Leadless electrocardiogram monitor

LEADLESS ELECTROCARDIOGRAM MONITOR

TECHNICAL FIELD

In general, this invention relates to electrocardiogram (ECG) monitoring in humans with wearable technology, and in particular to continuous and unobtrusive ECG monitoring utilizing a pair of ergonomically designed wireless smart bands that the user wears around the left and right wrists.

BACKGROUND

A regular ECG test is an essential diagnostic tool that characterizes the heart’s activity at a given point in time. Abnormal heart rhythms and cardiac symptoms may however sporadically appear, disappear, and reappear over time. Consequently, point-in-time ECG tests may miss critical cardiac anomalies, thereby leading to an increased risk of morbidity and mortality.

It is therefore important to monitor ECG continuously in at-risk patients as they go about their normal activities. Quite often, serious heart conditions like atrial fibrillation (AF), cardiomyopathy, and coronary heart disease arc diagnosed with continuous ECG monitoring. This allows for timely clinical interventions like medication and cardiac surgery that reduce adverse outcomes like stroke and heart attack, thereby saving lives.

In clinical practice, it is common to undertake continuous ECG monitoring using a Holter system that can generally record 24-48 hours of cardiac data. The Holter is a small wearable biopotential measurement device comprising several ECG leads. These ECG leads are snapped on to sticky gel electrodes that are attached at various locations on the patient’s chest. A Holter monitoring system is inconvenient and obtrusive due to the sticky gel chest electrodes that often cause discomfort and the unwieldy leads that hang between the electrodes and the Holter unit.

Recently, Medtronic has developed and marketed a leadless Holter system (SEEQ™) in the form of an adhesive chest strip (-4.5” long, ~ 2.0” wide, and ~ 0.6” thick) for continuous ECG monitoring.

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Though leadless, this monitor is awkward and uncomfortable because it uses sticky chest electrodes and it is too bulky to be attached to the chest.

Various kinds of belts that can be worn around the chest for continuous ECG monitoring are available in the market today. Many of these ECG chest belt systems are leadless and employ dry reusable electrodes. Still, these ECG belts need to be wom under clothing and are often quite tight around the chest, causing difficulty and uneasiness to the wearer.

Currently, continuous ECG monitoring technology comes with a number of problems and encumbrances. These include discomfort, uneasiness, sleep disruptions, difficulty in carrying out day-to-day activities, and inability to undertake long-term monitoring (for example, monitoring for days, months, and years).

With the advent of newer generation wearables like smartwatches, attempts have been made to integrate ECG monitoring into a smartwatch. For example, Apple has provided dry’ ECG electrodes on the backplate of a smartwatch (left-side electrodes) and a second set of electrodes on the smartwatch rim (right-side electrodes). A user has to w’ear the smartwatch on one wrist so that the electrodes underneath touch the wrist. Additionally, the user has to touch the second set of electrodes on the smartwatch rim with his/her other hand so that the heart lies in-between the left-side (backplate) and right-side (rim) electrodes that are electrically connected to signal amplification/conditioning circuitry’ inside the smartwatch. The quality of ECG signal acquired in this manner is generally satisfactory. However, the main limitation is that the user has to touch and hold a second set of electrodes on the smartwatch with his/her other hand for monitoring ECG waveform data. As a result, this system only provides an on demand 30 seconds of ECG monitoring, and not continuous and/or long-term ECG monitoring.

To avoid touching a second set of electrodes with the other hand and to accomplish leadless continuous ECG monitoring, attempts have been made to develop wearable single upper limb ECG systems.

Prior art has proposed the use of single arm wearable devices for leadless ECG monitoring. These systems comprise an upper arm band with more than one electrode on the underside that come in contact with the arm when the band is worn. The electrodes are interfaced with an amplification and control unit that may be affixed to the outer surface of the band. Single arm ECG systems have 2

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PCT/CA2020/050304 produced mixed results for a diverse population. The ECG signal acquired by these systems is often noisy, unreliable, and unusable, more so for women and older people.

Based on the principles of single arm ECG systems, other prior art has also proposed leadless ECG monitoring employing wearable single wrist systems. The quality and fidelity of data acquired by single wrist ECG systems has not been properly tested and/or verified. Intuitively, a single wrist ECG system will produce noisier and weaker signals as compared to a single arm ECG system. This is because the wrist is physically farther away from the heart as compared to the upper arm, thus resulting in greater impedance to the flow of electrical charge from the heart to the wrist electrodes.

SUMMARY

In one aspect of the present invention there is disclosed a wearable device related to ECG monitoring technology. The wearable device comprises a pair of ergonomically designed wireless smart bands that are worn around the left and right wrists for unobtrusive continuous leadless ECG waveform data monitoring and analysis. Both smart bands in the described pair are provided with dry’ reusable ECG electrodes on their underside. The electrodes in each smart band are interfaced with biopotential measurement hardware and software inside that smart band. Moreover, the hardware and software inside the two smart bands enables seamless wireless communication between them. When the two smart bands are worn on both hands, their respective electrodes come in contact with the left and right side of the body. With this configuration, the two smart bands independently measure biopotential on the left and right side of the body and wirelessly share/process this information to acquire/analyze high-fidelity ECG waveform data. Thus, the wireless smart band pair accomplishes ECG waveform data monitoring and analysis as per Einthoven’s law’ w ithout the need for physically completing a circuit via leads and/or touching and holding auxiliary electrodes. In one example, the two smart bands independently and simultaneously measure biopotential on the left and right side of the body.

The two smart bands in the described pair are alluded to as a primary smart band and a secondary’ smart band. Both the primary’ and secondary’ smart bands preferably comprise electrodes, ECG amplification/conditioning circuitry’, a microcontroller, a wireless transceiver, and a rechargeable battery. The primary’ smart band can be additionally provided with memory and a touchscreen

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WO 2020/181367 PCT/CA2020/050304 display. Both the primary and secondary smart bands preferably have wireless charging capabilities and can be chaiged on a twin wireless charging unit.

In one embodiment, both primary’ and secondary’ smart bands are provided with three ECG strip electrodes on their underside to maximize the electrode surface area and enhance connectivity’ around the wrist to obtain high-quality ECG signal. Each of the three strip electrodes can be arranged to have a rigid section on the smart band backplate and a flexible section along the underside of the smart band straps. In one example, the rigid electrodes are made of silver while the flexible electrodes are made of conductive fabric.

In one example, in both smart bands, the first strip is a right-side electrode and the second strip is a left-side electrode connected to a biopotential amplifier while the third strip is a ground electrode. In another example, in both smart bands, the right-side and left-side strip electrodes remain unchanged while the third strip is a right leg drive (RLD) electrode to reduce common mode noise and augment ECG signal quality. In yet another example, in both smart bands, the right-side and left-side strip electrodes remain unchanged while the third strip in the secondary smart band is a ground electrode and the third strip in the primary’ smart band is an RLD electrode for enhancing ECG waveform data quality.

In one example, the primary smart band is worn around the left wrist while the secondary smart band is worn around the right wrist. With this setup, the primary’ smart band acquires biopotential data from the left side of the body. Simultaneously, the secondary smart band acquires biopotential data from the right side of the body and transmits this information wirelessly to the primary’ smart band. Biopotential information from the left and right side of the body is processed and combined inside the primary’ smart band using a variety of methods to acquire high-fidelity ECG signal.

In one example, the biopotential data from both smart bands is sent directly’ to the microcontroller inside the primary smart band for processing and obtaining an ECG signal. In another example, the biopotential data from both smart bands is first sent to a differential amplifier for further amplification/conditioning and then to the microcontroller inside the primary’ smart band for processing and obtaining an ECG signal.

