Skin-like, Soft Patch for Continuous Cognitive Stress Monitoring

Presented at Georgia Tech 2023 Career, Research, and Innovation Development Conference PosterHere, we present a skin-like, wearable patch microfabricated to seamlessly integrate with the human body and provide high fidelity physiological monitoring in a simple, minimally obtrusive platform. Specifically, this device has been optimized to capture minute chest vibrations produced by the heart’s mechanical beats, referred to as the seismocardiogram (SCG). along with the traditional electrocardiogram (ECG) and pulse oximetry (PPG) signals in a single platform located on the sternum; mathematical tools developed in the study of seismology are then implemented to characterize the heart’s mechanical function and arousal state. In tandem with the PPG and ECG signals, this SCG analysis is used to continuously monitor cognitive stress, which is a notoriously difficult challenge because traditional monitoring signals, like heart rate variability and galvanic skin response are modulated by numerous confounding physiological factors. In contrast, preliminary studies with the soft device demonstrated an r2 correlation with salivary cortisol during controlled stressor activities of 0.81 compared to 0.59 for heart rate variability. Additional clinical testing is being pursued, and should this correlation be proven, this device would represent a substantial improvement in long-duration, continuous stress monitoring in daily life over alternative approaches. This in turn would have wide applications in dementia care, pain assessment, high stress workplace management (e.g., for surgeons and pilots), mental health treatment, and simple wellness

Soft Sternal Patch to Detect Sleep Stages and Sleep Apnea

Presented at the Georgia Tech Career, Research, and Innovation Development Conference (CRIDC), January 27, 2022.The Career, Research, and Innovation Development Conference (CRIDC) is designed to equip on-campus and online graduate students with tools and knowledge to thrive in an ever-changing job market.Obstructive sleep apnea (OSA) affects over 900 million adults globally, and around eighty percent of cases remain undiagnosed. This critical failure leaves millions of people at an increased risk for serious health complications, like hypertension, obesity, diabetes, and cardiac irregularities. Current diagnostic techniques are fundamentally limited by low throughputs, in the case of polysomnography, and high failure rates, in the case of home sleep tests. Here, we report a wireless, fully integrated, soft sternal patch with mechanics optimized to detect the mechanical, electrical, and optical signals that characterize the cardiovascular response to OSA. Analytical and computational studies in mechanics and material interfaces yielded a fully integrated, multi-sensor system capable of capturing ultrafine, low-frequency, sternal vibrations caused by the heart’s motion, cardiac electrical signals, and optical measurements of arterial blood oxygenation from a single location on the sternum, which has not been previously realized. Advanced digital signal processing and machine learning techniques are used to detect apneas and characterize each event’s acute cardiovascular consequences. In trials with symptomatic and control subjects conducted in their homes, the soft device demonstrates excellent ability to detect blood-oxygen saturation, respiratory effort, respiration rate, heart rate, cardiac pre-ejection period and ejection timing, aortic opening mechanics, heart rate variability, and sleep staging, making it the first single patch capable of capturing all the clinically essential metrics for OSA diagnosis recommended by the American Academy of Sleep Medicine. Finally, these metrics are used to autodetect apneas and hypopneas with 100% sensitivity and 95% precision with symptomatic patients compared to data scored by professionally certified sleep clinicians.NSF Grant ECCS-202546

Intelligent upper-limb exoskeleton using deep learning to predict human intention for sensory-feedback augmentation

The age and stroke-associated decline in musculoskeletal strength degrades the ability to perform daily human tasks using the upper extremities. Although there are a few examples of exoskeletons, they need manual operations due to the absence of sensor feedback and no intention prediction of movements. Here, we introduce an intelligent upper-limb exoskeleton system that uses cloud-based deep learning to predict human intention for strength augmentation. The embedded soft wearable sensors provide sensory feedback by collecting real-time muscle signals, which are simultaneously computed to determine the user's intended movement. The cloud-based deep-learning predicts four upper-limb joint motions with an average accuracy of 96.2% at a 200-250 millisecond response rate, suggesting that the exoskeleton operates just by human intention. In addition, an array of soft pneumatics assists the intended movements by providing 897 newton of force and 78.7 millimeter of displacement at maximum. Collectively, the intent-driven exoskeleton can augment human strength by 5.15 times on average compared to the unassisted exoskeleton. This report demonstrates an exoskeleton robot that augments the upper-limb joint movements by human intention based on a machine-learning cloud computing and sensory feedback.Comment: 15 pages, 6 figures, 1 table, Submitted for possible publicatio

Nanomaterials and Scalable, Low-Cost Screen Printing for Soft Wearable Bioelectronics

Poster to be presented at the 2022 Brumley D. Pritchett Lecture & the IMat Symposium on Materials Innovation, April 11-12, 2022, Georgia Institute of Technology, Atlanta, GA.Stretchable electronics have demonstrated tremendous potential in wearable healthcare, advanced diagnostics, soft robotics, and persistent human–machine interfaces. Still, their applicability is limited by a reliance on low-throughput, high-cost fabrication methods. Traditional MEMS/NEMS metallization and off-contact direct-printing methods are not suitable at scale. In contrast, screen printing is a high-throughput, mature printing method. The recent development of conductive nanomaterial inks that are intrinsically stretchable provides an exciting opportunity for scalable fabrication of stretchable electronics. The design of screen-printed inks is constrained by strict rheological requirements during printing, substrate–ink attraction, and nanomaterial properties that determine dispersibility and percolation threshold. Here, we present our recent work developing screen-printable nanomaterial inks, optimizing printing parameters for ultrafine patterning down to <60 µm, investigating multilevel material adhesion and reliability, designing complex sensors, and integrating these innovations into functional bioelectronics. Specifically, we present high precision screen printing of functional nanomaterials to enable fabrication of highly functional biopotential electrodes, thermoelectric nanogenerators, flexible circuits, semiconductors, printed vias, solderable circuit pads, strain gauges, and pressure sensors. These fundamental advances in materials fabrication and high-throughput bioelectronics fabrication have transformative potential for the field of soft electronics, and we are committed to further studies on these systems to validate their potential in functional devices.NSF GRFP under Grant No. DGE-203965

