The glucose sensor patch was fabricated in the laboratory. For the working electrode, Prussian blue PB was first electrodeposited onto the Au electrode, followed by a drop-cast layer of selective membrane containing glucose oxidase GO x and carbon nanotubes, and finally topped with a drop-cast layer of Nafion Fig.

In the presence of glucose, GO x catalyzes the following reaction:. a Layer-by-layer diagram of sensor patch components. b The two-step mechanism of glucose detection: glucose oxidase GO x -catalyzed glucose oxidation, yielding H 2 O 2 , and Prussian blue PB -catalyzed H 2 O 2 reduction.

The electrocatalyst PB consumes an electron during the reaction, causing an amperometric response. c Amperometric responses of glucose sensor patches with SP 2, 3 replicates and without SP 1, 3 replicates Nafion film in the two-week test, demonstrating the long-term stability of the sensors, especially with Nafion modification.

Data represent the mean ± s. of three replicates. d Comparison of the percentage decrease in sensor sensitivity between SP 1 and SP 2. e Amperometric responses of SP 2 to glucose in contrast to interference components lactic acid LA and hyaluronic acid HA. The product species hydrogen peroxide H 2 O 2 is then reduced by the PB transducer, eliciting an amperometric response, which reflects the fluctuation in the glucose concentration Fig.

Two glucose sensor patches, one without SP 1 and one with SP 2 the topmost Nafion film, were first characterized in a semi-infinite diffusion environment Fig. The CV curves and electrochemical responses remained stable in repeated experiments Fig. The amperometric responses of SP 1 and SP 2 to glucose concentrations were measured at 1.

Further analyses of the long-term stability study are shown in Fig. The decay in the amperometric response of the Nafion-coated sensors was within 7. These results, together with the stronger absolute amperometric responses of SP 2, prove the advantages that Nafion modification delivers to the glucose sensors.

The selectivity of SP 2 was further verified against other interfering components in ISF, such as lactic acid LA and hyaluronic acid HA Fig. SP 2 also showed good reproducibility in repeated tests with standard glucose solutions Fig.

The range of the 5 measured results of the same concentration was no larger than 7. As a result, the capture of glucose by the GO x selective membrane is better described by a finite diffusion model, leading to a different chronoamperometric response pattern.

Considering this deviation, SP 2 was further characterized in a microfluidic scenario. Four microliters of glucose solution was applied to the sensor electrodes, resulting in an initial thickness of approximately 80 μm Fig. Then, the sensor patch was connected to the electrochemical workstation Fig.

Herein, a calibration algorithm is proposed. where A is a constant, and b is a value determined by the glucose concentration C. The detailed data are given in Table S2. The final calibration algorithm is:. a Schematic diagram of glucose monitoring in the thin-layer electrochemical model.

d Comparison of the correlation coefficients corresponding to the linear fits in c. For on-body testing, the glucose sensor patch was fixed on the inside of the watchband, and a volunteer was asked to wear the watch on the wrist Fig.

The workflow of the watch system is illustrated in Fig. A calibration value obtained from a commercial glucose meter is first input into the system for the microcontroller to execute the calibration algorithm and confirm the constant value k.

a Photograph of a volunteer wearing the watch with blood glucose levels displayed in real time. b Workflow of the glucose-monitoring watch. c The blood glucose variation curve of a volunteer measured by the watch during the daytime compared to true blood glucose values reference obtained from finger blood.

d Glucose concentrations before and after a meal measured by the watch from five volunteers. of five replicates. e Plot of glucose concentrations measured from 23 volunteers by the watch and by a commercial glucose meter.

All fingerstick blood tests except the second were performed immediately after meals. A two-volunteer 1 diabetic and 1 nondiabetic trial was conducted to assess the accuracy of consecutive measurements by the watch. Five fasting glucose levels of each volunteer were measured by the watch within 1.

The two types of results matched well for both volunteers, indicating good accuracy and reproducibility of glucose measurements by the watch in the short term Fig. This result also serves as circumstantial evidence of the reproducibility of the iontophoresis function in the watch.

We further tested the performance of the watch on five other volunteers, measuring their blood glucose levels before and after a meal. The watch successfully captured the increase in blood glucose levels after a meal Fig. To evaluate the accuracy of glucose measurements by the watch with a widely acknowledged criterion, the Clarke error grid was plotted using the measurement results obtained from 23 volunteers Fig.

The results and statistics of measurement by the watch are presented in Fig. S11 and Table S3. The percentage of data points in zone A and zone B of the Clarke error grid, which represents clinically accepted accurate readings and acceptable moderate readings that would not lead to inappropriate treatments, indicates the accuracy of the tested glucose meter.