In a further embodiment, inside each smart band, a digital switch can be provided between each of the three strip electrodes and the associated signal amplification/conditioning circuitry’, resulting in 4

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WO 2020/181367 PCT/CA2020/050304 three digital electrode switches inside each smart band. These electrode switches allow various electrode configurations to be evaluated for enhancing ECG waveform data quality. This feature is useful for device testing and calibration whereby an optimum electrode configuration that results in best ECG signal quality can be readily determined. In one example, all three electrodes, namely, right, left, and RLD of the primary smart band are switched on while only right and left electrodes of the secondary- smart band are switched on.

In a further aspect, the microcontroller inside the primary- smart band analyzes the acquired ECG waveform data in real-time to compute parameters like heart rate (HR) and heart rate variability (HRV) and to generate alerts when these parameters are out of range. For example, if HRV is above a given threshold, an AF alert is generated. The primary smart band displays real-time ECG waveform data along with metrics like HR and HRV and any alerts that are generated. The onboard memory in the primary smart band stores all ECG-related information. The primary- smart band can also have the functionality to send the acquired ECG waveform data and related information wirelessly to a smartphone, personal computer (PC), tablet, or directly to a cloud server where it can be further processed/analyzed.

Fusion of DSP and Analog Signal Conditioning Techniques

In a further embodiment employing fusion of DSP and analog signal conditioning techniques, in both smart bands, the first strip is a right-side electrode and the second strip is a left-side electrode connected to a biopotential amplifier while the third strip is a reference electrode. In another example, in both smart bands, the right-side and left-side strip electrodes remain unchanged while the third strip or the reference electrode is a ground electrode. In yet another example, in both smart bands, the right-side and left-side strip electrodes remain unchanged while the third strip or the reference electrode is a right leg drive (RLD) electrode to reduce common mode noise and augment ECG signal quality. Finally, in another example, in both smart bands, the right-side and left-side strip electrodes remain unchanged while the third strip or reference electrode in the secondary- smart band is a ground electrode and the third strip or reference electrode in the primary- smart band is an RLD electrode for enhancing ECG waveform data quality-.

In one embodiment, inside each smart band, a digital switch is provided between each of the three strip electrodes and the associated signal amplification/conditioning circuitry, resulting in three digital electrode switches inside each smart band. In another embodiment, the digital switch of the third strip or reference electrode in each smart band is a changeover switch that is used to convert 5

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WO 2020/181367 PCT/CA2020/050304 the reference electrode into either a ground or RLD electrode. In one example, all digital switches inside the two smart bands are controlled by the respective microcontrollers inside the smart bands. These electrode switches allow various electrode configurations to be evaluated and used for enhancing ECG waveform data quality. This feature is useful for device testing and calibration whereby an optimum electrode configuration that results in best ECG signal quality can be readily determined and employed. In an example configuration, all three electrodes, namely, right, left, and RLD of the primary smart band are enabled while only right and left electrodes of the secondary smart band are enabled.

In one example, the biopotential data from both smart bands is sent directly’ to the microcontroller inside the primary’ smart band whereby various digital signal processing (DSP) techniques are employed to obtain an ECG signal. In another example, the biopotential data from both smart bands is first sent to a differential amplifier for analog signal amplification and conditioning, and then to the microcontroller inside the primary smart band for processing and obtaining an ECG signal. In yet another example, the ECG information obtained via the DSP and analog signal amplification/conditioning techniques is fused by the microcontroller inside the primary smart band to obtain an ECG signal of even higher quality and fidelity'.

Electrode Switching

Factors like individual physiology, electrode contact area, mechanical pressure on electrodes, and electrode vibration may introduce noise in the left and right side biopotential data acquired by the smart band pair. Therefore, the resulting ECG signal may also be contaminated with noise. In such scenarios, the digital switches that allow different configurations of the six electrodes of the two smart bands to be used during data acquisition can be employed to reduce noise for obtaining a highfidelity ECG signal. However, for a given operating condition (for example, mechanical pressure on the electrodes), a particular electrode configuration may give best results whereas for another operating condition (for example, electrode vibration), a different electrode configuration may produce better results. To overcome this limitation, in one embodiment, rapid switching of the six digital switches of the two smart bands is undertaken such that left and right side biopotential data is acquired and combined every data sampling period as the sy stem continuously and repeatedly loops through all possible electrode configurations to minimize noise and enhance signal quality’ under all operating conditions.

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In one example using electrode switching, the biopotential data from both smart bands is sent directly to the microcontroller inside the primary smart band whereby various digital signal processing (DSP) techniques are employed to obtain an ECG signal. In another example, the biopotential data from both smart bands is first sent to a differential amplifier for analog signal amplification and conditioning, and then to the microcontroller inside the primary smart band for processing and obtaining an ECG signal. In yet another example, the ECG information obtained via the DSP and analog signal amplification/conditioning techniques is fused by the microcontroller inside the primary smart band to obtain an ECG signal of even higher quality’ and fidelity.

Though this invention is described as related to a pair of wearable smart bands that are attached to a users left and right wrists, the underlying design and principle of the invention can be extended to a pair of wearables that can be attached at any location along the two upper limbs and/or even the two lower limbs. One example comprises a primary’ smart band worn around the wrist and a secondary’ smart band worn around the upper arm of the other hand. Another example comprises both primary’ and secondary’ smart bands worn around the two upper arms. Yet another example comprises a primary smart band worn around the wrist and a secondary smart band worn around the ankle of the other leg. It will be appreciated that the smart band could be a smartwatch or any other similar wearable.

This invention fulfills the theoretical underpinnings of electrocardiography and Einthoven’s law such that biopotential is measured on the left and right sides of the body with the heart in-between utilizing a pair of wirelessly synced wearables (for example, smart bands, smartwatches, and/or any combination thereof) that process all information to acquire high-fidelity single-lead ECG waveform data.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates an exemplary attachment of the wireless smart band pair on a user for continuous leadless ECG monitoring along with external devices to which data is wirelessly transmitted.

FIGS. 2A-2C illustrate the front, side, and back of the primary smart band showing the touchscreen display along with the rigid/flexible strip electrodes and clasping studs/holes.

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FIGS. 3A-3C illustrate the front, side, and back of the secondary smart band showing the front cover along with the rigid/flexible strip electrodes and clasping studs/holes.

FIG. 4 illustrates an alternate view of the primary’ smart band showing the touchscreen display along with the straps, clasping mechanism, and flexible strip electrodes.

FIG. 5 illustrates an alternate view of the secondary smart band showing the front cover along with the straps, clasping mechanism, and flexible strip electrodes.

FIG. 6 illustrates an exploded view of the primary·· smart band showing the key components.

FIG. 7 illustrates an exploded view of the secondary’ smart band showing the key components.

FIG. 8 illustrates the smart band pair being charged on a twin wireless charging unit.

FIG. 9 illustrates an operational diagram of the smart band pair whereby one electrode in each is a ground and biopotential data from both smart bands is sent directly to the microcontroller for processing.

FIG. 10 illustrates an operational diagram of the smart band pair whereby one electrode in each is an RLD and biopotential data from both smart bands is sent directly to the microcontroller for processing.

FIG. 11 illustrates an operational diagram of the smart band pair whereby one electrode in each is a ground and biopotential data from both smart bands is first sent to a differential amplifier and then to the microcontroller for processing.

FIG. 12 illustrates an operational diagram of the smart band pair whereby one electrode in each is an RLD and biopotential data from both smart bands is first sent to a differential amplifier and then to the microcontroller for processing.

FIG. 13 illustrates an operational diagram of the smart band pair whereby one electrode in the secondary is a ground while one electrode in the primary’ is an RLD and biopotential data from both smart bands is sent directly to the microcontroller for processing.

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FIG. 14 illustrates an operational diagram of the smart band pair whereby one electrode in the secondary is a ground while one electrode in the primary is an RLD and biopotential data from both smart bands is first sent to a differential amplifier and then to the microcontroller for processing.

