An integrated self-healable electronic skin system fabricated via dynamic reconstruction of a nanostructured conducting network.

Electronic skin devices capable of monitoring physiological signals and displaying feedback information through closed-loop communication between the user and electronics are being considered for next-generation wearables and the 'Internet of Things'. Such devices need to be ultrathin to achieve seamless and conformal contact with the human body, to accommodate strains from repeated movement and to be comfortable to wear. Recently, self-healing chemistry has driven important advances in deformable and reconfigurable electronics, particularly with self-healable electrodes as the key enabler. Unlike polymer substrates with self-healable dynamic nature, the disrupted conducting network is unable to recover its stretchability after damage. Here, we report the observation of self-reconstruction of conducting nanostructures when in contact with a dynamically crosslinked polymer network. This, combined with the self-bonding property of self-healing polymer, allowed subsequent heterogeneous multi-component device integration of interconnects, sensors and light-emitting devices into a single multi-functional system. This first autonomous self-healable and stretchable multi-component electronic skin paves the way for future robust electronics.

A hierarchically patterned, bioinspired e-skin able to detect the direction of applied pressure for robotics.

Tactile sensing is required for the dexterous manipulation of objects in robotic applications. In particular, the ability to measure and distinguish in real time normal and shear forces is crucial for slip detection and interaction with fragile objects. Here, we report a biomimetic soft electronic skin (e-skin) that is composed of an array of capacitors and capable of measuring and discriminating in real time both normal and tangential forces. It is enabled by a three-dimensional structure that mimics the interlocked dermis-epidermis interface in human skin. Moreover, pyramid microstructures arranged along nature-inspired phyllotaxis spirals resulted in an e-skin with increased sensitivity, minimal hysteresis, excellent cycling stability, and response time in the millisecond range. The e-skin provided sensing feedback for controlling a robot arm in various tasks, illustrating its potential application in robotics with tactile feedback.

Cardiovascular morphometry with high-resolution 3D magnetic resonance: First application to left ventricle diastolic dysfunction.

In this study, an image-based morphometry toolset quantifying geometric descriptors of the left ventricle, aorta and their coupling is applied to investigate whether morphological information can differentiate between subjects affected by diastolic dysfunction (patient group) and their age-matched controls (control group). The ventriculo-aortic region of 20 total participants (10 per group) were segmented from high-resolution 3D magnetic resonance images, from the left ventricle to the descending aorta. Each geometry was divided into segments in correspondence of anatomical landmarks. The orientation of each segment was estimated by least-squares fitting of the respective centerline segment to a plane. Curvature and torsion of vessels' centerlines were automatically extracted, and aortic arch was characterized in terms of height and width. Tilt angle between subsequent best-fit planes in the left ventricle and ascending aorta regions, curvature and cross-sectional area in the descending aorta resulted significantly different between patient and control groups (P-values< 0.05). Aortic volume (P = 0.04) and aortic arch width (P = 0.03) resulted significantly different between the two groups. The observed morphometric differences underlie differences in hemodynamics, by virtue of the influence of geometry on blood flow patterns. The present exploratory analysis does not determine if aortic geometric changes precede diastolic dysfunction, or vice versa. However, this study (1) underlines differences between healthy and diastolic dysfunction subjects, and (2) provides geometric parameters that might help to determine early aortic geometric alterations and potentially prevent evolution toward advanced diastolic dysfunction.

In vivo evaluation of a novel, wrist-mounted arterial pressure sensing device versus the traditional hand-held tonometer.

Although hemodynamic parameters can be assessed non-invasively, state-of-the-art non-invasive systems generally require an expert operator and are not applicable for ambulatory measurements. These limitations have restricted our understanding of the continuous behavior of hemodynamic parameters. In this manuscript, we introduce a novel wrist-mounted device that incorporates an array of pressure sensors which can be used to extract arterial waveforms and relevant pulse wave analysis biomarkers. In vivo evaluation is performed with Bland-Altman analysis to compare the novel sensor to a gold-standard hand-held tonometer by assessing their reproducibility and agreement in peripheral augmentation index (AIx) estimation at the radial artery. Arterial waves from 28 randomly selected participants were recorded in a controlled environment. Initially we assess the reproducibility of AIx results for both devices. The intra-class correlation coefficient (ICC) and mean difference ± SD were [0.913, 0.033±0.048] and [0.859, 0.039±0.076] for the hand-held and the wrist-mounted tonometer respectively. We then show that the AIx values derived from the novel tonometer have good agreement, accuracy, and precision when compared against the AIx values derived from the reference hand-held tonometer (ICC 0.927, mean difference 0.026±0.049). In conclusion, we have presented evidence that the new wrist-mounted arterial pressure sensor records arterial waveforms that can be processed to yield AIx values that are in good agreement with its traditional hand-held counterpart.

