Case: A 46-year-old male with EF 15% who was co-enrolled in two non-invasive remote monitoring clinical trials, using the WHOOP strap and Nanowear vest to track heart failure (HF) progression at Hershey Medical Center was readmitted for volume depletion. Our patient presented to his PCP’s office complaining of daytime fatigue. Review of systems was negative including no dizziness or light headedness. Blood pressures during this visit was 85/50 and 79/49. He was sent to the emergency department where he had persistent hypotension with a creatinine elevation from 2.4 to 3.71. He was admitted for IV fluid resuscitation and diuretic optimization. Methods: We report cumulative metrics pre- and post-hospitalization showing significant changes in sleep performance and S3 heart sound magnitude. Other measured variables with WHOOP included heart rate (HR), respiratory rate (RR), rapid eye movement (REM) sleep, and heart rate variability (HRV). Results: Following adequate hydration, return to euvolemia, and diuretic adjustment, the patient had statistically significant improvement in sleep metrics (Figure 1, Graph C). Patient’s daily strain, a surrogate of HR elevation over time, was also significantly decreased post discharge (5.19 to 0.73, p <0.01). Patient’s S3 heart sounds were measured during both hospitalizations and showed a decrease in amplitude consistent with volume depletion (Figure 1, Graphs A/B). Conclusion: We report physiologic trends that correlate with clinical status as measured using two novel non-invasive monitoring strategies. Poor sleep secondary to orthopnea and paroxysmal nocturnal dyspnea are considered signs that indicate volume overload. This case, indicates that volume depletion in patients with severely reduced EFs could also contribute to poor sleep performance, indicating a narrow therapeutic window. Further studies may validate these devices as remote monitoring tools for HF management.

Vectorcardiography (VCG) is a valuable diagnostic tool that complements the standard 12-lead ECG by offering additional spatiotemporal information to clinicians. However, due to the need for additional measurement hardware and too many electrodes in a clinical scenario if performed along with a standard 12-lead, there is a need to find methods to derive the VCG from the ECG. We have evaluated the use of Long Short-term Memory (LSTM) neural networks to learn the transformation from 12-lead ECG to VCG that is applicable across subjects and for each subject. We refer to these networks as generalized and personalized, respectively. We calculated the Root Mean Square Error (RMSE), R2, and Pearson correlation coefficient to compare waveforms of derived and actual VCG. We also extracted and compared diagnostic parameters from VCG, namely the QRS-loop magnitude, T-loop magnitude, and QRS-T spatial angle, from actual and derived VCGs using the Pearson correlation coefficient and Bland Altman limits of agreement. The personalized models performed better than generalized models in waveform comparisons and in the error of extracted diagnostic parameters from VCG waveforms. The use of personalized transformations for the derivation of VCG from standard 12-lead has the potential to improve and augment the diagnostic yield and accuracy of a standard 12-lead interpretation.

Currently, the only clinically utilized Phonocardiogram (PCG) is an electronic stethoscope used in a hospital or clinical environment. The availability of continuously recorded PCGs can provide a new avenue of research into chronic disease management at home. Researchers have proposed such wearable PCG devices. However, limitations exist in evaluating such devices as PCG recording devices in home-like environments. Here, we evaluate a wearable PCG system in a belt-type form factor with an embedded force sensor, accelerometer, and a single lead ECG to study the feasibility of acquiring diagnostic-grade PCGs while the wearer performs daily activities. We describe qualitative and quantitative exploratory analysis methods for cross-subject comparison of PCG signal quality, wearer comfort, and the impact of activities using Signal-to-Noise (SNR) comparisons and cross-spectral coherence between activity and PCG. The analysis of the data suggests that a common user-chosen method of donning a wearable PCG is not applicable across subjects for obtaining optimal PCG recording quality. We propose a method to calibrate wearable PCG devices using an embedded force sensor and by following a protocol involving feedback from the embedded force sensor to determine the optimal method of wearing the device. Following a similar path to precision medicine using genomic data and the extrapolation of risk, wearable devices with healthcare applications should be developed with the ability to be adapted and calibrated to each individual. In the immediate future this may involve calibration procedures such as those followed in this work, using controlled measurements performed with each patient to tune a device for them.

