Elsevier

Biosensors and Bioelectronics

Volume 117, 15 October 2018, Pages 537-545
Biosensors and Bioelectronics

CLASP (Continuous lifestyle awareness through sweat platform): A novel sensor for simultaneous detection of alcohol and glucose from passive perspired sweat

https://doi.org/10.1016/j.bios.2018.06.065Get rights and content

Highlights

  • Combinatorial biosensor for continuous, dynamic monitoring of alcohol and glucose in ultra- low volumes sweat.

  • Biomolecular interactions occurring at the electrode- sweat interface due to charge modulations are evaluated by non-faradaic EIS and CA.

  • Detection of physiologically relevant ranges of alcohol (3–125 mg/dl) and glucose (0.85–5.5 mg/dl) in sweat.

  • Demonstration of stable temporal response on continuous exposure to alcohol and glucose in sweat over a 120-min duration.

Abstract

Wearable- IOT based low- cost platforms can enable dynamic lifestyle monitoring through enabling promising and exciting opportunities for wellness and chronic- disease management in personalized environments. Diabetic and pre- diabetic populations can modulate their alcohol intake by tracking their glycemic content continuously to prevent health risks through these platforms. We demonstrate the first technological proof of a combinatorial biosensor for continuous, dynamic monitoring of alcohol and glucose in ultra- low volumes (1–5 µL) of passive perspired sweat towards developing a wearable- IOT based platform. Non-invasive biosensing in sweat is achieved by a unique gold- zinc oxide (ZnO) thin film electrode stack fabricated on a flexible substrate suitable for wearable applications. The active ZnO sensing region is immobilized with enzyme complexes specific for the detection of alcohol and glucose through non- faradaic electrochemical impedance spectroscopy (EIS) and chronoamperometry (CA). Biomolecular interactions occurring at the electrode- sweat interface are represented by the impedance and capacitive current changes in response to charge modulations arising in the double layer. We also report the detection of alcohol concentrations of 0.01–100 mg/dl and glucose concentrations of 0.01–50 mg/dl present in synthetic sweat and perspired human sweat. The limit of detection obtained for alcohol and glucose was found to be 0.1 mg/dl in perspired human sweat. Cross- reactivity studies revealed that glucose and alcohol did not show any signal response to cross- reactive molecules. Furthermore, the stable temporal response of the combinatorial biosensor on continuous exposure to passive perspired human sweat spiked with alcohol and glucose over a 120-min duration was demonstrated.

Introduction

Internet of things (IOT) platforms have emerged as a class of rapidly evolving embedded technologies that interconnects everyday objects in the environment with sensors using internet to create application- specific solutions for remote, real- time monitoring (Haghi et al., 2017; Hiremath et al., 2014). IOT has primarily made its way into the biosensing applications market through continuous self- tracking of health indicators and preventive medicine to provide for immediate care without the need of hospitalization (Swan, 2012). Rise in health risks and the steep increase in medical costs associated with treatments has led to the transformation of the current health care system into a highly industrialized ecosystem through the emergence of wearable personal devices. In addition to wellness management, wearable biosensing technology offers low- cost diagnostic solutions for chronic and fatal disease management in remote locations. By 2021, healthcare devices will dominate the IOT space and is expected to grow into $45.4 billion market by then (Evans, 2011). Wearable sensors provide users with the opportunity of seamless monitoring of the body's vital parameters and disease symptoms in a time controlled manner. With wellness devices gaining traction, one of the daunting challenges being faced in healthcare is the need for continuous, dynamic non-invasive monitoring of biochemical markers to understand chronic health conditions. Hence, integration of wearable diagnosis devices on an IOT platform proves promising for enabling continuous, point- of- care chronic disease detection improving early stage detections and providing the user with warnings to seek medical care. Existing wearables devices monitor digital biomarkers to track heart rate and physical activity, however, there is no information obtained on human health status which can be understood by probing biochemical markers. Recent advances have been made towards understanding easily accessible human biofluids (sweat, saliva, urine) to non-invasively monitor biomarkers that reflect the physiological state of the body. Perspired human sweat is recognized to be a highly attractive source of valuable information for this type of monitoring, and due to its ease of access, presence of biomarkers, stimulation, collection, and analysis (Jason, 2016). Literature studies show clinical correlations between sweat analyte and blood analyte levels which confirm that there is value in investigating sweat of wellness and disease management (Moyer et al., 2012, Gamella et al., 2014). Portable bioelectronic devices capable of detecting electrolytes, glucose, and lactate in small- volumes of sweat using amperometric techniques have been demonstrated previously (Abrar et al., 2016, Anastasova et al., 2017, Azevedo et al., 2005, Gao et al., 2016, Jia et al., 2013, Thomas et al., 2012). Alcohol and glucose are two biochemical markers that have a significant impact on human lifestyle. Alcohol consumption by diabetics and pre- diabetics can alter blood sugar levels to either hyperglycemic or hypoglycemic stages depending on their nourishment state (Emanuele et al., 1998). In the 18–50 age group of the U.S., an estimated population of 3 billion are diagnosed with diabetes and 27. 4 billion are prediabetic (Diabetes.org, 2017). Almost 37% of the total U.S. population consumes alcohol at moderate levels (NIAAA, 2015). A curvilinear relationship exists between alcohol consumption and incidence of type 2 diabetes (Babor et al., 2012) posing serious risks to a large demographic within this age group. Hence, there is an imminent need to monitor the effects of alcohol consumption on blood glucose levels for health and lifestyle management. Passive sweat based dynamic monitoring of these two biochemical markers offers a paradigm shifting opportunity towards wholistic on-body monitoring.