Remarkably, no experimental data points fell in zone D or zone E, suggesting that the watch yields high-quality measurement results without misleading or false readings The data points are concentrated in zone A Additionally, all volunteers reported a comfortable wearing experience resembling that of commercial smartwatches, with no obvious sensational difference e.

To verify that daily body motions do not impair the sensing performance of the watch, we compared the measurement results from two watches, one worn on a static arm and the other on a moving arm, of the same nondiabetic volunteer.

The difference between the average results of six measurements each from the two watches was 2. S12 , comparable to the error of the same sensor between repeated measurements, indicating that daily body motions do not affect the performance of the watch.

In summary, we developed a highly integrated glucose monitoring watch and achieved noninvasive continual blood glucose monitoring with clinically acceptable accuracy. Reverse iontophoresis-based ISF extraction by a flexible glucose sensor patch allows painless glucose detection, and the watch-like design ensures comfortable daily wear, facilitating continual glucose monitoring.

Real-life testing of the watch on 23 volunteers revealed Subsequent efforts could be made in a few directions; for example, the accuracy could be improved by providing customized models to accommodate potentially interfering factors such as age, gender 38 , exercise 39 , and illness The PCB could be miniaturized and integrated into existing smartwatch models to create a truly noninvasive continuous glucose monitoring smartwatch.

All reagents were used as received. The fabrication of the electrodes is illustrated in Fig. First, the polyimide PI film was cleaned with acetone, ethanol, and ultrapure water. Then, the electrode and wire areas were defined by a photolithographed layer of positive photoresist AZ Finally, another layer of positive photoresist AZ was photolithographed onto the nonelectrode areas to insulate the wires.

For the working electrodes, three modification steps were performed sequentially, coating the Au electrode with a Prussian blue PB layer, a GO x selective membrane, and a Nafion film.

PB was electrodeposited onto the Au electrodes at 0. The designated counter electrodes were left unmodified. where D m is the mass diffusive coefficient and C g is the glucose concentration. As glucose is rapidly consumed in the extracted ISF, the mass transfer pattern quickly switches from a semi-infinite diffusion model to a finite diffusion model, i.

Taking semi-infinite diffusion and the boundary effect into account 36 , the following equation is obtained using the Laplace transform:. The switching of one of them from 1 to 0 and the other from 0 to 1 represents the complete switching of the diffusion model applied, i.

The PCB circuit is based around the STM32LK8 bit microcontroller Texas Instruments module 3 in Fig. In the schematic diagram of the microcontroller interface, PA1 and PA5 are connected to the working electrodes for amperometric signal reading, and PA8 is connected to the constant current source for current delivery for reverse iontophoresis Fig.

The Bluetooth chip is connected to pins PA2 and PA3 of the microcontroller to achieve wireless transmission to a cell phone. The signals are further transmitted and processed by the filter circuitry Fig.

On the sensor interface, pins 1, 5, 6, and 12 correspond to the extraction electrodes; pins 2 and 11 correspond to the counter electrodes; pins 3 and 10 correspond to the working electrodes; and pins 4 and 7 correspond to the reference electrodes Fig.

A mobile application was designed for a better user experience. As shown in Figs. In addition, the application is capable of storing historic data and plotting the trend of blood glucose over the period of wearing. The on-body testing of the watch was performed in compliance with the protocol that was approved by the institutional review board of China-Japan Friendship Hospital K Thirteen diabetic patients aged 40—60 were recruited from China-Japan Friendship Hospital, and 10 nonpatients aged 20—40 were recruited within Beihang University.

Six fingerstick blood samples were taken from each subject and measured by a commercial glucose meter Accusure , Yuwell Co. The values obtained with the commercial glucose meter and with our watch were recorded and further analyzed. To test the reproducibility of the reverse iontophoresis function, we carried out volunteer trials.

Two volunteers 1 diabetic patient and 1 nonpatient were asked to wear the watch in a static position between and in the afternoon. Each watch was able to run 5 blood glucose tests during the 1. was performed for each volunteer at each time point when the watch ran its glucose measurement.

We conducted further experiments to verify that body motion did not cause inaccurate test results. A nondiabetic volunteer wore a glucose detecting watch on each wrist. Lowell, B. Mitochondrial dysfunction and type 2 diabetes. Science , — Article Google Scholar. Yu, Y. Flexible electrochemical bioelectronics: The rise of in situ bioanalysis.

Kim, J. Wearable non-invasive epidermal glucose sensors: A review. Talanta , — Li, H. Nanoscale 13 , — Bariya, M. Wearable sweat sensors. Wearable biosensors for healthcare monitoring. Zhao, J. Body-interfaced chemical sensors for noninvasive monitoring and analysis of biofluids.