Single breath-hold 3D measurement of left atrial volume using compressed sensing cardiovascular magnetic resonance and a non-model-based reconstruction approach.

BACKGROUND: Left atrial (LA) dilatation is associated with a large variety of cardiac diseases. Current cardiovascular magnetic resonance (CMR) strategies to measure LA volumes are based on multi-breath-hold multi-slice acquisitions, which are time-consuming and susceptible to misregistration. AIM: To develop a time-efficient single breath-hold 3D CMR acquisition and reconstruction method to precisely measure LA volumes and function. METHODS: A highly accelerated compressed-sensing multi-slice cine sequence (CS-cineCMR) was combined with a non-model-based 3D reconstruction method to measure LA volumes with high temporal and spatial resolution during a single breath-hold. This approach was validated in LA phantoms of different shapes and applied in 3 patients. In addition, the influence of slice orientations on accuracy was evaluated in the LA phantoms for the new approach in comparison with a conventional model-based biplane area-length reconstruction. As a reference in patients, a self-navigated high-resolution whole-heart 3D dataset (3D-HR-CMR) was acquired during mid-diastole to yield accurate LA volumes. RESULTS: Phantom studies. LA volumes were accurately measured by CS-cineCMR with a mean difference of -4.73 ± 1.75 ml (-8.67 ± 3.54%, r2 = 0.94). For the new method the calculated volumes were not significantly different when different orientations of the CS-cineCMR slices were applied to cover the LA phantoms. Long-axis "aligned" vs "not aligned" with the phantom long-axis yielded similar differences vs the reference volume (-4.87 ± 1.73 ml vs. -4.45 ± 1.97 ml, p = 0.67) and short-axis "perpendicular" vs. "not-perpendicular" with the LA long-axis (-4.72 ± 1.66 ml vs. -4.75 ± 2.13 ml; p = 0.98). The conventional bi-plane area-length method was susceptible for slice orientations (p = 0.0085 for the interaction of "slice orientation" and "reconstruction technique", 2-way ANOVA for repeated measures). To use the 3D-HR-CMR as the reference for LA volumes in patients, it was validated in the LA phantoms (mean difference: -1.37 ± 1.35 ml, -2.38 ± 2.44%, r2 = 0.97). Patient study: The CS-cineCMR LA volumes of the mid-diastolic frame matched closely with the reference LA volume (measured by 3D-HR-CMR) with a difference of -2.66 ± 6.5 ml (3.0% underestimation; true LA volumes: 63 ml, 62 ml, and 395 ml). Finally, a high intra- and inter-observer agreement for maximal and minimal LA volume measurement is also shown. CONCLUSIONS: The proposed method combines a highly accelerated single-breathhold compressed-sensing multi-slice CMR technique with a non-model-based 3D reconstruction to accurately and reproducibly measure LA volumes and function.

In vivo evaluation of a novel 'diastole-patching' algorithm for the estimation of pulse transit time: advancing the precision in pulse wave velocity measurement.

Carotid-to-femoral pulse wave velocity (PWV) is the gold standard for the assessment of aortic stiffness. It is calculated by the ratio of pulse transit time (PTT) between two arterial sites and the distance between them. The precision of PTT estimation depends upon the algorithm that determines characteristic points at the foot of the pulse waveforms. Different algorithms yield variable PTT values thus affecting the precision of PWV and subsequently its diagnostic and prognostic accuracy. Our aim was to apply in vivo a new 'diastole-patching' algorithm and investigate whether it improves the precision of PWV measurement. Two repeated PWV measurements were performed in a general population (340 subjects) by a reference apparatus (SphygmoCor) which uses the tangential method for PTT estimation. PTT was re-estimated by the 'diastole-patching' algorithm. We computed statistical parameters of agreement, consistency, precision and variability between the two PWV measurements. The 'diastole-patching' method yielded more precise and reproducible measurements of PWV compared to the tangential method at the total population. In those cases where the reference method provided PWV measurements with difference >1 m s(-1), the 'diastole-patching' algorithm further improved the precision of PWV. These findings may have direct implications concerning the enhancement of the diagnostic and prognostic value of PWV.

First in vivo application and evaluation of a novel method for non-invasive estimation of cardiac output.