FIG. 15 illustrates the circuit diagram of a biopotential amplifier with a ground/RLD strip electrode implemented using Analog Devices AD8232 chip.

FIG. 16 illustrates a flowchart depicting the method of continuous ECG monitoring and HR/HRV analysis whereby biopotential data from both smart bands is sent directly to the microcontroller for processing.

FIG. 17 illustrates a flowchart depicting the method of continuous ECG monitoring and HR/HRV analysis whereby biopotential data from both smart bands is first sent to a differential amplifier and then to the microcontroller for processing.

FIG. 18 illustrates examples of various locations on the human body where wearables employing the underlying design and principle of the current invention can be attached to undertake continuous leadless ECG monitoring.

FIG. 19 illustrates an example operational diagram of the smart band pair in a further embodiment using fusion of DSP and analog signal conditioning techniques.

FIG. 20 illustrates fusion of two complementary techniques, namely, DSP and analog signal conditioning to obtain a high-fidelity ECG signal.

FIG. 21 illustrates a flowchart depicting one example method of continuous high-fidelity ECG monitoring and HR/HRV analysis via fusion of two complementary techniques, namely, DSP and analog signal conditioning.

FIG. 22 illustrates an example operational diagram of the smart band pair for leadless ECG monitoring via electrode switching.

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FIGS. 23/1-235 illustrates a truth table enlisting all possible states of the six electrode switches for electrode switching.

FIG. 24 illustrates a flowchart depicting one example method of continuous high-fidelity ECG monitoring and HR/HRV analysis via electrode switching.

DETAILED DESCRIPTION

A preferred embodiment of the present invention will be set forth in detail with reference to the drawings, in which like reference numerals refer to like elements or method steps throughout.

FIG. 1 illustrates an exemplary attachment of the wireless smart band pair on a user for continuous leadless ECG monitoring along with external devices to which data is wirelessly transmitted. In this example, the primary’ smart band 102 is worn by the user 104 around the left wrist whereas the secondary smart band 106 is worn around the right wrist. The heart 108 is shown inside the chest cavity' positioned slightly towards the left. The secondary’ smart band 106 wom around the right wrist measures the right-side biopotential by virtue of the electrodes provided on its underside (not shown) and sends this information wirelessly to the primary’ smart band 102 worn around the left wrist. Simultaneously, the primary smart band 102 wom around the left wrist measures the left-side biopotential by virtue of the electrodes provided on its underside (not shown) and combines/processes this information with the wirelessly received right-side biopotential information to acquire high-fidelity ECG waveform data. The primary’ smart band 102 analyzes the acquired ECG w’aveform data, stores all information locally, and also transmits this information wirelessly to remote devices 110 like smartphones, laptops, tablets, and cloud databases for storage and further analysis. The primary’ 102 and secondary’ 106 smart bands can also be swapped between the two hands to acquire ECG waveform data in a manner similar to the one described above. That is, the primary smart band 102 can be also worn around the right wrist and the secondary’ smart band 106 can also be wom around the left wrist for continuous leadless ECG monitoring as outlined in the invention.

FIGS. 2A-2C illustrate one embodiment of the front, side, and back of the primary’ smart band showing the touchscreen display along with the rigid/flexible strip electrodes and clasping studs/holes. The primary’ smart band comprises an enclosure 202 made of stainless steel, a

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WO 2020/181367 PCT/CA2020/050304 touchscreen display 204, upper 206 and lower 208 straps made of flexible rubber, and an on/off button 210. Studs 212 made of hard rubber and corresponding holes 214 are provided on the primary’ smart band straps for clasping it snugly around the wrist. It will be appreciated that while two sets of studs 212 and holes 214 are shown, a single set, multiple sets or other arrangements could be used instead. It will also be appreciated that the display 204 could be a plain display that is not a touchscreen.

Three rigid strip electrodes 216, 218, 220 and three flexible strip electrodes 222, 224, 226 are provided on the underside of the primary smart band. The three rigid strip electrodes 216,218, 220 are embedded in the primary’ smart band backplate 228 that is made of plastic. The three flexible strip electrodes 222, 224,226 are embedded in the upper 206 and lower 208 straps of the smart band. Each of the three rigid 216, 218, 220 and flexible 222, 224, 226 strip electrodes are electrically connected inside the primary smart band. That is rigid strip electrode 216 is connected to flexible strip electrode 222, rigid strip electrode 218 is connected to flexible strip electrode 224, and rigid strip electrode 220 is connected to flexible strip electrode 226. In one example, the rigid strip electrodes 216, 218,220 are made of silver while the flexible strip electrodes 222, 224,226 are made of silver foil. In another example, the rigid strip electrodes 216, 218, 220 are made of chrome-plated steel while the flexible strip electrodes 222, 224, 226 are made of conductive fabric. A variety of conductive materials can be used to fabricate the rigid and flexible strip electrodes described in this invention.

In one example, the approximate dimensions of the primary’ smart band enclosure 202 are 43.0 mm (length) x 42.0 mm (width) x 9.5 mm (height). The width of the straps 206, 208 is approximately 41.0 mm and closely matches the length of the smart band enclosure 202. The approximate width of the rigid 216, 218, 220 and flexible 222, 224, 226 strip electrodes is 8.5 mm and the approximate separation between them is 5.5 mm. In this example, the 5.5 mm gap between the flexible strip electrodes 222, 224,226 conveniently allows for the primary- smart band clasping studs 212 and holes 214 to be provided within this gap. The approximate weight of such a primary smart band is 40 g.

FIGS. 3A-3C illustrate one embodiment of the front, side, and back of the secondary smart band showing the front cover along with the rigid/flexible strip electrodes and clasping studs/holes. The design, footprint, materials, dimensions, weight, and fabrication of the secondary’ smart band is similar to that of the primary’ smart band. The only difference is that the secondary smart band does not have a display. In this example, the secondary’ smart band comprises an enclosure 302 made of £1

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WO 2020/181367 PCT/CA2020/050304 stainless steel, a plastic front cover 304, upper 306 and lower 308 straps made of flexible rubber, and an on/offbutton 310. It also comprises three rigid strip electrodes 312,314,316 embedded in aplastic backplate 318 and three flexible strip electrodes 320,322,324 embedded in the upper 306 and lower 308 straps. Studs 326 made of hard rubber and holes 328 are provided on the secondary smart band straps for clasping it snugly around the wrist. It will be appreciated that while two sets of studs 212 and holes 214 are shown, a single set, multiple sets or other arrangements could be used instead.

There are several advantages of the disclosed rigid and flexible strip electrodes over isolated and/or small footprint electrodes proposed in prior art. First, the surface area of each electrode is maximized to improve overall connectivity around the wrist. Second, since each electrode touches the skin all around the wrist, its reliability of coming in contact with the skin at all times (for example, during sleep) is significantly higher. Finally, by forming a connection all around the wrist, the dependence of each electrode’s performance on its physical position around the wrist is minimized. Therefore, the smart band pair described in this invention, by virtue of its rigid and flexible strip electrodes, is able to acquire good quality ECG waveform data with a high degree of accuracy.

FIG. 4 illustrates an alternate view of the primary’ smart band showing the touchscreen display along with the straps, clasping mechanism, and flexible strip electrodes. The profile shape of the primary’ smart band straps 206, 208 is curved, and they’ provide a snug fit around the wrist using the stud 212 and hole 214 clasping mechanism. When worn around the wrist, the rigid strip electrodes (not shown) and the flexible strip electrodes 222, 224, 226 embedded in the straps 206, 208 make contact with the skin all around the wrist. The primary smart band is switched on by activating the on/offbutton 210. The touchscreen display 204 helps in visualizing ECG waveform data and its analysis in realtime. In one example, the touchscreen display 204 displays real-time ECG waveform data along with HR/HRV metrics and pertinent alarms when these metrics are out of range. In another example, the user can interact with the touchscreen display 204 to perform tasks like reviewing historic ECG waveform data and/or sending a distress signal to other connected users/devices.

