EP-4734844-A1 - PHYSICOCHEMICAL-SENSING ELECTRONIC SKIN FOR STRESS RESPONSE MONITORING

Abstract

Systems and methods for a wearable stress response assessment system may include aniontophoresis module, a multi-inlet microfluidic sweat sampling component, and a sensor patchconfigured to detect concentrations of electrolytes and metabolites present in a sweat sample andmonitor physiological signs prevalent in a human patient. An iontophoresis module may providefor stimulation of a biofluid sample. A biofluid may be a sweat sample. Stimulation may beachieved via electrostimulation and/or application of a stimulating agent. A microfluidic sweatsampling component may include adhesive and PDMS layers with carefully designed inlets andchannels for efficient collection and sampling of biofluid. Enzymatic and ISE biosensors mayquickly and accurately identify concentrations of key biomarkers present in a biofluid samplewhich may assess, in combination with monitored physiological signs, a human patient's stressresponse.

Inventors

• GAO, WEI
• XU, Changhao

Assignees

• California Institute of Technology

Dates

Publication Date

20260506

Application Date

20240626

Claims (20)

1. 1. A wearable assessment system, comprising: a sweat sensor patch adapted to adhere to and induce sweat production from human skin; a microfluidic sweat sampling component comprising multiple inlets to contact the human skin and collect a sweat sample from the human skin, wherein the microfluidic sweat sampling component couples to the sweat sensor patch; a metabolite detection logical circuit to identify concentrations of target metabolites in the sweat sample; an electrolyte detection logical circuit to identify concentrations of target electrolytes in the sweat sample; and a physiological indicator logical circuit to identify target signals representative of physiological signs from the human skin.
2. 2. The wearable assessment system of claim 1, wherein the sweat sensor patch is a multilayered sensor patch further comprising: a sweat-stimulation electrode; an enzymatic biosensor; an ion selection sensor (ISE); a capacitive pulse sensor; a resistive galvanic skin response (GSR) sensor; and a skin temperature sensor.
3. 3. The wearable assessment system of claim 1, wherein the sweat sensor patch further comprises: a top layer fabricated through serial inkjet printing of silver and carbon; a bottom layer fabricated through serial inkjet printing of silver and carbon; and a middle polydimethylsiloxane (PDMS)-based airgap layer, wherein the middle polydimethylsiloxane (PDMS)-based airgap layer is spin-coated between the top and bottom layers.
4. 4. The wearable assessment system of claim 1, wherein the microfluidic sweat sampling component comprises at least one of: (i) a carbochol hydrogel-loaded sweatstimulation electrode and (ii) a hydrogel-loaded sweat-stimulation electrode, wherein the carbochol hydrogel-loaded sweat-stimulation electrode and the hydrogel-loaded sweat-stimulation electrode are configured to induce sweat production.
5. 5. The wearable assessment system of claim 1, wherein the metabolite detection logical circuit is configured to identify concentrations of glucose, lactate, and uric acid (UA) in the collected sweat sample.
6. 6. The wearable assessment system of claim 1, wherein the electrolyte detection logical circuit is configured to identify concentrations of Na + , K + , and NHT in the collected sweat sample.
7. 7. The wearable assessment system of claim 1, wherein the physiological indicator logical circuit is configured to identify signals representative of pulse waveform, galvanic skin response (GSR), and skin temperature from the human skin.
8. 8. The wearable assessment system of claim 1, wherein the assessment is based on the analyzed metabolite concentrations, electrolyte concentrations, and physiological signs.
9. 9. The wearable assessment system of claim 1, further comprising a smart device with one or more processors and machine-readable instructions embedded thereon, wherein the machine readable instructions cause the one or more processors to analyze the detected metabolite concentrations, the detected electrolyte concentrations, and the identified physiological signs, and display an assessment on a graphical user interface.