Targeted maintenance of blood pressure for hypertensive patients requires accurate monitoring of blood pressure at home. Use of multiparametric vital signs ECG, heart sounds, and thoracic impedance for blood pressure estimation at home has not been reported previously. In an observational multi-site study, 120 subjects (female (N = 61, 52%)) between 18 and 83 years of age were recruited with the following stratification (Normal (20%), prehypertensive (37%), stage 1(26%), and stage 2 (18%). From these subjects, 1686 measurements of blood pressure from a sphygmomanometer were associated with simultaneously acquired signals from the SimpleSense device. An ensemble of tree-based models was trained with inputs as metrics derived from the multiparametric and patient demographics data. A test Mean Absolute Difference (MAD) of ± 6.38 mm of Hg and ± 5.10 mm of Hg were obtained for systolic and diastolic blood pressures (SBP; DBP), respectively. Comparatively, the MAD for wrist-worn blood pressure cuff OMRON BP6350 (GUDID—10073796266353) was ± 8.92 mm of Hg and ± 6.86 mm of Hg, respectively. Machine learning models trained to use multiparametric data can monitor SBP and DBP without the need for calibration, and with accuracy levels comparable to at-home cuff-based blood pressure monitors.

Nocturnal symptoms such as Paroxysmal Nocturnal Dyspnea (PND) events are common in Heart Failure (HF) patients. However, the changes in cardiac and respiratory physiology leading up to and in recovery after a waking event (WE) has not been presented thus far with fine granularity in HF patients.

Nocturnal symptoms such as Paroxysmal nocturnal dyspnea (PND) are common among Heart Failure (HF) patients. Current HF management does not include a method to continuously monitor and risk-stratify patients based on physiological changes surrounding nocturnal arousals.

Health and long term care is a growth area for wearable heath monitoring systems. Wearable diagnostic and therapeutic systems can contribute to timely point-of-care of patients with chronic health condition, especially chronic neurological disorders, cardiovascular diseases and strokes that are leading causes of mortality worldwide. Recent progress in nano-bio-tech sensor systems and mobile platforms has resulted in novel wearable health monitoring systems for neurological and cardiovascular disorders. This talk addresses this emerging area with selected videos of subjects for real time measurements and control cardiac and neurological diseases. Combined with state-of-the-art embedded wireless network devices to communicate with smartphone, laptop or directly to remote server through mobile network (GSM,4G-LTE,GPRS), they can function as wearable wireless health- diagnostic systems that are more intuitive to use.

Catheter ablation is a procedure used to remove or destroy the harmful cells in the heart that impede a proper electrical function. The electrical pathway from the sections of the heart that induce cardiac arrhythmias are treated. Some of the abnormalities include, atrial fibrillation, atrial flutter, ventricular tachycardias, ventricular fibrillation and sudden cardiac death. Previously, electroanatomic systems were used in difficult interventional ablation procedures. These procedures were used where the target is difficult to identify and with people having complex congenital heart defects. The basic modalities of electroanatomic systems are: (1) non-fluoroscopic localization of electrophysiological catheters (2) 3D display of activation sequences from electrograms, and (3) imaging of the heart through computed tomography and magnetic resonance imaging. Catheter based ablation required sensing and imaging mechanics that accurately sense the location of the invasive electrode that removes the unwanted cells. This article summarizes the types of catheter based ablation techniques that is currently used in achieving the aforementioned objective.

Protein association starts with random collisions of individual proteins. Multiple collisions and rotational diffusion brings the molecules to a state of orientation. Majority of the protein associations are influenced by electrostatic interactions. To introduce: electrostatic rate enhancement, Brownian dynamics and transient complex theory has been traditionally used. Due to the recent advances in interdisciplinary sciences, an array of molecular assembly methods is being studied. Protein nanostructural assembly and macromolecular crowding are derived from the subsets of biochemistry to study protein-protein interactions and protein self-assembly. This paper tries to investigate the issue of enhancing the protein self-association rate, and bridging the gap between the simulations and experimental results. The methods proposed here include: electrostatic rate enhancement, macromolecular crowing, nanostructural protein assembly, microfluidics based approaches and magnetic force based approaches. Despite the suggestions of several methods, microfluidic and magnetic force based approaches seem to serve the need of protein assembly in a wider scale. Congruence of these approaches may also yield better results. Even though, these methods prove to be conceptually strong, to prevent the disagreement of theory and practice, a wide range of experiments is required. This proposal intends to study theoretical and experimental methods to successfully implement the aforementioned assembly strategies, and conclude with an extensive analysis of experimental data to address practical feasibility.