FIG. 5 illustrates an alternate view of the secondary’ smart band showing the front cover along with the straps, clasping mechanism, and flexible strip electrodes. The profile shape of the secondary’ smart band straps 306,308 is curved, and they provide a snug fit around the wrist using the stud 326 and hole 328 clasping mechanism. When worn around the wrist, the rigid strip electrodes (not shown) and the flexible strip electrodes 320, 322, 324 embedded in the straps 306, 308 make contact with the skin all around the wrist. The secondary’ smart band is switched on by activating the on/offbutton 12

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310. In place of a touchscreen display, in this embodiment the secondary’ smart band is provided with a plastic front cover 304.

FIG. 6 illustrates an exploded view of the primary’ smart band showing the key components in one embodiment. These include a touchscreen display 204, printed circuit board 602 containing all related hardware and running the desired software, enclosure 202, rechargeable battery’ 604, backplate 228 with embedded rigid strip electrodes 216, 218, 220 and straps 206,208 with flexible strip electrodes 222, 224, 226 and clasping holes 214.

FIG. 7 illustrates an exploded view of the secondary’ smart band showing the key components in one embodiment. These include a plastic front cover 304, printed circuit board 702 containing all related hardware and running the desired software, enclosure 302, rechargeable battery 704, backplate 318 with embedded rigid strip electrodes 312,314,316 and straps 306,308 with flexible strip electrodes 320,322,324 and clasping holes 328.

In one example, desired components of the primary (FIG. 6) and secondary (FIG. 7) smart bands are provided with clipping mechanisms enabling them to be snap fitted.

FIG. 8 illustrates the smart band pair being charged on a twin wireless charging unit. Both primary’ 102 and secondary 106 smart bands are provided with rechargeable batteries 604, 704 and wireless charging hardware/software. The smart band pair 102, 106 can therefore be charged on a twin wireless charging unit 802. It will be appreciated that other charging arrangements, including wired, could also be used.

FIG. 9 illustrates an example operational diagram of the smart band pair whereby one electrode in each is a ground and biopotential data from both smart bands is sent directly to the microcontroller for processing. In this example, the secondary’ smart band 106 is attached to a user’s right wrist and the primary’ smart band 102 is attached to the user’s left wrist.

In FIG. 9, in the secondary smart band 106, the three rigid strip electrodes 312, 314, 316 and the three flexible strip electrodes 320,322,324 are electrically connected. Similarly, in the primary’ smart band 102, the three rigid strip electrodes 216, 218, 220 and the three flexible strip electrodes 222, 224,226 are electrically connected.

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Referring to FIG. 9, the secondary smart band 106 comprises three strip electrodes namely ground 312,320, right 314, 322, and left 316, 324 electrodes that are connected to biopotential amplification and conditioning circuitry 902 via three digital switches Sgs, Srs, &s. Similarly, the primary’ smart band 102 comprises three strip electrodes namely ground 216, 222, right 218, 224, and left 220,226 electrodes that are connected to biopotential amplification and conditioning circuitry 904 via three digital switches Sgp, Srp, Slp.

As shown in FIG. 9, the right-side biopotential signal (Vr) measured by the secondary’ smart band ground 312,320, right 314, 322, and left 316, 324 electrodes is acquired by the microcontroller 906 via an analog-to-digital (A/D) converter 908. Using the radio transceiver 910 and antenna 912, the microcontroller906 wirelessly sends the right-side biopotential signal (Vr) to the primary’ smart band 102 attached to the user’s left wrist. The primary’ smart band microcontroller 914 wirelessly receives the right-side biopotential signal ( Vr) via its radio transceiver 916 and antenna 918. At the same time, the left-side biopotential signal (Vl) measured by the primary’ smart band ground 216,222, right 218, 224, and left 220, 226 electrodes is also acquired by the primary’ smart band microcontroller 914 via an A/D converter 920. The primary’ smart band microcontroller 914 then processes and combines the biopotential signals Vr and Vl to produce a high-fidelity ECG signal. In its simplest form, a singlelead ECG signal (F7) is synthesized by the smart band microcontroller 914 as per equation 1:

V^Vl-Vr (1)

In FIG. 9, the acquired ECG signal Vj and related analytics are stored inside memory 922 and all related information is displayed in real-time on the touchscreen display 204 of the primary’ smart band 102. Moreover, the primary smart band 102 also wirelessly transmits all ECG-related information via its radio transceiver 916 and antenna 918 to external devices 110 like smartphones, PCs, and tablets.

FIG. 10 illustrates an example operational diagram of the smart band pair whereby one electrode in each is an RLD and biopotential data from both smart bands is sent directly' to the microcontroller for processing. In this example, the secondary’ smart band 106 is attached to user’s right wrist and the primary’ smart band 102 is attached to user’s left wrist.

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In FIG. 10, the secondary smart band strip electrodes 312,320,314, 322, 316, 324 and the primary smart band strip electrodes 216, 222, 218, 224, 220, 226 are connected in a manner similar to that described for FIG 9.

As shown in FIG. 10, the secondary’ smart band 106 comprises three strip electrodes namely RLD 312, 320, right 314, 322, and left 316, 324 electrodes that are connected to biopotential amplification/conditioning circuitry 902 and RLD circuitry 1002 via three digital switches Sds, Srs, Sls. Similarly, the primary·· smart band 102 comprises three strip electrodes namely RLD 216, 222, right 218, 224, and left 220, 226 electrodes that are connected to biopotential amplification/conditioning circuitry' 904 and RLD circuitry 1004 via three digital switches Sdp, Srp, Slp·

Referring to FIG. 10, the method for single-lead ECG waveform data acquisition is similar to that described for FIG. 9. The only difference is that the quality and fidelity of the acquired ECG signal is further augmented by virtue of the RLD electrodes 312, 320, 216, 222 and circuitry 1002,1004 that minimize common mode noise.

FIG. 11 illustrates an example operational diagram of the smart band pair whereby one electrode in each is a ground and biopotential data from both smart bands is first sent to a differential amplifier and then to the microcontroller for processing. In this example, the secondary’ smart band 106 is attached to user’s right wrist and the primary smart band 102 is attached to user’s left wrist.

In FIG. 11, the secondary’ smart band strip electrodes 312, 320,314, 322, 316, 324 and the primary’ smart band strip electrodes 216, 222, 218, 224, 220, 226 are connected in a manner similar to that described for FIG 9.

As shown in FIG. 11, the secondary smart band 106 comprises three strip electrodes namely ground 312,320, right 314,322, and left 316,324 electrodes that are connected to biopotential amplification and conditioning circuitry 902 via three digital switches Sgs, Srs, Sls- Similarly, the primary' smart band 102 comprises three strip electrodes namely ground 216,222, right 218, 224, and left 220,226 electrodes that are connected to biopotential amplification and conditioning circuitry 904 via three digital switches Sgp, Srp, Slp.

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Referring to FIG. 11, similar to the method described for FIG. 9, the primary smart band microcontroller 914 wirelessly receives the right-side biopotential signal ( Vr) via its radio transceiver 916 and antenna 918. The microcontroller 914 then sends this signal via a digital-to-analog (D/A) converter 1102 to a differential amplifier 1104. At the same time, this differential amplifier 1104 also receives the left-side biopotential signal (K) measured by the primary smart band strip electrodes 216, 222, 218, 224, 220, 226 in conjunction with the biopotential amplification and conditioning circuitry 904. The primary smart band microcontroller 914 then acquires the amplified ECG signal output from the differential amplifier 1104 via the A/D converter 920. This highlights another method for amplifying the biopotential signals Vr and V_L for obtaining a high-quality ECG signal.

