view of placement of three modules, including real time ECG recording and processing, hardware co-design and IoT. The signal acquisition system is illustrated in FIG. 4, comprised set of three active ECG electrodes, two of them for recording purpose (406) and the other is reference electrode (402), called right hand driven, used to remove various kind of noise. High gain instrumentation amplifier, high pass, and pass and notch filter, with high gain analog to digital converter are the basic components of signal conditioning circuit (408), which produce ECG signal of defined frequency band and amplitude to be analyzed further. In some embodiments, the signal conditioning circuit (408) may be having high impedance operational amplifier with ultra-low bias current with active bootstrapping and a common mode voltage feedback circuit. In some embodiments, three or more sensing electrodes are placed in seat belt, chair or arm. The recorded signals are multiplexed with various differential signal input combinations. The system further includes a data acquisition board (410) which receives signals from conduction circuit (408) and transmits it to a doctor (410) via internet of things (IoT).
[51] Figure 5 illustrates an implementation of three phases of ECG signals processing, including pre-processing, feature extraction and classification. As illustrated in FIG. 5, programming of arrhythmia algorithms is conducted in MATLAB, to analyzed several ECG arrhythmias signals in considering reference input taken from MIT BIH arrhythmia database. These signals are applied on real-time situation (502, (504) for noise removal as a part of pre-processing stage (506) and stage (508) is configured to extract various useful signal features as a part of feature extraction and in stage (510) signals are classified in various categories, including Normal Sinus rhythm (N) (512), Left Bundle Branch Block (LBBB) (514), Right Bundle Branch Block (RBBB) (516), Premature Ventricular Contraction(PVC) (518), Atrial-Ventricular Blocks (AV) (520), Ventricular hypertrophy (VH) (522), Atrial tachycardia (AT) (524), Junctional Arrhythmia (JA)signals (526).
[52] Figure 6 illustrates a perspective view of pre-processing stage as a part of software implementation of the present invention. The noise removal pre-processing stage (602) in which noisy ECG signals are downloaded in. mat format in MATLAB WAVELET GUI, is decomposed using Daubechies wavelet transform (db6) at level (604). Baseline Wander Noise (0.5Hz) and Power line interference noise (50/60Hz), are extracted and truncated using approximation wavelet coefficients at level (A9) and detail wavelet coefficients at level (604) (D2), respectively, as indexed by (606, 608, and 610). Soft thresholding (612), from fixed threshold rule is applied on rest of the coefficients. At last, Inverse wavelet transform is used for re-construction (614), of de-noised signal, having modified values of wavelet coefficients.
[53] Figure 7 illustrates ECG feature extraction and optimization stage by the application of wavelet transform on de-noised ECG signal. The ECG signal can be analyzed by extracting various features from stage (702) to (706), including, i) temporal/time-domain features (708), Pre-RR interval, Post RR interval, Average RR interval, Local average RR interval; ii) Morphological/Spatial ECG features (710), i.e., P wave, QRS complex, S wave, T wave, PR interval, PQ interval, ST segment, QT segment or mixed features; (iii) Statistical features (712), i.e., mean, median and standard deviation, (iv) frequency domain features (714), i.e., Energy and Entropy. Through numerical simulation of statistical parameters (716) (standard deviation, mean and median) followed by wavelet decomposed de-noisy ECG signal, optimal selection of ECG feature sets is done (718), which is used as an input feature vector in the next processing stage (720).
[54] Figure 8 illustrates perspective view of classification of ECG arrhythmias using artificial neural network on the basis of extracted and optimized wavelet-based input ECG features. A side profile view of an example of Neural Network based classifier (806) in pattern recognition tool box (804) in MATLAB 14 to categorized selected ECG features (802) which make up high classification accuracy of the device according to the present invention. A three-layer, i. Input Layer, ii Hidden Layer and Output layer, architecture is designed having number of neurons equal to input feature set. The network (806) detects ECG arrythmia (808) with three classifications as sensitivity (810), selectivity (812) and accuracy (814).
[55] Figure 9 illustrates an example of side profile view of hardware/software co-design part of the device and Bluetooth module to transmit analyzed ECG signal wirelessly anywhere. For the micro controller unit (MCU), ALTERA CYCLONE III FPGA IC, Intel; EP3C5E144C7NFPGA series 6, is selected to have an ultra-low power unit. Nios II is a 32-bit reduced instruction set computer (RISC) architecture is embedded as soft-core processor of up to 25 MHz system clock with 12-bit analog-to-digital converter (ADC). In further, the Bluetooth low energy (BLE) using Texas Instruments CC25 series (Texas Instruments Incorporated, Dallas, 75243 TX, USA) connection system is utilized to have a power-optimized system-on-chip (SOC) solution that supports maximum 2 Mbps data rates. The system states a data base of ECG arrythmia (902) which is fed to ECG signal preprocessing (904) in MATLAB along with ECG feature extraction (906) and classification of ECG arrythmia (908). Then there is a hardware implementation (910) to further store and transmit said ECG signal to user interface (914) via wireless modules such as Bluetooth (912)
[56] The present invention further states that said system further comprises an IoT interface wirelessly communicating with said data acquisition module and said user interface module, wherein said IoT interface comprises a web-based cloud interface which is configured to receive continuously said electrocardiography (ECG) signal of a defined frequency band and amplitude in real-time, wherein said IoT interface is configured to store said received ECG signals in a cloud-based storage for a specific period of time in order to be retrieved from said user interface.
