Highly integrated watch for noninvasive continual glucose ...

Complete Design Overview of the Glucose Monitoring Watch

The design of this advanced glucose monitoring watch is depicted in Fig. 1. It features a vibrant LED display, a printed circuit board (PCB), a rechargeable power source, an innovative circular wristband, and a specialized glucose sensor patch (refer to Fig. 1a). The PCB, shaped to fit the watch face, integrates five essential functional components for system power management, signal processing, and wireless communication, resulting in a highly compact and efficient wearable electronic system (see Fig. 1b). The glucose sensor patch is made from a 100 µm thick polyimide (PI) film using microelectromechanical systems (MEMS) technology (refer to Fig. S1). This patch is securely attached to the watchband and conforms closely to the user's skin. Each patch incorporates two glucose sensors, comprised of a working electrode, a reference electrode, and a counter electrode (illustrated in Fig. 1c). Additionally, these sensors are equipped with extraction electrodes designed for the noninvasive uptake of interstitial fluid (ISF) from the skin. The process of biomarker extraction occurs transdermally through reverse iontophoresis (as shown in Fig. 1d), utilizing two mechanisms: electromigration and electroosmosis. When a controlled electric current is passed through the extraction electrodes, small molecular ions within the ISF migrate toward the electrode of opposite charge. Given that skin possesses a negative charge at physiological pH, it selectively allows the passage of positive ions, creating a flow of solvent that carries solutes, such as glucose and lactate, towards the cathode. The glucose extracted is subsequently measured by the adjacent sensor.

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a Exploded view of the device. b Diagram showcasing the PCB layout, highlighting each functional module, which includes (1) constant current supply, (2) A/D differential unit, (3) microcontroller, (4) Bluetooth module, and (5) power source. c Design of the flexible glucose sensor patch for the extraction of interstitial fluid (ISF) and glucose detection. d Mechanism of reverse iontophoresis employed for the noninvasive extraction of ISF via the glucose sensor patch. e System-level schematic of the watch, displaying the interaction between functional units and its user interface on a smartphone.

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The overall system architecture presented in Fig. 1e sheds light on the cooperative functionality of the glucose monitoring device. A rechargeable battery (3.3V) serves as the power reservoir for the system. The constant current source links to one end of each extraction electrode to provide the microampere level electric current (50 µA) essential for reverse iontophoresis. The glucose molecules obtained from the ISF are examined by the two sensors, generating a current that is transformed into a voltage signal, which is amplified by an instrumentation amplifier. Following this, the voltage signal is forwarded to an analog-to-digital converter (ADC), and the resulting digital signal forms the input for the microcontroller, which applies a calibration algorithm to determine the precise blood glucose level. Ultimately, this numerical reading is displayed on the watch's LED screen and transmitted to the user's smartphone via Bluetooth. Details of the circuit design can be found in the 'Methods and Materials' section, as well as in Figs. S13 and S14.

Features of the Glucose Sensor Technology

The fabrication of the glucose sensor patch occurred within our laboratory setup. After sputtering Au onto the PI film (for more details see the 'Methods and Materials' section), the counter electrodes were retained in their original state, while the other electrodes underwent additional modifications. Ag/AgCl ink was printed onto the extraction electrodes and reference electrodes. As for the working electrode, Prussian blue (PB) was first deposited on the Au electrode through an electrodeposition process, followed by a selective membrane overlay containing glucose oxidase (GOx) and carbon nanotubes, and concluded with a coating of Nafion (depicted in Fig. 2a, refer to 'Methods and Materials' for further analysis). When glucose is present, the following reaction is catalyzed by GOx:

$${\rm{glucose}}\,+\,{\rm{oxygen}}\,\mathop{\to }\limits^{{\rm{GO}}x}\,{\rm{hydrogen}}\,{\rm{peroxide}}\,+\,{\rm{gluconic}}\,{\rm{acid}}$$

a Layered structure of the sensor patch components. b The dual-step mechanism for glucose detection: glucose oxidase (GOx)-catalyzed glucose oxidation producing H2O2, followed by the reduction of H2O2 facilitated by Prussian blue (PB). This electrocatalyst PB responds to an electron loss during the reaction, resulting in an amperometric output. c Amperometric response readings of glucose sensor patches (SP#2, replicates 3) in contrast to those without (SP#1, replicates 3), during a two-week evaluation, exemplifying the stability of these sensors, particularly with the Nafion enhancement. Data presented represent the mean ± standard deviation of three trials. d A comparative analysis of the sensor sensitivity reduction percentages between SP#1 and SP#2, also depicting the mean ± s.d. of three trials. ***p<0.001 via Student's t-test. e Amperometric responses from SP#2 when measuring glucose against interfering substances like lactic acid (LA) and hyaluronic acid (HA).