The development of intelligent miniaturized nano-bio-and info-tech based sensors capable of wireless communication will fundamentally change the way we monitor and treat patients with chronic disease and after surgery. These new sensors will allow the monitoring of the patients as they maintain their normal daily activities, and provide warning to healthcare workers when critical events arise. This will facilitate early discharge of patients from hospitals as well as providing reassurance to patients and family that potential problems will be detected at an early stage. The use of continuous monitoring allows both transient and progressive abnormalities to be reliably detected thus avoiding the problems of conventional diagnosis and monitoring methods where by data is captured only for a brief period during hospital/clinic visits. We have been working with a printable organic semiconductor and thin film transistor, and have fabricated and tested various biosensors that can measure important physiological signs before and after surgery. Integrated into "smart" fabrics - garments with wireless technology - and independent e-bandaid sensors, nanosensors in tattoos and socks, minimally invasive implantable devices, the sensor systems will be able to monitor a patient's condition in real time and thus provide point-of-care diagnostics to health-care professionals and greater freedom for patients.

Neurocardiology is the exploration of neurophysiological, neurological and neuroanatomical facets of neuroscience's influence in cardiology. The paraphernalia of emotions on the heart and brain are premeditated because of the interaction between the central and peripheral nervous system. This is an investigative attempt to study emotion based neurocardiology and the factors that influence this phenomenon. The factors include: interaction between sleep EEG (electroencephalogram) and ECG (electrocardiogram), relationship between emotion and music, psychophysiological coherence between the heart and brain, emotion recognition techniques, and biofeedback mechanisms. Emotions contribute vitally to the mundane life and are quintessential to a numerous biological and everyday-functional modality of a human being. Emotions are best represented through EEG signals, and to a certain extent, can be observed through ECG and body temperature. Confluence of medical and engineering science has enabled the monitoring and discrimination of emotions influenced by happiness, anxiety, distress, excitement and several other factors that influence the thinking patterns and the electrical activity of the brain. Similarly, HRV (Heart Rate Variability) widely investigated for its provision and discerning characteristics towards EEG and the perception in neurocardiology.

This review focusses on introducing the mechanics in carbon nanotubes (CNT), and the major applications of CNT and its composites in biomedicine. It emphasizes the nanomechanics of these materials by reviewing the widely followed experimental methods, theoretical models, simulations, classification, segregation and applications the aforementioned materials. First, several mechanical properties contributing to the classification of the CNT, for various biomedicine applications, are discussed in detail to provide a cursory glance at the uses of CNT. The mechanics of CNT discussed in this paper include: elasticity, stress, tension, compression, nano-scale mechanics. In addition to these basic properties, a brief introduction about nanoscale composites is given. Second, a brief review on some of the major applications of CNT in biomedicine including drug delivery, therapeutics, diagnostics and regenerative medicine is given.

Neurocardiology is the pathophysiological interplay of nervous and cardiovascular systems. The communication between the heart and brain has revealed various methodologies in healthcare that could be investigated to study the heart-brain interactions and other cardiovascular and neurological diseases. A textile based wearable nanosensor system in the form of e-bra, e-shirt, e-headband, e-brief, underwear etc, was presented in this SPIE conferences earlier for noninvasive recording of EEG and EKG, and showing the correlation between the brain and heart signals. In this paper, the technology is expanded further using fractal based geometries using 3D printing system for low cost and flexible wearable sensor system for healthcare.

Magnetic nanotubes hold the potential for neuroscience applications because of their capability to deliver chemicals or biomolecules and the feasibility of controlling the orientation or movement of these magnetic nanotubes by an external magnetic field thus facilitating directed growth of neurites. Therefore, we sought to investigate the effects of laminin treated magnetic nanotubes and external alternating magnetic fields on the growth of dorsal root ganglion (DRG) neurons in cell culture. Magnetic nanotubes were synthesized by a hydrothermal method and characterized to confirm their hollow structure, the hematite and maghemite phases, and the magnetic properties. DRG neurons were cultured in the presence of magnetic nanotubes under alternating magnetic fields. Electron microscopy showed a close interaction between magnetic nanotubes and the growing neurites Phase contrast microscopy revealed live growing neurons suggesting that the combination of the presence of magnetic nanotubes and the alternating magnetic field were tolerated by DRG neurons. The synergistic effect, from both laminin treated magnetic nanotubes and the applied magnetic fields on survival, growth and electrical activity of the DRG neurons are currently being investigated.