Trends Chem. Xie, Z. Flexible and stretchable antennas for biointegrated electronics. Li, X. Triboelectric nanogenerators for self-powered drug delivery. Xu, J. Wearable biosensors for non-invasive sweat diagnostics.

Biosensors 11 , Yu, J. et al. Microneedle-array patches loaded with hypoxia-sensitive vesicles provide fast glucose-responsive insulin delivery. Natl Acad. USA , — Lee, H. A graphene-based electrochemical device with thermoresponsive microneedles for diabetes monitoring and therapy.

Teymourian, H. Microneedle-based detection of ketone bodies along with glucose and lactate: Toward real-time continuous interstitial fluid monitoring of diabetic ketosis and ketoacidosis. Jk, A. Wearable salivary uric acid mouthguard biosensor with integrated wireless electronics.

Liao, Y. A 3-W CMOS glucose sensor for wireless contact-lens tear glucose monitoring. IEEE J. Solid-State Circuits 47 , — Mitsubayashi, K. Cavitas sensors: Contact lens type sensors and mouthguard sensors.

Electroanalysis 28 , — Park, J. Soft, smart contact lenses with integrations of wireless circuits, glucose sensors, and displays. Bandodkar, A. Tattoo-based noninvasive glucose monitoring: A proof-of-concept study. A fully integrated and self-powered smartwatch for continuous sweat glucose monitoring.

ACS Sens. Chen, Y. Skin-like biosensor system via electrochemical channels for noninvasive blood glucose monitoring. Pu, Z. A thermal activated and differential self-calibrated flexible epidermal biomicrofluidic device for wearable accurate blood glucose monitoring.

Rentz, L. Deconstructing commercial wearable technology: Contributions toward accurate and free-living monitoring of sleep.

Sensors 21 , Zhang, Z. The challenges and pitfalls of detecting sleep hypopnea using a wearable optical sensor: Comparative study. Internet Res. Bumgarner, J. Smartwatch algorithm for automated detection of atrial fibrillation. Perez, M. Large-scale assessment of a smartwatch to identify atrial fibrillation.

Ahn, J. Hypertension 27 , 4 Carni, D. Blood oxygenation measurement by smartphone. IEEE Instrum. Chen, Q. A wearable blood oxygen saturation monitoring systembased on bluetooth low energy technology. People with diabetes have to test their blood sugar levels several times a day, usually by pricking their finger with a lancet.

This can be uncomfortable and painful for many, which can result in less frequent testing and consequently worse control of blood sugar levels. The last decade has seen the rise of blood sugar monitors that are installed by pricking the skin and only need replacing every few weeks.

One of the best sellers is FreeStyle Libre, developed by Abbott Diabetes Care in the U. Many companies around the world aim to make the lives of millions of people with diabetes easier by developing non-invasive methods of glucose monitoring.

Making these methods as accurate as traditional test strips is a tough undertaking, however. Companies that can crack the challenges of measuring glucose accurately and affordably with no needles stand to reap a share of the fast-growing market of blood glucose monitors.

Here is a shortlist of some of the most exciting candidates in the market and in the pipeline. D-Base is a shoebox-sized blood sugar monitor developed by the German firm DiaMonTech. The device measures blood sugar levels by beaming an infrared laser through the skin of a finger and causing glucose in the skin to convert the light to heat.

The machine then calculates glucose levels based on the increase of heat in the skin. The increase in temperature is too minimal to be noticed by the user.

In , D-Base was approved in the EU for use by medical professionals in clinical trials and diabetes centers. Additionally, DiaMonTech is working on smaller versions of the technology, including a handheld device called D-Pocket as well as the small D-Sensor that can be used in wearable devices.

Developed by U. company Senseonics and distributed by Ascensia Diabetes Care, Eversense is a subcutaneous implant that continuously monitors blood glucose levels.

Although it initially needs to be installed under the skin by a doctor, the sensor can last for up to three months before needing a replacement. Eversense measures glucose in the interstitial fluid under the skin of the upper arm by using a polymer that fluoresces in response to the levels of blood sugar.

The data is then sent to a transmitter that displays the blood glucose levels in real time. The device received U. Food and Drug Administration FDA approval in and the company struck a deal with Roche to distribute the sensor.

A six-month version of the implant was approved in Europe in and in the U. in early Senseonics is also working on an implant that can last for up to one year. Developed by the U. To provide a readout, the sensor is clipped on the ear.

The device is indicated for adults with type 2 diabetes and is marketed in Europe. and is developing the second generation of GlucoTrack, which consists of a wireless ear clip sensor paired with a smartphone.

Initial study results of the Gen 2 monitor have shown good performance and accuracy. glucoWISE is a sensor under development that could measure blood glucose levels by just placing it on the skin between the thumb and forefinger.