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The product of this reaction, hydrogen peroxide (H2O2), is subsequently reduced by the PB transducer, generating an amperometric signal that mirrors the glucose concentration alterations (as demonstrated in Fig. 2b). The amperometric response is documented at a voltage of 0.1V relative to the reference electrode.

Two glucose sensor patches were characterized: one without a Nafion film (SP#1) and one equipped with it (SP#2). Both were subjected to testing in a controlled semi-infinite diffusion environment (see Fig. S3). The sensor patches were submerged in a bulk solution (100 mL) while being linked to an electrochemical workstation (refer to Fig. S4). The cyclic voltammetry curves and responses remained consistent across multiple trials (see Fig. S2). The amperometric responses of the glucose sensor patch (SP#2) indicated a linear diffusion behavior in the bulk glucose solution, noted for ISF glucose concentrations varying from 0 to 200 µM (see Fig. S5). The amperometric comparisons between SP#1 and SP#2 established readings of 1.40 and 2.42 nA/µM respectively, denoting a 40% increase in sensitivity attributed to the Nafion film application (as presented in Fig. 2c). Long-term studies conducted over a fortnight documented a 15% sensitivity decrease for SP#1 (1.40 to 1.06 nA/µM) against 8% for SP#2 (2.42 to 2.21 nA/µM) (refer to Fig. 2c, d). Further results from this long-term stability study are detailed in Fig. S6. The sensitivity decay observed in Nafion-coated sensors remained within 7.5% across all tested glucose concentrations. Collectively, these findings, alongside the amplified amperometric responses of SP#2, confirm the advantages conferred by the Nafion treatment. The selectivity of SP#2 was examined against potential interferents in ISF like lactic acid (LA) and hyaluronic acid (HA) (see Fig. 2e). SP#2 also exhibited excellent consistency in repeat tests with standard glucose solutions (refer to Fig. S7). The variability among the five measured results of the identical concentration did not exceed 7.6% of the mean (for 20 µM) across all five concentrations assessed.

In practical applications, the biofluid volume beneath the sensor and skin remains on a microscale (<5 µL). Consequently, the capture of glucose through the GOx selective membrane is better aligned with a finite diffusion model, thus generating distinct chronoamperometric response characteristics. To accommodate this factor, SP#2 was further characterized under microfluidic conditions. Upon introduction of four microliters of glucose solution to the sensor electrodes, an initial fluid thickness of around 80 µm was achieved (illustrated in Fig. 3a). The sensor patch was then connected to the electrochemical workstation (see Fig. S9). The recorded chronoamperometric responses for the sensors declined swiftly, reaching a steady near-zero output within 200 seconds across glucose concentrations spanning from 0 to 200 µM (Fig. 3b). This highlighted the need for an algorithm to calibrate the sensors' performance with microvolume solutions. A proposed calibration algorithm takes into account Fick's second law, the Cottrell equation applicable under a semi-infinite boundary, and the thin-layer electrochemical model. The conclusive current output i(t) can be formulated as:

$$i(t)=A\,{t}^{-b}$$

Here, A serves as a constant, and b represents a value influenced by the glucose concentration C. The variable b may show a direct correlation with C (b = kC) or an inverse relationship (b = k/C). A comprehensive derivation can be found in the 'Methods and Materials' section. The linear relationships of b and 1/b against varying glucose concentrations were plotted alongside the experimental data (see Fig. 3c), with the correlation coefficients depicted in Fig. 3d, demonstrating a superior correlation of b being directly proportional to glucose concentration (C) in ISF. Detailed data can be referenced in Table S2. The final calibration formula established is:

$$i(t)=A\,{t}^{-kC}.$$

a Schematic depiction of glucose monitoring within a thin-layer electrochemical model. b Current-time behavior of the sensors under 4 µL glucose solution at varying concentrations. c Linear correlation of b and 1/b against glucose concentration C. d A comparison of correlation coefficients related to the linear fittings displayed in (c). Data denote mean ± s.d. from three replicates. ***p<0.01 via Student's t-test.