Additive manufacturing or 3D printing techniques are being vigorously investigated as a replacement to the traditional and conventional methods in fabrication to bring forth cost and time effective approaches. Introduction of 3D printing has led to printing micro and nanoscale structures including tissues and organelles, bioelectric sensors and devices, artificial bones and transplants, microfluidic devices, batteries and various other biomaterials. Various microfabrication processes have been developed to fabricate micro components and assemblies at lab scale. 3D Fabrication processes that can accommodate the functional and geometrical requirements to realize complicated structures are becoming feasible through advances in additive manufacturing. This advancement could lead to simpler development mechanisms of novel components and devices exhibiting complex features. For instance, development of microstructure electrodes that can penetrate the epidermis of the skin to collect the bio potential signal may prove very effective than the electrodes that measure signal from the skin's surface. The micro and nanostructures will have to possess extraordinary material and mechanical properties for its dexterity in the applications. A substantial amount of research being pursued on stretchable and flexible devices based on PDMA, textiles, and organic electronics. Despite the numerous advantages these substrates and techniques could solely offer, 3D printing enables a multi-dimensional approach towards finer and complex applications. This review emphasizes the use of 3D printing to fabricate micro and nanostructures for that can be applied for human healthcare.

Football players are more to violent impacts and injuries more than any athlete in any other sport. Concussion or mild traumatic brain injuries were one of the lesser known sports injuries until the last decade. With the advent of modern technologies in medical and engineering disciplines, people are now more aware of concussion detection and prevention. These concussions are often overlooked by football players themselves. The cumulative effect of these mild traumatic brain injuries can cause long-term residual brain dysfunctions. The principle of concussion is based the movement of the brain in the neurocranium and viscerocranium. The brain is encapsulated by the cerebrospinal fluid which acts as a protective layer for the brain. This fluid can protect the brain against minor movements, however, any rapid movements of the brain may mitigate the protective capability of the cerebrospinal fluid. In this paper, we propose a wireless health monitoring helmet that addresses the concerns of the current monitoring methods - it is non-invasive for a football player as helmet is not an additional gear, it is efficient in performance as it is equipped with EEG nanosensors and 3D accelerometer, it does not restrict the movement of the user as it wirelessly communicates to the remote monitoring station, requirement of individual monitoring stations are not required for each player as the ZigBee protocol can couple multiple transmitters with one receiver. A helmet was developed and validated according to the above mentioned parameters.

Detection of sleepiness and drowsiness in human beings has been a daunting task for both engineering and medical technologies. Accuracy, precision and promptness of detection have always been an issue that has to be dealt by technologists. Generally, the bio potential signals – ECG, EOG, EEG and EMG are used to classify and discriminate sleep from being awake. However, the potential drawbacks may be high false detections, low precision, obtrusiveness, aftermath analysis, etc. To overcome the disadvantages, this paper reviews the design aspects of a wireless and a real time monitoring system to track sleep and detect fatigue. This concept involves the use of EOG and EEG to measure the blink rate and asses the person’s condition. In this user friendly and intuitive approach, EOG and EEG signals are obtained by the textile based nanosensors mounted on the inner side of a flexible headband. The acquired signals are then electrically transmitted to the data processing and transmission unit, which transmits the processed data to the receiver/monitoring module through ZigBee communication. This system is equipped with a software program to process, feature extract, analyze, display and store the information. Thereby, immediate detection of a person falling asleep is made feasible and, tracking the sleep cycle continuously provides an insight about the fatigue level. This approach of using a wireless, real time, dry sensor on a flexible substrate mitigates obtrusiveness that is expected from a wearable system. We have previously presented the results of the aforementioned wearable systems. This paper aims to extend our work conceptually through a review of engineering and medical techniques involved in wearable systems to detect drowsiness.