Surgical or critically ill patients often require continuous assessment of cardiac output (CO) for diagnostic purposes or for guiding therapeutic interventions. A new method of non-invasive CO estimation has been recently developed, which is based on pressure wave analysis. However, its validity has been examined only in silico. Aim of this study was to evaluate in vivo the reproducibility and accuracy of the "systolic volume balance" method (SVB). Twenty two subjects underwent 2-D transthoracic echocardiography for CO measurement (reference value of CO). The application of SVB method required aortic pressure wave analysis and estimation of total arterial compliance. Aortic pulses were derived by mathematical transformation of radial pressure waves recorded by applanation tonometry. Total compliance was estimated by the "pulse pressure" method. The agreement, association, variability, bias and precision between Doppler and SVB measures of CO were evaluated by intraclass correlation coefficient (ICC), mean difference, SD of differences, percentage error (PR) and Bland-Altman analysis. SVB yielded very reproducible CO estimates (ICC=0.84, mean difference 0.27 ± 0.73 L/min, PR = 16.7%). SVB-derived CO was comparable with Doppler measurements, indicating a good agreement and accuracy (ICC = 0.74, mean difference = -0.22 ± 0.364 L/min, PR ≈ 15). The basic mathematical and physical principles of the SVB method provide highly reproducible and accurate estimates of CO compared with echocardiography.

Total arterial compliance estimated by a novel method and all-cause mortality in the elderly: the PROTEGER study.

Aortic stiffness, assessed by carotid-to-femoral pulse wave velocity (PWV), often fails to predict cardiovascular (CV) risk and mortality in the very elderly. This may be due to the non-linear association between PWV and compliance or to blood pressure decrease in the frailest subjects. Total arterial compliance (C T) is the most relevant arterial property regarding CV function, compared to local or regional arterial stiffness. A new method for C T estimation, based on PWV, was recently proposed. We aimed to investigate the value of C T to predict all-cause mortality at the elderly. PWV was estimated in 279 elderly subjects (85.5 ± 7.0 years) who were followed up for a mean period of 12.8 ± 6.3 months. C T was estimated by the formula C T = k × PWV(-2); coefficient k is body-size dependent based on previous in silico simulations. Herein, k was adjusted for body mass index (BMI) with a 10 % change in BMI corresponding to almost 11 % change in k. For a reference BMI = 26.2 kg/m(2), k = 37. Survivors (n = 185) and non-survivors (n = 94) had similar PWV (14.2 ± 3.6 versus 14.9 ± 3.8 m/s, respectively; p = 0.139). In contrast, non-survivors had significantly lower C T than survivors (0.198 ± 0.128 versus 0.221 ± 0.1 mL/mmHg; p = 0.018). C T was a significant predictor of mortality (p = 0.022, odds ratio = 0.326), while PWV was not (p = 0.202), even after adjustment for gender, mean pressure and heart rate. Age was an independent determinant of C T (p = 0.016), but not of PWV. C T, estimated by a novel method, can predict all-cause mortality in the elderly. C T may be more sensitive arterial biomarker than PWV regarding CV risk assessment.

Validation of a novel and existing algorithms for the estimation of pulse transit time: advancing the accuracy in pulse wave velocity measurement.

The method used for pulse transit time (PTT) estimation critically affects the accuracy and precision of regional pulse wave velocity (PWV) measurements. Several methods of PTT estimation exist, often yielding substantially different PWV values. Since there is no analytic way to determine PTT in vivo, these methods cannot be validated except by using in silico or in vitro models of known PWV and PTT values. We aimed to validate and compare the most commonly used "foot-to-foot" algorithms, namely, the " diastole-minimum," "tangential," "maximum first derivative," and "maximum second derivative" methods. Also, we propose a new "diastole-patching" method aiming to increase the accuracy and precision in PWV measurements. We simulated 2,000 cases under different hemodynamic conditions using an accurate, validated, distributed, one-dimensional arterial model. The new algorithm detects and "matches" a specific region of the pressure wave foot between the proximal and distal waveforms instead of determining characteristic points. The diastole-minimum and diastole-patching methods showed excellent agreement compared with "real" PWV values of the model, as indicated by high values of the intraclass correlation coefficient (>0.86). The diastole-patching method resulted in low bias (absolute mean difference: 0.26 m/s). In contrast, PWV estimated by the maximum first derivative, maximum second derivative, and tangentia methods presented low to moderate agreement and poor accuracy (intraclass correlation coefficient: <0.79 and bias: >0.9 m/s). The diastole-patching method yielded PWV measurements with the highest agreement, accuracy, and precision and lowest variability.

Generic and patient-specific models of the arterial tree.

