The electronic device includes a pad module and a main module. At least part of the patch module is attached to a user to obtain a bio-signal of the user. The pad module includes a first housing and a plurality of first electrodes disposed in the first housing. The main module is configured to record the bio-signal of the user that is transferred through the pad module. The main module includes a second housing that is coupled with the first housing in a first direction. The main module also includes a plurality of second electrodes disposed in the second housing. The plurality of second electrodes are configured to make electrical contact with the plurality of first electrodes. The main module further includes a plurality of magnetic bodies disposed in the second housing to correspond to positions of the plurality of second electrodes.

The electronic device includes a pad module and a main module. At least part of the patch module is attached to a user to obtain a bio-signal of the user. The pad module includes a first housing and a plurality of first electrodes disposed in the first housing. The main module is configured to record the bio-signal of the user that is transferred through the pad module. The main module includes a second housing that is coupled with the first housing in a first direction. The main module also includes a plurality of second electrodes disposed in the second housing. The plurality of second electrodes are configured to make electrical contact with the plurality of first electrodes. The main module further includes a plurality of magnetic bodies disposed in the second housing to correspond to positions of the plurality of second electrodes.

Methods and systems are provided for automatically determining a phase shift and noise insensitive similarity metric for electrocardiogram (ECG) beats in a Holter monitor recording. In one embodiment, a deep neural network may be trained to map an ECG beat to a phase shift insensitive and noise insensitive feature space embedding using a training data triad, wherein the training data triad may be produced by a method comprising: selecting a first beat and a second beat recorded via one or more Holter monitors, determining a dynamic time warping (DTW) distance between the first beat and the second beat, setting a similarity label for the first beat and the second beat based on the DTW distance, and storing the first beat, the second beat, and the similarity label, in a location of non-transitory memory as an ECG training data triad.

An arrangement may include a first system provided for processing physiological data representative of a beating heart. The first system may be adapted to execute a process for using at least one pattern to detect a notable finding in the physiological data and for sending the notable finding to a second system. The second system may be adapted to execute a process for analyzing the notable finding, for determining at least one new pattern to send to the first system, and for sending the at least one new pattern to the first system. The at least one new pattern may also include a rule that includes a set of conditions and an action to perform if the set of conditions is met.

The invention relates to the system and method of remote ECG monitoring, remote disease screening, and early-warning system based on wavelet analysis. The system includes a wireless ECG signal acquisition device, a mobile terminal, and a cloud storage platform. The wireless ECG signal acquisition device worn on the user's chest is used to collect ECG signals anywhere and anytime. The method includes transmitting the ECG signals to the mobile terminal using the wavelet analysis algorithm, analyzing and processing the received ECG signal, and uploading the processed ECG signals to the cloud storage platform. The cloud storage platform stores users' personal information and ECG signals. According to the ECG features detection with support vector machine learning algorithm for heart diseases diagnosis and features classification, the system gives feedback report and proposal, and transmits them to the mobile terminal.

An adjustable ECG sensor is attachable to a patient to sense cardiac signals and includes an adjustable leadwire having a flexible substrate, a conductor extending along the flexible substrate, and a connector end connectable to a receiver associated with an ECG monitor. The adjustable ECG sensor further includes an electrode having an electrode pad, a clip connected to the electrode pad and attachable to any one of multiple locations on the adjustable leadwire, and a pin that punctures the flexible substrate and electrically connects to the conductor of the adjustable leadwire. The adjustable ECG sensor is fitted to the patient by attaching the clip of the electrode to one of the multiple locations on the adjustable leadwire.

An apparatus for generating ECG recordings and a method for using the same are disclosed. The apparatus includes a handheld device having four electrodes on an outer surface thereof, the handheld device having an extended configuration and a storage configuration. The apparatus also includes a controller configured to measure signals between the electrodes to provide signals that are used to generate an ECG recording selected from the group consisting of standard lead traces and precordial traces. When the handheld device is in the extended configuration and the first and second electrodes contact a first hand of a patient such that the first and second electrodes contact different locations on the first hand, the third electrode is in contact with a location on the patient's other hand and the fourth electrode contacts a point on the patient's body that depends on the particular trace being measured.

An apparatus for generating ECG recordings and a method for using the same are disclosed. The apparatus includes a handheld device having four electrodes on an outer surface thereof, the handheld device having an extended configuration and a storage configuration. The apparatus also includes a controller configured to measure signals between the electrodes to provide signals that are used to generate an ECG recording selected from the group consisting of standard lead traces and precordial traces. When the handheld device is in the extended configuration and the first and second electrodes contact a first hand of a patient such that the first and second electrodes contact different locations on the first hand, the third electrode is in contact with a location on the patient's other hand and the fourth electrode contacts a point on the patient's body that depends on the particular trace being measured.

A system and method for display of subcutaneous cardiac monitoring data are provided. Cutaneous action potentials of a patient and other sensed data associated with the patient are recorded as electrocardiogram (EGC) data over a set time period using a subcutaneous insertable cardiac monitor. A set of R-wave peaks is identified within the ECG data and an R-R interval plot is constructed. A difference between recording times of successive pairs of the R-wave peaks in the set is determined. A heart rate associated with each difference is also determined. The pairs of the R-wave peaks and associated heart rate are plotted as the R-R interval plot. A diagnosis of cardiac disorder is facilitated based on patterns of the plotted pairs of the R-wave peaks, the associated heart rates in the R-R interval plot, and background data based on the other sensed data.

A system and method for display of subcutaneous cardiac monitoring data are provided. Cutaneous action potentials of a patient and other sensed data associated with the patient are recorded as electrocardiogram (EGC) data over a set time period using a subcutaneous insertable cardiac monitor. A set of R-wave peaks is identified within the ECG data and an R-R interval plot is constructed. A difference between recording times of successive pairs of the R-wave peaks in the set is determined. A heart rate associated with each difference is also determined. The pairs of the R-wave peaks and associated heart rate are plotted as the R-R interval plot. A diagnosis of cardiac disorder is facilitated based on patterns of the plotted pairs of the R-wave peaks, the associated heart rates in the R-R interval plot, and background data based on the other sensed data.