FIG. 12 illustrates an example operational diagram of the smart band pair whereby one electrode in each is an RLD and biopotential data from both smart bands is first sent to a differential amplifier and then to the microcontroller for processing. In this example, the secondary smart band 106 is attached to user’s right wrist and the primary smart band 102 is attached to user’s left wrist.

In FIG. 12, the secondary’ smart band strip electrodes 312,320,314, 322, 316, 324 and the primary’ smart band strip electrodes 216, 222, 218, 224, 220, 226 are connected in a manner similar to that described for FIG 9.

As shown in FIG. 12, the secondary’ smart band 106 comprises three strip electrodes namely RLD 312, 320, right 314, 322, and left 316, 324 electrodes that are connected to biopotential amplification/conditioning circuitry 902 and RLD circuitry 1002 via three digital switches Sds, Srs, Sls- Similarly, the primary·· smart band 102 comprises three strip electrodes namely RLD 216, 222, right 218, 224, and left 220, 226 electrodes that are connected to biopotential amplification/conditioning circuitry' 904 and RLD circuitry 1004 via three digital switches Sdp, Srp, SlpReferring to FIG. 12, the method for single-lead ECG waveform data acquisition is similar to that described for FIG. 11. The only difference is that the quality and fidelity of the acquired ECG signal is further augmented by virtue of the RLD electrodes 312, 320, 216, 222 and circuitry 1002,1004 that minimize common mode noise.

FIG. 13 illustrates an example operational diagram of the smart band pair whereby one electrode in the secondary is a ground while one electrode in the primary’ is an RLD and biopotential data from 16

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WO 2020/181367 PCT/CA2020/050304 both smart bands is sent directly to the microcontroller for processing. In this example, the secondary’ smart band 106 is attached to user’s right wrist and the primary’ smart band 102 is attached to user’s left wrist.

In FIG. 13, the secondary smart band strip electrodes 312,320,314, 322, 316, 324 and the primary’ smart band strip electrodes 216, 222, 218, 224, 220, 226 are connected in a manner similar to that described for FIG 9.

As shown in FIG. 13, the secondary smart band 106 comprises three strip electrodes namely ground 312, 320, right 314, 322, and left 316, 324 electrodes that are connected to biopotential amplification/conditioning circuitry’ 902 via three digital sw itches S_GS, Srs, Sis On the other hand, the primary’ smart band 102 comprises three strip electrodes namely RLD 216, 222, right 218, 224, and left 220, 226 electrodes that are connected to biopotential amplification/conditioning circuitry’ 904 and RLD circuitry 1004 via three digital switches Sdp, Srp, Slp.

Referring to FIG. 13, the method for single-lead ECG waveform data acquisition is similar to that described for FIG. 9. The only difference is that the secondary’ smart band 106 comprises a ground electrode 312,320 while the primary smart band 102 comprises an RLD electrode 216,222 to further reduce noise and enhance quality and fidelity of the acquired ECG signal.

FIG. 14 illustrates an example operational diagram of the smart band pair whereby one electrode in the secondary is a ground while one electrode in the primary’ is an RLD and biopotential data from both smart bands is first sent to a differential amplifier and then to the microcontroller for processing. In this example, the secondary smart band 106 is attached to user’s right wrist and the primary’ smart band 102 is attached to user’s left wrist.

In FIG. 14, the secondary’ smart band strip electrodes 312, 320,314, 322, 316, 324 and the primary’ smart band strip electrodes 216, 222, 218, 224, 220, 226 are connected in a manner similar to that described for FIG 9.

As shown in FIG. 14, the secondary smart band 106 comprises three strip electrodes namely ground 312, 320, right 314, 322, and left 316, 324 electrodes that are connected to biopotential amplification/conditioning circuitiy 902 via three digital sw itches S_Gs, Srs, Sis. On the other hand, the primary’ smart band 102 comprises three strip electrodes namely RLD 216, 222, right 218, 224, 17

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WO 2020/181367 PCT/CA2020/050304 and left 220, 226 electrodes that are connected to biopotential amplification/conditioning circuitry’ 904 and RLD circuitry’ 1004 via three digital switches Sdp, Srp. Slp.

Referring to FIG. 14, the method for single-lead ECG waveform data acquisition is similar to that described for FIG. 11. The only difference is that the secondary smart band 106 comprises a ground electrode 312,320 while the primary’ smart band 102 comprises an RLD electrode 216,222 to further reduce noise and enhance quality and fidelity of the acquired ECG signal.

In the examples shown in FIGS. 9-14, switches S_GP/S_Dp, S_RP, S_LP are provided for primary smart band strip electrodes 216, 222, 218, 224, 220, 226 and switches ScsSds, Srs, Sls&k provided for secondary’ smart band strip electrodes 312, 320, 314, 322, 316, 324. This allows for different electrode configurations and connections to be used for each smart band to minimize signal-to-noise ratio (SNR), thus further enhancing ECG signal quality. This feature is useful for device testing and calibration whereby related hardware/software can be fine-tuned to obtain optimum signal quality.

A truth table in Table 1 below summarizes all possible electrode configurations and connections that can be used on each smart band to optimize and augment ECG signal quality’. In Table 1, S_G is the ground electrode switch, Sd is the RLD electrode switch, Sl is the left electrode switch, and & is the right electrode switch of the primary’ and/or secondary’ smart band. The on state of an electrode switch is represented by true (7) while the off state of an electrode switch is represented by false (F).

<td> Sg/Sd</td><td> Sl</td><td> S_R</td>

<td> t</td><td> F</td><td> F</td>

<td> F</td><td> T</td><td> F</td>

<td> F</td><td> F</td><td> T</td>

<td> T</td><td> T</td><td> F</td>

<td> T</td><td> F</td><td> T</td>

<td> F</td><td> T</td><td> T</td>

<td> T</td><td> T</td><td> T</td>

<td> F</td><td> F</td><td> F</td>

FIG. 15 illustrates an example circuit diagram of a biopotential amplifier with an RLD strip electrode implemented using Analog Devices AD8232 chip. The biopotential amplifiers described in FIG. 914, can be easily implemented using commercially available ECG analog front ends like the AD8232 chip 1502. The disclosed circuit diagram shows the values of various electronic components and the

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FIG. 16 illustrates a flowchart depicting one example method of continuous ECG monitoring and HR/HRV analysis whereby biopotential data from both smart bands is sent directly to the microcontroller for processing. At step 1602 both primary’ 102 and secondary’ 106 smart bands are switched on using buttons 210 and 310. At step 1604 the microcontroller 914 inside the primary’ smart band checks whether biopotential data that is wirelessly received from the secondary smart band 106 and the biopotential data that is received via A/D converter of the primary’ smart band 102 is valid. If the data in step 1604 is found to be valid, the primary smart band 102 waits for this data to be ready for processing at step 1606. Once all biopotential data is ready, the primary’ smart band microcontroller 914 performs various analyses like digital filtering and other mathematical operations on this data at step 1608 to produce high-fidelity ECG w aveform data. At step 1610, the primary’ smart band microcontroller 914 detects ECG R-peaks and then at step 1612 it computes metrics like HR and HRV. In this example, at step 1614, the primary smart band microcontroller 914 checks the calculated HR/HRV metrics against predefined acceptable values. Based on whether the calculated HR/HRV parameters are in range or out of range, alarm flags are accordingly set at steps 1616 and 1618. At step 1620, the primary’ smart band touchscreen display 204 shows ECG waveform data and related analytics along with the alarm status in real-time. Moreover, at step 1620, the primary smart band wirelessly transmits all ECG waveform data and related analytics to third-party’ devices 110.