10. 10. A wearable stress response assessment system, comprising: a multilayer sweat sensor patch adapted to adhere to and induce sweat production from human skin, wherein the multilayer sweat sensor patch further compnses: a carbochol hydrogel-loaded sweat-stimulation electrode; a hydrogel-loaded sweat-stimulation electrode; three enzymatic biosensors; and three ion-selective sensors (ISEs); wherein the carbochol hydrogel-loaded sweat-stimulation electrode and the hydrogel-loaded sweat-stimulation electrode are integrated into a skin-interfaced laser- engraved microfluidic component, wherein the skin-interfaced laser-engraved microfluidic component collects an induced sweat sample for analysis; wherein the three enzymatic biosensors are integrated into a metabolite detection logical circuit that is further integrated within the sensor patch, wherein each enzymatic biosensor is configured to identify concentrations of one of glucose, lactate, and uric acid (UA) in the collected sweat sample; and wherein the three ion-selective sensors (ISEs) are integrated into a electrolyte detection logical circuit that is further integrated within the sensor patch, wherein each ion-selective sensor is configured to identify concentrations of one of Na + , K + , and NH4 + in the collected sweat sample.
11. 11. The wearable stress assessment system of claim 10, further comprising a skin- interfaced indicator logical circuit that comprises: a capacitive pulse sensor configured to detect signals representative of a human subject’s pulse waveform; a resistive galvanic skin response (GSR) sensor configured to detect signals representative of a human subject’s GSR level; and a skin temperature sensor configured to detect signals representative of a human subject’s skin temperature.
12. 12. The wearable stress assessment system of claim 10, wherein the three enzymatic biosensors each comprise: an electrodeposited gold nanoparticles layer; an electrodeposited Prussian blue transduction layer; an electrodeposited nickel hexacyanoferrate (NiHCF) protection layer; and an enzyme layer in a glutaraldehyde-crosslinked bovine serum (BSA) matrix.
13. 13. The wearable stress assessment system of claim 10, further comprising a smart device, wherein the smart device analyzes the detected metabolite concentrations, and the detected electrolyte concentrations, and displays a stress assessment based on the analyzed metabolite concentrations and analyzed electrolyte concentrations.
14. 14. The wearable stress assessment system of claim 13, wherein the stress assessment is determined using machine learning methods.
15. 15. The wearable stress assessment system of claim 10, further comprising an in situ signal processing and wireless communication module.
16. 16. The wearable stress assessment system of claim 10, wherein the sweat sensor patch further comprises: a top layer fabricated through serial inkjet printing of silver and carbon; a bottom layer fabricated through serial inkjet printing of silver and carbon; and a middle polydimethylsiloxane (PDMS)-based airgap layer, wherein the middle polydimethylsiloxane (PDMS)-based airgap layer is spin-coated between the top and bottom layers.
17. 17. The wearable stress assessment system of claim 10, wherein the three enzymatic biosensors further comprise a diffusion-limiting membrane layer that further tunes metabolite detections ranges for high concentration detection.
18. 18. The wearable stress assessment system of claim 10, wherein the three ion- selective sensors (ISEs) comprise: a carbon layer; and a polystyrene-block-poly (ethylene butylene)- block-polystyrene (SEBS) - polyvinyl chloride (PVC)/bis(2-ethylhexyl) sebacate (DOS) - ionophore/lipophilic anionic sites mixture based membrane layer.
19. 19. A method, comprising: applying a stimulating agent to a human sweat gland, wherein the stimulating agent induces production of a sweat sample; collecting the induced sweat sample in a microfluidic sweat sampling component, wherein the microfluidic sweat sampling component channels the collected sweat sample into a metabolite reservoir and a electrolyte reservoir; identifying metabolite concentrations in the collected sweat sample via a metabolite detection logical circuit, wherein the metabolite detection logical circuit retrieves a first collected sweat sample from the metabolite reservoir; identifying electrolyte concentrations in the collected sweat sample via an electrolyte detection logical circuit, wherein the electrolyte detection logical circuit retrieves a second collected sweat sample from the electrolyte reservoir; and transmitting information representative of the identified metabolite and electrolyte concentrations to a smart device.
20. 20. The method of claim 19, further comprising identifying physiological signals on the human sweat gland via a physiological indicator logical circuit, wherein the physiological indicator logical circuit identifies signals representative of pulse waveform, galvanic skin response (GSR), and skin temperature.