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On-Body Evaluation of the Glucose Monitoring Device

For practical on-body testing, the glucose sensor patch is affixed on the inner side of the watchband, and a volunteer is instructed to don the wristwatch (see Fig. 4a, with Fig. S10 for reference). The operational sequence of the watch system is outlined in Fig. 4b. Initially, a calibration value sourced from a conventional glucose meter is introduced into the system, allowing the microcontroller to process the calibration algorithm and establish the constant value k. Subsequently, electric current is applied to the extraction electrodes to initiate reverse iontophoresis for a 15-minute interval, during which the microcontroller captures the signal output for one minute to determine the corresponding blood glucose level. In order to mitigate interference from other metabolites and electrolytes extracted, the remaining ISF is permitted to dissipate for an additional minute. The complete measurement cycle culminates in a total duration of 17 minutes, enabling the user to have their blood glucose checked approximately four times each hour.

a Image of a volunteer utilizing the watch displaying real-time blood glucose levels. b Workflow process of the glucose-monitoring device. c Blood glucose variation recorded by the watch throughout the day compared to actual blood glucose values (reference) acquired from finger-prick blood tests. d Assessing glucose concentrations pre- and post-meal taken from five volunteers. The data signifies mean ± s.d. from five trials. ***p<0.001 via Student's t-test. e Comparison of glucose concentrations as gauged by the watch against measurements from a commercial glucose meter made on 23 volunteers.

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In daily usage, the volunteer observed the watch for an approximate duration of 10 hours, during which blood glucose variations were meticulously documented (figure 4c). To evaluate the precision of the readings from the watch, the volunteer's blood glucose was also measured four times via fingerstick blood tests using a commercial glucose meter (the results are represented by black points in figure 4c). All tests except for the second were conducted promptly after meals. The readings from the watch, particularly the spikes, accurately mirrored the volunteer’s true blood glucose variations. A paired trial involving two volunteers (one diagnosed with diabetes and the other healthy) was executed to scrutinize the accuracy of consecutive measurements facilitated by the watch. Five fasting glucose assessments for each subject were performed within the span of 1.5 hours, yielding corresponding results that closely aligned with those from the fingerstick tests. This finding validates the reliability and replication of glucose measurements achieved by the device in the short term (see Fig. S8). This serves as supplementary evidence for repeatability of the iontophoresis function of the watch. Additional performance testing on another group of five volunteers indicated the device effectively recorded blood glucose elevations following meals (refer to Fig. 4d). To further assess the accuracy of glucose readings from the watch using an established criterion, the Clarke error grid was plotted using measurement data from 23 individuals (see Fig. 4e), comprising 13 diabetes patients and 10 without diabetes. The results and measurement statistics from the watch are documented in Fig. S11 and Table S3. The data points shown in zones A and B of the Clarke error grid signify clinically acceptable and reasonable readings that would not lead to inappropriate treatment decisions, confirming the watch's accuracy. Impressively, no measurement points fell into zone D or zone E, indicating the watch provides high-quality measurements without erroneous indicators. The data is predominantly concentrated in zones A (46.99%) and B (37.35%), culminating in an overall accuracy rate of 84.34% for blood glucose evaluations conducted with the watch. Furthermore, users consistently reported comfort while wearing the watch, likening their experience to that of typical smartwatches, with no significant discomfort such as skin irritation during glucose extractions. Even with a moderately snug watchband, the sensor patch maintained secure contact with the user’s wrist. To assure that everyday movements did not impair the watch's sensing capabilities, a comparative analysis was done using two watches: one placed on a static arm and the other on a moving arm of the same healthy volunteer. The difference in average results (six readings each) was noted to be 2.1% (see Fig. S12), paralleling the error margin of the same sensor during repeated measurements, thus confirming that normal daily motions do not interfere with the watch’s operational performance.

Set Up Your Continuous Glucose Monitoring on a Smartwatch

Connecting your CGM system to a smartwatch is a simple process. Here’s how you get started:

1.

First, ensure that your CGM system is compatible with your mobile device. For instance, you can verify the compatibility of your smart device with Dexcom G7.

For additional details about the oxygen smart watch, don't hesitate to connect with us.

here

. Afterward, download the

Dexcom G7 application

to monitor your glucose information.

2.

Next, ensure your smartphone is connected to your smartwatch. For example, ensure that you can receive alerts from your iPhone to your Apple Watch.

3.

Confirm that the Dexcom G7 app is installed on your smartwatch. Once linked, glucose data sent to your smartphone will also appear on your smartwatch display.

4.

To ensure seamless updates, maintain your smartphone within a 20-foot range of your transmitter while remaining close to your smartwatch.

Integrating CGM with your smartwatch allows effortless glucose monitoring with just a glance at your wrist. You gain the insights necessary to make informed adjustments for remaining within your target glucose levels. Through remote glucose monitoring, you and your family can make health-enhancing decisions throughout your daily activities.

Learn more about Dexcom's Continuous Glucose Monitoring Systems and their connectivity options with your compatible

Apple

or

Android

smartwatches. For assistance with setup or technical support, you can

visit our support resources

.

If you seek further information, please check out our smart watch that monitors blood sugar.