FIG. 17 illustrates an example flowchart depicting the method of continuous ECG monitoring and HR/HRV analysis whereby biopotential data from both smart bands is first sent to a differential amplifier and then to the microcontroller for processing. This flowchart describes a method for ECG w’aveform data acquisition and analysis that is similar to that described for FIG. 16. The main difference is that at step 1704 the primary smart band microcontroller 914 checks for the validity of the amplified primary’ and secondary’ smart band biopotential data that it receives from the differential amplifier 1104 inside the primary’ smart band 102.

FIG. 18 illustrates examples of various locations on the human body where wearables employing the underlying design and principle of the current invention can be attached to undertake continuous leadless ECG monitoring. As illustrated at 1802, the primary' smart band 102 can be worn around the 19

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WO 2020/181367 PCT/CA2020/050304 left wrist while a secondary smart band 1804 can be worn around the right upper arm. As illustrated at 1808, a primary smart band 1806 can be worn around the left upper arm while the secondary’ smart band 1804 can be worn around the right upper arm. Finally, as illustrated at 1810, the primary smart band 102 can be worn around the right wrist while a secondary’ smart band 1812 can be worn around the left ankle. These examples demonstrate that the disclosed wireless smart band pair and/or other similar wearable pair can be attached at various locations along the four limbs to accomplish leadless Einthoven-type single-lead ECG measurements.

Fusion of DSP and Analog Signal Conditioning Techniques

FIG. 19 illustrates an example operational diagram of the smart band pair. Here, the reference electrode in each smart band is either a ground or RLD. Biopotential data from both smart bands is sent directly and also via a differential amplifier to the primary’ smart band’s microcontroller for processing. In this example, the secondary’ smart band 106 is attached to a user’s right w rist while the primary smart band 102 is attached to the user’s left wrist.

Referring to FIG. 19, the secondary smart band 106 comprises three strip electrodes namely ground or RLD 312, 320, right 314, 322, and left 316, 324 electrodes that are connected to biopotential amplification and conditioning circuitry 902 via three digital switches Sds, Srs, Sls. Similarly, the primary smart band 102 comprises three strip electrodes namely ground or RLD 216,222, right 218, 224, and left 220, 226 electrodes that are connected to biopotential amplification and conditioning circuitry’ 904 via three digital switches Sdp, Srp, Slp. The secondary’ smart band switches Sds, Srs, Sls are controlled by the secondary smart band microcontroller 1910 while the primary’ smart band switches Sdp, Srp, Slp are controlled by the primary’ smart band microcontroller 1916.

In FIG. 19, Sdp in the primary’ smart band 102 and Sds in the secondary’ smart band 106 are changeover switches with tw o binary states, namely, 0 and 1. In state 0, they convert their respective electrodes to ground electrodes via grounding whereas in state 1, they’ convert their respective electrodes to RLD electrodes via the amplifiers 1906 and 1908. This allows for various combinations of ground and RLD electrodes to be readily used in the primary’ and secondary’ smart bands to reduce noise and enhance ECG signal quality.

Referring to FIG. 19, switches Srp and Slp are provided for primary’ smart band strip electrodes 218,224,220,226 and sw itches Srs and Sls are provided for secondary smart band strip electrodes 314,322,316,324. Again, these switches have two binary’ states, namely, 0 and 1. A state 0 will 20

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WO 2020/181367 PCT/CA2020/050304 remove these electrodes from the ECG monitoring circuit whereas a state 1 will connect these electrodes to the ECG monitoring circuit. This allows for different electrode configurations and connections to be used for each smart band to minimize signal-to-noise ratio (SNR), thus further enhancing ECG signal quality.

In one example, if states of Sds, Sls, Srs, Sdp, Slp, and Srp are 1, then secondary’ and primary’ smart band strip electrodes 314,322, 316, 324,218, 224, 220, and 226 will be involved in ECG waveform data monitoring wherein the reference electrodes 312,320,216, and 222 will act as RLD electrodes. In another example, if states of S_DS, S_LS, and Srp are 0 while states of S_DP, and Slp are 1, then secondary’ and primary smart band strip electrodes 314, 322, 220, and 226 will be involved in ECG waveform data monitoring wherein the reference electrodes 312, 320 will act as ground electrodes and reference electrodes 216, 222 will act as RLD electrodes. In addition to reducing noise, the switching feature is also very useful for device testing and calibration whereby related hardware/software can be fine-tuned to obtain optimum signal quality.

As shown in FIG. 19, the right-side biopotential signal (Vr) measured by the secondary’ smart band electrodes 312, 320, 314, 322, 316, and 324 is acquired by the microcontroller 1910 via an analogto-digital (A/D) converter 1912. Using the radio transceiver 1915 and antenna 1914, the microcontroller 1910 wirelessly sends the right-side biopotential signal (Vr) to the primary’ smart band 102 attached to the user’s left wrist. The primary smart band microcontroller 1916 wirelessly receives the right-side biopotential signal (Vr) via its radio transceiver 1918 and antenna 1920. At the same time, the left-side biopotential signal (H) measured by the primary smart band electrodes 216,222,218,224,220,226 is also acquired by the primary smart band microcontroller 1916 via an A/D converter 1922. Additionally, the left-side biopotential signal (Vl) is fed to the first terminal of a differential amplifier 1924 inside the primary smart band 102. Moreover, the right-side biopotential signal (Vr) from the primary’ smart band microcontroller 1916 is fed via a D/A converter 1926 to the second terminal of the differential amplifier 1924. The differential amplifier 1924 output (Fo^) is then acquired by the primary’ smart band microcontroller 1916 via the A/D converter 1928.

In reference with FIG. 19, the primary smart band microcontroller 1916 employs various DSP techniques on the biopotential signals Vr and Vl to produce a high-fidelity ECG signal. Based on equation 1, in one example, a single-lead ECG signal (ECGotgitai) is synthesized by the primary’ smart band microcontroller 1916 by computing the difference between the biopotential signals Vr and Vl as per equation 2:

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ECG_DigM = (Vl - Vr) (2)

In another example, a single-lead ECG signal (ECGDigitai) is synthesized by the primary’ smart band microcontroller 1916 by computing the weighted mean of the biopotential signals Vr and Vl using respective weights W_R and W_L as per equation 3:

„„ .(WWW tCG_DlgUal - ₊ (3)

In yet another example, a single-lead ECG signal (ECGd,^) is synthesized by the primary smart band microcontroller 1916 by computing a convolution between the biopotential signals V_R and V_Las péréquation 4, whereby n is the number of samples in the Vr and Vl arrays:

oo

ECG_Digital[n] = F_s[n] ^[n] = £ ^[*1·^ - A] (4) k=—co

As per FIG. 19, the primary smart band microcontroller 1916 also receives the signal V_Dlj^ which is the result of the analog signal amplification and conditioning of V_R and V_L via the differential amplifier 1924. Therefore, the high-fidelity analog ECG signal (ECGAnaiog), can be defined via equation 5 as follows:

ECGAndog = Voff (5)

ECG_DlgItal (equations (2)-(4) and FIG. 19) and ECG Analog (equation (5) and FIG. 19) represent highfidelity ECG signals that are obtained via two very distinct and complementary’ techniques - DSP and analog signal conditioning respectively.

In one example, the primary’ smart band microcontroller 1916 (FIG. 19) combines and fuses the ECGoigitai and ECGAnaiog signals to further suppress noise and obtain an even higher quality and fidelity signal, namely, ECGrusion.