Description

PHYSICOCHEMICAL-SENSING ELECTRONIC SKIN FOR STRESS RESPONSE MONITORING RELATED APPLICATION [0001] This application claims the benefit of U.S. Provisional Application No. 63/523,443 filed on June 27, 2023, the contents of which are incorporated herein by reference in their entirety. [0002] This invention was made with government support under Grant No. NNX16A069A awarded by NASA and under Grant No. N00014-21-1-2483 awarded by the Office of Naval Research. The government has certain rights in the invention. TECHNICAL FIELD [0003] The present disclosure relates generally to wearable sensors for stress monitoring. In particular, some implementations may relate to systems and methods for physicochemical- sensing electronic skin for stress response monitoring using human sweat samples. BACKGROUND [0004] Stress is a complex concept that has often been used to capture a wide range of phenomena. For example, the term '’stress" has at times been used to refer to life events or experiences that occur to individuals (e.g.. the break-up of a romantic relationship, losing one’s job) and at other times to refer to the response to these types of experiences. Given the broad ways in which the term ’’stress" has often been used, there have been calls to increase the specificity’ with which aspects of stress (e.g., stimulus, response) are defined. This disclosure focuses on "‘stress” as the stress response, which occurs when demands placed on an individual exceed their resources to manage those demands. However, systems and methods disclosed herein may be applied to other “stress”-inducing situations. [0005] Stress responses can occur across multiple levels and systems, including cognitive, affective, behavioral, and biological processes. The stress response is relevant to a wide range of mental and physical health outcomes, including depression, anxiety disorders, and cardiovascular disease. In contrast to the stress response, a stressor is an exposure (e.g., stressful event or stimulus) that triggers this response. [0006] Approaches to quantify stress responses typically rely on subjective surveys and questionnaires. To account for this, wearable sensors can potentially be used to continuously monitor stress-relevant biomarkers. However, the biological stress response is spread across the nervous, endocrine, and immune systems, and the capabilities of conventional sensors are not sufficient for condition-specific stress response evaluation. [0007] Wearable bioelectronic technology/devices (including wearable sensors) offer many advantages for personalized health monitoring. Wearable devices are non-invasive and present less user error than other monitoring methods. Additionally, wearable devices offer the potential to monitor health status over time as opposed to collecting a sample that reflects health status at only a snap shot in time. This type of real-time monitoring offers more accurate and individualized diagnosis, treatment, and prevention for health conditions. Specifically, wearable devices can measure pulse, respiration rate, temperature, and other health status indicators. [0008] Sweat sensors are one type of wearable bioelectronic sensors that are particularly desirable because sweat contains many key biomarkers including electrolytes, metabolites, amino acids, hormones, and drug levels. However, existing sweat sensors face several key problems. First, existing sensors lack an effective continuous monitoring strategy. They employ sensors that are only able to measure a limited set of biomarkers. This limited set of biomarkers alone does not provide a full enough picture of a human subject’s health status to serve as an effective stress assessment tool. Additionally, these sensors often require a large sample of sweat to provide accurate analysis of biomarkers. This requires a larger and more powerful device, which may not be suitable as a wearable. Therefore, monitoring, and especially continuous monitoring presents a challenge due to the need for high power and for power storage. Existing models present additional challenges including that they require complex fabrication, are difficult to reproduce in large quantities in an affordable way, and are fragile, making them not suitable as wearable devices for long periods. [0009] For at least these reasons, the current “gold standard” for measuring biomarkers in the body is blood testing. Blood testing has several drawbacks including that it is invasive, as it requires withdrawal of blood from the veins. Also, accurate blood testing, and/or blood testing generally, needs larger samples, generally requiring a human patient to come to the lab and be tested. Because of the lab requirement and invasiveness, blood testing is generally only performed at a snapshot or discrete moment in time. This means that in many cases, unless a patient is experiencing a flare up or other type of health episode at the time of testing, the testing may not reveal any unusual biomar