Recent Advances in Materials and Flexible Sensors for Arrhythmia Detection

Arrhythmias are one of the leading causes of death in the United States, and their early detection is essential for patient wellness. However, traditional arrhythmia diagnosis by expert evaluation from intermittent clinical examinations is time-consuming and often lacks quantitative data. Modern wearable sensors and machine learning algorithms have attempted to alleviate this problem by providing continuous monitoring and real-time arrhythmia detection. However, current devices are still largely limited by the fundamental mismatch between skin and sensor, giving way to motion artifacts. Additionally, the desirable qualities of flexibility, robustness, breathability, adhesiveness, stretchability, and durability cannot all be met at once. Flexible sensors have improved upon the current clinical arrhythmia detection methods by following the topography of skin and reducing the natural interface mismatch between cardiac monitoring sensors and human skin. Flexible bioelectric, optoelectronic, ultrasonic, and mechanoelectrical sensors have been demonstrated to provide essential information about heart-rate variability, which is crucial in detecting and classifying arrhythmias. In this review, we analyze the current trends in flexible wearable sensors for cardiac monitoring and the efficacy of these devices for arrhythmia detection

Soft wireless sternal patch to detect systemic vasoconstriction using photoplethysmography

Summary: Vasoconstriction is a crucial physiological process that serves as the body’s primary blood pressure regulation mechanism and a key marker of numerous harmful health conditions. The ability to detect vasoconstriction in real time would be crucial for detecting blood pressure, identifying sympathetic arousals, characterizing patient wellbeing, detecting sickle cell anemia attacks early, and identifying complications caused by hypertension medications. However, vasoconstriction manifests weakly in traditional photoplethysmogram (PPG) measurement locations, like the finger, toe, and ear. Here, we report a wireless, fully integrated, soft sternal patch to capture PPG signals from the sternum, an anatomical region that exhibits a robust vasoconstrictive response. With healthy controls, the device is highly capable of detecting vasoconstriction induced endogenously and exogenously. Furthermore, in overnight trials with patients with sleep apnea, the device shows a high agreement (r2 = 0.74) in vasoconstriction detection with a commercial system, demonstrating its potential use in portable, continuous, long-term vasoconstriction monitoring

Fully Screen-Printed PI/PEG Blends Enabled Patternable Electrodes for Scalable Manufacturing of Skin-Conformal, Stretchable, Wearable Electronics

Recent advances in soft materials and nano-microfabrication have enabled the development of flexible wearable electronics. At the same time, printing technologies have been demonstrated to be efficient and compatible with polymeric materials for manufacturing wearable electronics. However, wearable device manufacturing still counts on a costly, complex, multistep, and error-prone cleanroom process. Here, we present fully screen-printable, skin-conformal electrodes for low-cost and scalable manufacturing of wearable electronics. The screen printing of the polyimide (PI) layer enables facile, low-cost, scalable, high-throughput manufacturing. PI mixed with poly(ethylene glycol) exhibits a shear-thinning behavior, significantly improving the printability of PI. The premixed Ag/AgCl ink is then used for conductive layer printing. The serpentine pattern of the screen-printed electrode accommodates natural deformation under stretching (30%) and bending conditions (180°), which are verified by computational and experimental studies. Real-time wireless electrocardiogram monitoring is also successfully demonstrated using the printed electrodes with a flexible printed circuit. The algorithm developed in this study can calculate accurate heart rates, respiratory rates, and heart rate variability metrics for arrhythmia detection

Fully Screen-Printed PI/PEG Blends Enabled Patternable Electrodes for Scalable Manufacturing of Skin-Conformal, Stretchable, Wearable Electronics

Recent advances in soft materials and nano-microfabrication have enabled the development of flexible wearable electronics. At the same time, printing technologies have been demonstrated to be efficient and compatible with polymeric materials for manufacturing wearable electronics. However, wearable device manufacturing still counts on a costly, complex, multistep, and error-prone cleanroom process. Here, we present fully screen-printable, skin-conformal electrodes for low-cost and scalable manufacturing of wearable electronics. The screen printing of the polyimide (PI) layer enables facile, low-cost, scalable, high-throughput manufacturing. PI mixed with poly(ethylene glycol) exhibits a shear-thinning behavior, significantly improving the printability of PI. The premixed Ag/AgCl ink is then used for conductive layer printing. The serpentine pattern of the screen-printed electrode accommodates natural deformation under stretching (30%) and bending conditions (180°), which are verified by computational and experimental studies. Real-time wireless electrocardiogram monitoring is also successfully demonstrated using the printed electrodes with a flexible printed circuit. The algorithm developed in this study can calculate accurate heart rates, respiratory rates, and heart rate variability metrics for arrhythmia detection