Recent advance in imaging modalities used frequently in clinical routine can provide description of the geometrical and hemodynamical properties of the arterial tree in great detail. The combination of such information with models of blood flow of the arterial tree can provide further information, such as details in pressure and flow waves or details in the local flow field. Such knowledge maybe be critical in understanding the development or state of arterial disease and can help clinicians perform better diagnosis or plan better treatments. In the present review, the state of the art of arterial tree models is presented, ranging from 0-D lumped models, 1-D wave propagation model to more complex 3-D fluid-structure interaction models. Our development of a generic and patient-specific model of the human arterial tree permitting to study pressure and flow waves propagation in patients is presented. The predicted pressure and flow waveforms are in good agreement with the in vivo measurements. We discuss the utility of these models in different clinical application and future development of interest.

On the estimation of total arterial compliance from aortic pulse wave velocity.

Total arterial compliance (C(T)) is a main determinant of cardiac afterload, left ventricular function and arterio-ventricular coupling. C(T) is physiologically more relevant than regional aortic stiffness. However, direct, in vivo, non-invasive, measurement of C(T) is not feasible. Several methods for indirect C(T) estimation require simultaneous recording of aortic flow and pressure waves, limiting C(T) assessment in clinical practice. In contrast, aortic pulse wave velocity (aPWV) measurement, which is considered as the "gold standard" method to assess arterial stiffness, is noninvasive and relatively easy. Our aim was to establish the relation between aPWV and C(T). In total, 1000 different hemodynamic cases were simulated, by altering heart rate, compliance, resistance and geometry using an accurate, distributed, nonlinear, one-dimensional model of the arterial tree. Based on Bramwell-Hill theory, the formula C(T) = k • aPWV(-2) was found to accurately estimate C(T) from aPWV. Coefficient k was determined both analytically and by fitting C(T) vs. aPWV data. C(T) estimation may provide an additional tool for cardiovascular risk (CV) assessment and better management of CV diseases. C(T) could have greater impact in assessing elderly population or subjects with elevated arterial stiffness, where aPWV seem to have limited prognostic value. Further clinical studies should be performed to validate the formula in vivo.

3D simulation of the aqueous flow in the human eye.

Glaucoma results in an increase in the resistance of the aqueous humor outflow, which in turn leads to an increase of the intraocular pressure (IOP). Several treatments are proposed to reduce and stabilize the IOP that include medications, filtering surgery and glaucoma drainage devices (GDD). So far computational fluid dynamics (CFD) modeling of the eye drainage system has not yet been well studied. Therefore our goal was to provide a 3D CFD model of the eye based on the anatomy of a real human eye. Such a tool would serve for future evaluation of new glaucoma surgical techniques involving, for example, GDD. The model was based on stacks of microphotographs from human eye slides from which digital processing of the images of the eye structure and 3D reconstruction of the model were performed. Simulations of the distribution of pressure and flow velocity in the model of a healthy eye gave results comparable to physiology references. Mimicking glaucoma conditions led to an increase of the IOP from normal range, which went down to lower values after a filtering procedure. Further refinements in the boundary conditions for the filtering procedure shall improve the accuracy of this innovative tool for modeling glaucoma surgery.

The "systolic volume balance" method for the noninvasive estimation of cardiac output based on pressure wave analysis.

Cardiac output (CO) monitoring is essential for the optimal management of critically ill patients. Several mathematical methods have been proposed for CO estimation based on pressure waveform analysis. Most of them depend on invasive recording of blood pressure and require repeated calibrations, and they suffer from decreased accuracy under specific conditions. A new systolic volume balance (SVB) method, including a simpler empirical form (eSVB), was derived from basic physical principles that govern blood flow and, in particular, a volume balance approach for the conservation of mass ejected into and flowed out of the arterial system during systole. The formulas were validated by a one-dimensional model of the systemic arterial tree. Comparisons of CO estimates between the proposed and previous methods were performed in terms of agreement and accuracy using "real" CO values of the model as a reference. Five hundred and seven different hemodynamic cases were simulated by altering cardiac period, arterial compliance, and resistance. CO could be accurately estimated by the SVB method as follows: CO = C × PP(ao)/(T - P(sm) × T(s)/P(m)) and by the eSVB method as follows: CO = k × C × PP(ao)/T, where C is arterial compliance, PP(ao) is aortic pulse pressure, T is cardiac period, P(sm) is mean systolic pressure, T(s) is systolic duration, P(m) is mean pressure, and k is an empirical coefficient. SVB applied on aortic pressure waves did not require calibration or empirical correction for CO estimation. An empirical coefficient was necessary for brachial pressure wave analysis. The difference of SVB-derived CO from model CO (for brachial waves) was 0.042 ± 0.341 l/min, and the limits of agreement were -0.7 to 0.6 l/min, indicating high accuracy. The intraclass correlation coefficient and root mean square error between estimated and "real" CO were 0.861 and 0.041 l/min, respectively, indicating very good accuracy. eSVB also provided accurate estimation of CO. An in vivo validation study of the proposed methods remains to be conducted.