The concept of fusion of complementary’ ECG signals (ECGoigttai and ECGAnaiog) to obtain a higher fidelity ECG signal (ECGfusk»,) can be explained via FIG. 20 and represented by equation 6:

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<img file="CA3132984C_D0001.tif" />

ECGp_uston (6)

There are several other ways by which ECG_Fusim, can be computed. In one example, ECG_F^_lon is computed as an arithmetic mean of ECGd,#^ and ECG_Anaiog as per equation (7):

_err _ECG_Dtgltal + ECG_Analogt,L(jp_uston--------------The biopotential amplifiers described in FIG. 19, can be easily implemented using commercially available ECG analog front ends like the AD8232 chip 1102. The disclosed circuit diagram of FIG. 15 shows the values of various electronic components and the primary’ smart band strip electrodes 216, 222, 218, 224, 220, 226 connected to the AD8232 chip 1102.

FIG. 21 illustrates a flowchart depicting one example method of continuous high-fidelity ECG monitoring and HR/HRV analysis via fusion of two complementary techniques, namely, DSP and analog signal conditioning. At step 2102 both primaiy 102 and secondary’ 106 smart bands are switched on using buttons 210 and 310 At step 2104 the microcontroller 1916 inside the primary’ smart band checks whether biopotential data Fr that is wirelessly received from the secondary’ smart band 106, the biopotential data Vl that is received from amplifier 904 via A/D converter 1922, and biopotential data Fp^that is received from the differential amplifier 1924 via A/D converter 1928 is valid. If all data in step 2104 is found to be valid, the primary smart band 102 waits for this data to be ready for processing at step 2106. Once all biopotential data is ready, the primary’ smart band microcontroller 1916 performs various computations like digital filtering, differencing, convolution, fusion, and other mathematical operations on this data at step 2108 to produce high-fidelity ECG waveform data. At step 2110, the primary’ smart band microcontroller 1916 detects ECG R-peaks and then at step 2112 it computes metrics like HR and HRV. In this example, at step 2114, the primary smart band microcontroller 1916 checks the calculated HR/HRV metrics against predefined acceptable values. Based on whether the calculated HR/HRV parameters are in range or out of range, alarm flags are accordingly set at steps 2116 and 2118. At step 2120, the primary’ smart band touchscreen 204 displays ECG waveform data and related analytics along with the alarm status in real-time. Moreover, at step 2120, the primaiy' smart band wirelessly transmits all ECG waveform data and related analytics to third-party devices 110.

Electrode Switching

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FIG. 22 illustrates an example operational diagram of the smart band pair. Here, the reference electrode in each smart band is either a ground or RLD. Biopotential data from both smart bands is sent directly and also via a differential amplifier to the primary’ smart band’s microcontroller for processing. In this example, the secondary’ smart band 106 is attached to a user’s right wrist while the primary smart band 102 is attached to the user’s left wrist.

In FIG. 22, in the secondary smart band 106, the three rigid strip electrodes 312, 314, 316 and the three flexible strip electrodes 320,322,324 are electrically connected. Similarly, in the primary’ smart band 102, the three rigid strip electrodes 216, 218, 220 and the three flexible strip electrodes 222, 224, 226 are electrically connected.

Referring to FIG. 22, the secondary’ smart band 106 comprises three strip electrodes namely ground or RLD 312, 320, right 314, 322, and left 316, 324 electrodes that are connected to biopotential amplification and conditioning circuitry 902 via three digital switches Sds, Srs, Sls. Similarly, the primary’ smart band 102 comprises three strip electrodes namely ground or RLD 216,222, right 218, 224, and left 220, 226 electrodes that are connected to biopotential amplification and conditioning circuitry 904 via three digital switches Sdp, Srp, Slp. The secondary’ smart band switches Sds, Srs, Sls are controlled by the secondary smart band microcontroller 2210 while the primary’ smart band switches Sdp, Srp, Slp are controlled by the primary’ smart band microcontroller 2216.

In FIG. 22, Sdp in the primary’ smart band 102 and Sds in the secondary’ smart band 106 are changeover switches with two binary states, namely, 0 and 1. In state 0, they convert their respective electrodes to ground electrodes via grounding whereas in state 1, they' convert their respective electrodes to RLD electrodes via the amplifiers 2206 and 2208. This feature allows for various combinations of ground and RLD electrodes to be readily used in the primary’ and secondary’ smart bands to reduce noise and enhance ECG signal quality.

Referring to FIG. 22, switches Srp and Slp are provided for primary smart band strip electrodes 218, 224, 220, 226 and switches Srs and ôï^are provided for secondary smart band strip electrodes 314,322,316,324. Again, these switches have two binary states, namely, 0 and 1. A state 0 will remove these electrodes from the ECG monitoring circuit whereas a state 1 will connect these electrodes to the ECG monitoring circuit. This allows for different electrode configurations and connections to be used for each smart band to minimize signal-to-noise ratio (SNR), thus further enhancing ECG signal quality.

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In one example, if states of Sds, Sls, Srs, Sdp, Slp, and Srp are 1, then secondary and primary smart band strip electrodes 314,322, 316, 324, 218, 224, 220, and 226 will be involved in ECG waveform data monitoring wherein the reference electrodes 312,320,216, and 222 will act as RLD electrodes.

In another example, if states of Sb$, Sls, and Srp are 0 while states of Srs, Sdp, and Slp are 1, then secondary’ and primary smart band strip electrodes 314, 322, 220, and 226 will be involved in ECG waveform data monitoring wherein the reference electrodes 312, 320 will act as ground electrodes and reference electrodes 216, 222 will act as RLD electrodes. In addition to reducing noise, the switching feature is also very useful for device testing and calibration whereby related hardware/software can be fine-tuned to obtain optimum signal quality.

In one embodiment, rapid switching of all six switches, namely, Sds, Sls, Srs, Sdp, Slp, and Srp is undertaken in such a manner that left and right side biopotential data is acquired, processed, and combined every data sampling period as the system continuously and repeatedly loops through all possible configurations of the switches. Since each switch has 2 states (0 and 1) and total number of switches are 6, there are 2⁶ = 64 unique configurations that are possible per data sampling period (FIGS. 23A-23B).

In one example, a truth table of the type shown in FIGS. 23A-23B is stored inside the primary’ smart band memory 2230 with the pointer 2302 at configuration # 1. As per configuration # 1 row, the desired states of the secondary’ smart band switches Sls, Srs, and Sos are wirelessly transmitted by the primary smart band microcontroller 2216 to the secondary’ smart band microcontroller 2210 employing radio transceivers 2218, 2212 and antennas 2220, 2214. The secondary’ smart band microcontroller 2210 then sets the states of switches Sls, Srs, and Sds based on the information received from the primary’ smart band microcontroller 2216. At the same time, the primary’ smart band microcontroller 2216 sets the states of switches S_Lp, Sr_P, and S_Dp as per configuration # 1 row. Once all six switches are set to the states described by configuration # 1 row, the secondary’ smart band 106 acquires biopotential data from the right wrist and transmits it wirelessly to the primary’ smart band 102 that also simultaneously acquires biopotential data from the from the left wrist. Then, the primary’ smart band microcontroller 2216 moves the pointer 2302 to the next row on the truth table (FIGS. 23A-23B) and the above procedure of setting of states of all six switches and biopotential data acquisition is repeated. A new data sampling period begins when the pointer 2302 resets (reaches configuration # 1 row) and ends when the pointer 2302 reaches configuration # 64 row. In this

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PCT/CA2020/050304 manner, left and right side biopotential data is continuously acquired by the smart bands 102,106 for all 64 switch configurations for every data sampling period.

In one example, the rapid switching described above can be undertaken by the primary- smart band microcontroller 2216 by utilizing its clock signal. In another example, a field programmable gate array (FPGA) module working in conjunction with the primary- smart band microcontroller 2216 can be employed to accomplish the rapid switching.