[57] The signal conduction module further comprises an operational amplifier of a specific impedance configured to amplify said cardiac signals received from said signal acquisition module, and an ultra-low bias current with active bootstrapping and a common mode voltage feedback circuit.
[58] The system further comprises at least two- polymer based flexible dry non-contact ECG electrodes placed over a chest of said user in order to record bio-potential on the said user’s surface.
[59] The system further comprises at least three or more sensing electrodes configured to be placed in a seat belt or a chair or an arm in order to detect and record signals from said user, wherein said recorded signals are configured to be multiplexed with a number of differential signal input combinations. The signal processing and conduction module is configured to acquire said ECG signals in a range of 0.05 to 120 Hz.
[60] The recorded ECG signals are directly transmitted and stored on said user interface module of said user, wherein said user interface includes smart phones having access to Bluetooth and/or web connectivity.
[61] The system further comprises a fabric including a sensor pad comprising an array of contactless ECG electrodes; and a signal processor operatively connected to said sensor pad and adapted to receive contactless ECG signals from said contactless ECG electrodes.
[62] The system further comprises a time-frequency based wavelet transform interface configured to receive and analyze said detected signals from said contactless electrodes, wherein said analyzed signals are configured 440 to be classified through artificial neural networks, in order to identify cardiac activity, wherein said classified signals are configured to be transmitted wirelessly to a cardiologist for interpretation.
[63] The system further comprises a main on/off button configured to turn said system in ON and/or OFF condition, wherein when said main on/off button is turned in ON condition, said system searches for said user interface module through a Bluetooth connection of said user interface, wherein when said Bluetooth connection of said user interface is turned off, said system automatically turns in OFF condition.
[64] The present invention comprises novel FPGA based fully automated platform for ECG signal processing in wearable sensor-system, generally consisting of one or two on-board flexible ECG electrodes which adjust themselves according to user movement. The consistent ECG signals from patent’s body is recorded using contact-less, Polymer based Dry ECG electrodes, say capacitive sensing method. This received signal is analyzed using time-frequency based Wavelet transform method followed by signal classification of selected features to identify cardiac activity using Artificial Neural Networks. Both of these units are coupled in low power FPGA device where the received signal may be transmitted wirelessly to the cardiologist for interpretation. The small start button powers the device ON. The device will detect the connection of the Bluetooth, which will either associate the Smartphone or not. When there is no Bluetooth device connection, the device will be turned to off-line state allowing the data to be stored only in the SD card. Meanwhile, the on-line evaluation will send real-time ECG data to the smart phone application. Finally, in preferred embodiments, the various elements are configured in specs holder shape device which incorporate ECG electrodes, smaller size FPGA signal processing and battery-operated unit, to make robust, portable and easy to handle system for ECG analysis.
[65] The drawings and the forgoing description give examples of embodiments. Those skilled in the art will appreciate that one or more of the described elements may well be combined into a single functional element. Alternatively, certain elements may be split into multiple functional elements. Elements from one embodiment may be added to another embodiment. For example, orders of processes described herein may be changed and are not limited to the manner described herein. Moreover, the actions of any flow diagram need not be implemented in the order shown; nor do all of the acts necessarily need to be performed.
[66] Also, those acts that are not dependent on other acts may be performed in parallel with the other acts. The scope of embodiments is by no means limited by these specific examples. Numerous variations, whether explicitly given in the specification or not, such as differences in structure, dimension, and use of material, are possible. The scope of embodiments is at least as broad as given by the following claims.
[67] Benefits, other advantages, and solutions to problems have been described above with regard to specific embodiments. However, the benefits, advantages, solutions to problems, and any component(s) that may cause any benefit, advantage, or solution to occur or become more pronounced are not to be construed as a critical, required, or essential feature or component of any or all the claims.