In this work, we have effectively demonstrated for the first time a wholistic approach towards biosensing alcohol and glucose combinatorially in a continuous, dynamic manner in ultra- low volumes (1–5 µL) of passive perspired human sweat. We also report the robust and stable performance of the combinatorial biosensor in perspired human sweat and synthetic sweat (SS) buffers of varying pH ranges 4–8. We observed that pH changes in sweat microenvironment does not influence the performance of the developed biosensor enabling the continuous operation of the sensor without degradation in sensor response. AC- based EIS and DC- based CA techniques are the two detection modalities used to report the impedance and current changes in response to the target concentrations presented to biosensing system. EIS and CA provides an insight into the biomolecular interactions occurring at the electrode- buffer interface through which information regarding the target analyte concentrations can be extracted (Bard and Faulkner, 2000, Scholz, 2015). Furthermore, the selectivity and the specificity of the combinatorial biosensor towards target analytes has been validated to demonstrate the feasibility of detection in human sweat buffer. Dynamic responses to varying levels of the biomolecules was demonstrated for a period of ~ 120 min.

Section snippets

Materials and reagents

Polyamide substrates (pore size – 200 nm, thickness – 60 µm) were obtained from GE Healthcare Life Sciences (Piscataway, NJ, USA). The linker molecule dithiobis succinimidyl propionate (DSP), dimethyl sulfoxide (DMSO), and 1 × phosphate buffered saline (PBS) were purchased from Thermo Fisher Scientific Inc. (Waltham, MA, USA). Salt-free streptavidin from Streptomyces avidiini (≥ 13 units/mg protein), alcohol oxidase enzyme from Pichia pastoris (10–40 units/mg protein), glucose oxidase from

Modulation of hybrid electrode- solution interface to evaluate the sweat- based combinatorial biosensor's performance through EIS and CA techniques

The combinatorial biosensor, as shown in Fig. 1A, that was designed for the detection of alcohol and glucose employs a novel hybrid electrode with gold as the measurement electrode and a thin film of zinc oxide (ZnO) as the active sensing region on a flexible nanoporous substrate. The active sensing region of the biosensor is surface functionalized with specific enzyme biomolecule complexes for alcohol and glucose detection as shown in Fig. 1B. The response of the functionalized biosensor to

Conclusion

This work is the first- time demonstration of a biosensor utilizing ultra- low passive perspired human sweat volumes for rapid and dynamic monitoring of alcohol and glucose in a temporal manner suitable for wearable IOT applications. A relationship between blood glucose levels and consumption of alcohol has been found to interfere with blood glucose levels and reduce the effectiveness of insulin (Emanuele et al., 1998, Avogaro and Tiengo, 1993). Alcohol consumption is prone to increasing

Acknowledgements

Funding for this research was supported by the National Institute on Alcohol Abuse and Alcoholism of the National Institutes of Health (R43AA026114). We acknowledge the contributions of Ankita Rugi and Amreek Saini for assisting in performing the experiments. The authors thank Saigautam Sirivella for helping with the schematics. The authors would like to thank Richard Willis for programming the data compilation software. We also thank Ambalika Tanak and David Kinnamon for their help in

Conflict of interest statement

Drs. Shalini Prasad and Sriram Muthukumar have a significant interest in Enlisense LLC, a company that may have a commercial interest in the results of this research and technology. The potential individual conflict of interest has been reviewed and managed by The University of Texas at Dallas, and played no role in the study design; in the collection, analysis, and interpretation of data; in the writing of the report, or in the decision to submit the report for publication.

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