With reference to FIG. 22 and FIGS. 23A-23B, for each switch configuration, the right-side biopotential signal (Ri) measured by the secondary- smart band electrodes 312, 320, 314, 322, 316, and 324 is acquired by the microcontroller 2210 via an analog-to-digital (A/D) converter 2212. Using the radio transceiver 2212 and antenna 2214, the microcontroller 2210 wirelessly sends the rightside biopotential signal (Ri) to the primary- smart band 102 attached to the user’s left wrist. The primary smart band microcontroller 2216 wirelessly receives the right-side biopotential signal (Ri) via its radio transceiver 2218 and antenna 2220. At the same time, the left-side biopotential signal (Li) measured by the primary smart band electrodes 216,222, 218, 224,220, 226 is also acquired by the primary smart band microcontroller 2216 via an A/D converter 2222. Additionally, the left-side biopotential signal (Li) is fed to the first terminal of a differential amplifier 2224 inside the primaiysmait band 102. Moreover, the right-side biopotential signal (Ri) from the primary- smart band microcontroller 2216 is fed via a D/A converter 2226 to the second terminal of the differential amplifier 2224. The differential amplifier 2224 output (Vi) is then acquired by the primary- smart band microcontroller 2216 via the A/D converter 2228.

When biopotential data is acquired via the described switching method as a continuous stream and buffered over a period of time, there will be 64 right-side biopotential signals (Ri), 64 left-side biopotential signals (Li), and 64 analog differential signals (Vi). The primary smart band microcontroller 2216 can employ a number of techniques to aggregate and combine these 64 biopotential signals to produce higher fidelity biopotential signals. In one example, the 64 right-side biopotential signals (Ri) can be aggregated by computing their weighted mean using weights Wm as per equation 8, whereby total switch configurations c = 64:

v _{= (8)}

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Similarly, the 64 left-side biopotential signals (A) can be aggregated by computing their weighted mean using weights as per equation 9, whereby total switch configurations c = 64:

^L Σ^ο¹^ (9)

Finally, the 64 analog differential signals (V) can be aggregated by computing their weighted mean using weights Wv, as per equation 10, whereby total switch configurations c = 64:

^ν°^ι - yc-l_w

2.(=0 y/ (10)

In another embodiment, Rt, Li, and P'S can be aggregated by employing a log product as per equations 11-13, whereby total switch configurations c = 64:

<img file="CA3132984C_D0002.tif" />

(11) (12)

V_Din = (13)

With reference to FIG. 22 and aggregation equations 8-13, the primary’ smart band microcontroller 2216 can employ various DSP techniques on the biopotential signals Vr and Vl to produce a highfidelity ECG signal. In one example, a single-lead ECG signal (ECG Digital) is synthesized by the primary smart band microcontroller 2216 by computing the difference between the biopotential signals Vr and Vl as per equation 14:

ECGoignai = (Vl — Vr) (14)

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In another example, a single-lead ECG signal (ECG_DlgI^i) is synthesized by the primary smart band microcontroller 2216 by computing the weighted mean of the biopotential signals Vr and V_L using respective weights Wr and Wl as péréquation 15:

_err WM + w_Ry_R) ^u_{Dlgital +} (15)

In yet another example, a single-lead ECG signal (ECGrHgitd) is synthesized by the primary smart band microcontroller 2216 by computing a convolution between the biopotential signals Vr and Vl as péréquation 16, whereby n is the number of samples in the Vr and V_L arrays:

CO

ECG_DigUal [«1 = Vr [n] * V_L [n] = £ V_R [fc]. V_L [n - Λ] (16) k=-oo

As per FIG. 22 and aggregation equations 8-13, the primary smart band microcontroller 2216 also synthesizes the signal Vd,#, which is the result of the analog signal amplification and conditioning of R, and L, via the differential amplifier 2224. Therefore, the high-fidelity analog ECG signal (ECGAndog), can be defined via equation 17 as follows:

ECG.^alog = VDff (17)

ECG_Digital (equations (14)-(16)) and ECG_Anaro_S (equation (17)) represent high-fidelity ECG signals that are obtained via two very distinct and complementary’ techniques - DSP and analog signal conditioning respectively.

In one example, the primary’ smart band microcontroller 2216 (FIG. 22) combines and fuses the ECGoigitai and ECGjnaiog signals to further suppress noise and obtain an even higher quality’ and fidelity signal, namely, ECGf_iis1o„ as per equation 18:

ECG_Fuston — J(ECG_Diÿicar)² 4- (ECG_Analogf (18)

There are several other ways by which ECGrusian can be computed. In one example, ECGrusion is computed as an arithmetic mean of EC Goûtai and ECGAnaiog as péréquation (19):

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FC G + ECG_Ana(_Og tCup_USÎ_On 2 (19)

FIG. 24 illustrates a flowchart depicting one example method of continuous high-fidelity ECG monitoring and HR/HRV analysis via electrode switching. At step 2402 both primary’ 102 and secondary’ 106 smart bands are switched on using buttons 210 and 310. At step 2404 the microcontroller 2216 inside the primaiy smart band checks whether the pointer 2302 has reached the end of the truth table stored inside the primary’ smart band memory 2230. If pointer 2302 has not reached the end of the truth table at step 2404, then at step 2408, the states of all six switches are set as per the row indicated by the pointer, biopotential data acquisition is initiated, and the pointer is incremented by’ 1. However, if pointer 2302 has reached the end of the truth table at step 2404, then, at step 2406, the pointer is reset, and start/end of a sampling period is mariked. The above procedure continues in the main loop for all pointer positions and resets. At step 2410, the primary smart band microcontroller 2216 performs various operations on the received biopotential data like processing, aggregation, and fusion to produce high-fidelity ECG waveform data. At step 2412, the primary’ smart band microcontroller 2216 detects ECG R-peaks and then at step 2414 it computes metrics like HR and HRV. In this example, at step 2416, the primary’ smart band microcontroller 2216 checks the calculated HR/HRV metrics against predefined acceptable values. Based on whether the calculated HR/HRV parameters are in range or out of range, alarm flags are accordingly’ set at steps 2418 and 2420. At step 2422, the primaiy’ smart band touchscreen display 204 displays ECG waveform data and related analytics along with the alarm status in real-time. Moreover, at step 2422, the primary’ smart band wirelessly transmits all ECG waveform data and related analytics to third-party’ devices 110.

It will be appreciated by one skilled in the art that variants can exist in the above-described arrangements and applications.

For example, in one embodiment, the described smart band pair can also be used for intermittent ECG monitoring and analysis. For example, the user can operate the on/off switches 210,310 on the primary and secondary smart bands 102,106 to enable and disable ECG waveform data acquisition and analysis as required. In another example, the microcontrollers 910, 916, inside the primary and secondary’ smart bands 102, 106 can be programmed to acquire and analyze ECG w’aveform data at

CA 03132984 2021-09-07

WO 2020/181367 PCT/CA2020/050304 predefined intervals, for example, acquire and analyze ECG waveform data for 5 minutes every 30 minutes.

In another embodiment, the described smart band pair can be used solely for biopotential data acquisition and transmission while all data processing/analysis can be done on external devices. For example, the primary' smart band 102 can acquire and wirelessly transmit the first biopotential data to a smartphone and the secondary smart band 106 can acquire and wirelessly transmit the second biopotential data to the same smartphone. This smartphone can then process and combine the received first and second biopotential data to produce a high-fidelity ECG signal. The smartphone can also perform further analyses on the ECG signal like R-peak detection, HR/HRV evaluation, and alarm generation. The said smartphone can be replaced by a laptop, tablet, and/or any similar computing device.

In addition, while certain functions have been attributed to the primary smart band for the purpose of illustration in the foregoing description, it will be appreciated that the functions and abilities of the smart bands can be interchanged and/or shared between the primary’ and secondary smart bands.

The specific examples provided herein relate to a continuous leadless electrocardiogram monitor, however, the materials, methods of application and arrangements of the invention can be varied. The scope of the claims should not be limited by the preferred embodiments set forth in the examples but should be given the broadest interpretation consistent with the description as a whole.