, Claims:WE CLAIM:
1. A portable non-contact electrocardiography (ECG) measuring system for automatic detection of cardiac arrhythmia, the system comprising:
a signal acquisition module (102) configured to detect and record an input cardiac signals from a user, wherein said signal acquisition module (102) comprises a plurality of contactless electrocardiography (ECG) electrodes
with a first contactless electrode being a reference electrode (106) and a second and a third contact electrodes (104) are configured to receive said input cardiac signals from said user, wherein said reference electrode (106) is configured to eliminate noise extracted during detecting and recording said signals from said second and third electrodes (104);
a signal processing and conduction module (108) operatively coupled to said signal acquisition module (102) and configured to receive said detected and recorded cardiac signal from said signal acquisition module (102), wherein said signal processing and conduction module (108) comprises an instrumentation amplifier (110) which is configured to amplify said received input signal and transmit said amplified signal to a notch filter (112) which is configured to filter said amplified signal within a first threshold range of frequency and attenuates said amplified signal above said first threshold frequency, wherein said filtered signals are transmitted to an analog to digital converter (114) which is configured to convert said transmitted signals from said notch filter (112) into an electrocardiography (ECG) signal of a defined frequency band and amplitude;
a data acquisition module (116) operatively coupled to said processing and conduction module (108) and configured to receive said electrocardiography (ECG) signal of a defined frequency band and amplitude, wherein said data acquisition module (116) comprises a storage unit (118) which is configured to store said received ECG signal; and
a user interface module (122) communicatively coupled to said data acquisition module (116) via a communication channel (120), wherein said user interface module (122) comprises a smart electronic gadget with a display screen and is configured to receive in real-time said ECG signals from said data acquisition module (116), wherein said user continuously monitors said ECG signals detected and recorded from said user via said plurality of electrodes (104).
2. The system as claimed in claim 1, wherein said system further comprises:
an IoT interface wirelessly communicating with said data acquisition
module and said user interface module, wherein said IoT interface comprises a web-based cloud interface which is configured to receive continuously said electrocardiography (ECG) signal of a defined frequency
band and amplitude in real-time, wherein said IoT interface is configured to store said received ECG signals in a cloud-based storage for a specific
period of time in order to be retrieved from said user interface.
3. The system as claimed in claim 1, wherein said signal conduction module further comprises: an operational amplifier of a specific impedance configured to amplify said cardiac signals received from said signal acquisition module, and an ultra- low bias current with active bootstrapping and a common mode voltage feedback circuit.
4. The system as claimed in claim 1, wherein said system further comprise: at least two- polymer based flexible dry non-contact ECG electrodes placed over a chest of said user in order to record bio-potential on the said user’s surface.
5. The system as claimed in claim 1, wherein the system further comprises:
at least three or more sensing electrodes configured to be placed in a seat
belt or a chair or an arm in order to detect and record signals from said user, wherein said recorded signals are configured to be multiplexed with a number of differential signal input combinations.
6. The system as claimed in claim 1, wherein said signal processing and conduction module is configured to acquire said ECG signals in a range of 0.05 to 120 Hz, and wherein said recorded ECG signals are directly transmitted and stored on said user interface module of said user, wherein said user interface includes smart phones having access to Bluetooth and/or web connectivity.
7. The system as claimed in claim 1, wherein said system further
comprises:
a fabric including a sensor pad comprising an array of contactless ECG electrodes; a signal processor operatively connected to said sensor pad and adapted to receive contactless ECG signals from said contactless ECG electrodes.
8. The system as claimed in claim 1, wherein said system further comprises:
a time-frequency based wavelet transform interface configured to receive and analyze said detected signals from said contactless electrodes, wherein said analyzed signals are configured to be classified through
artificial neural networks, in order to identify cardiac activity, wherein said classified signals are configured to be transmitted wirelessly to a cardiologist for interpretation.
9. The system as claimed in claim 1, wherein said system further comprises:
a main on/off button configured to turn said system in ON and/or OFF condition, wherein when said main on/off button is turned in ON condition, said system searches for said user interface module through a Bluetooth connection of said user interface, wherein when said Bluetooth connection of said user interface is turned off, said system automatically turns in OFF condition.
10. A method of operating a portable non-contact electrocardiography (ECG) measuring system for automatic detection of cardiac arrhythmia, the method comprising steps:
detecting and recording an input cardiac signals from a user by a plurality of contactless electrocardiography (ECG) electrodes into a signal acquisition module, wherein said signal acquisition module comprises said plurality of contactless electrocardiography (ECG) electrodes with a first contactless electrode being a reference electrode and a second and a third contact electrodes are configured to receive said input cardiac signals from said user, wherein said reference electrode is configured to eliminate noise extracted during detecting and recording said signals from said second and third electrodes;
transmitting said recorded input signals to a signal processing and conduction module operatively coupled to said signal acquisition module, wherein said signal processing and conduction module comprises an instrumentation amplifier which is configured to: amplify said received input signal by said instrumentation amplifier and transmitting said amplified signal to a notch filter which is configured to: filter said amplified signal within a first threshold range of frequency and attenuates said amplified signal above said first threshold frequency, wherein said filtered signals are transmitted to an analog to digital converter which is configured to: convert said transmitted signals from said notch filter into an electrocardiography (ECG) signal of a defined frequency band and amplitude; storing said received electrocardiography (ECG) signal of a defined frequency band and amplitude to a data acquisition module operatively coupled to said processing and conduction module, wherein said data acquisition module comprises a storage unit which is configured to store said received ECG signal;
monitoring continuously said electrocardiography (ECG) signal of a defined frequency band and amplitude on a user interface module communicatively coupled to said data acquisition module via a communication channel, wherein said user interface module comprises a smart electronic gadget with a display screen and is configured to receive in real-time said ECG signals from said data acquisition module, wherein said user continuously monitors said ECG signals detected and recorded from said user via said plurality of electrodes.