Notes

Prism adaptation outcomes inside sophisticated regional soreness symptoms: The therapo-physiological one circumstance new design and style exploratory record.
We have provided the first comparison of non-invasive and implanted EMG sensors as input signals for torque estimates in healthy individuals and SCI patients.

Implanted EMG sensors have the potential to be used as a reliable input for assistive exoskeleton joint torque actuation.
Implanted EMG sensors have the potential to be used as a reliable input for assistive exoskeleton joint torque actuation.
Photoplethysmography (PPG) waveform analysis is being increasingly investigated for continuous, non-invasive, and cuff-less blood pressure (BP) measurement. However, the efficacy of this approach and the useful features and models remain largely unclear. PLX5622 The objectives were to develop easy-to-understand models relating PPG waveform features to BP changes (after a cuff calibration) and to determine their value in BP measurement accuracy.

The study data comprised finger, toe, and ear PPG waveforms, an ECG waveform, and reference manual cuff BP measurements from 32 human subjects (25% hypertensive) before and after slow breathing, mental arithmetic, cold pressor, and nitroglycerin administration. Stepwise linear regression was employed to create parsimonious models for predicting the intervention-induced BP changes from popular PPG waveform features, pulse arrival time (PAT, time delay between ECG R-wave and PPG foot), and subject demographics. Leave-one-subject-out cross validation was applied to compare the BP change prediction root-mean-squared-errors (RMSEs) of the resulting models to reference models in which PPG waveform features were excluded.

Finger b-time (PPG foot to minimum second derivative time interval) and ear STT (PPG amplitude divided by maximum derivative), when combined with PAT, reduced the systolic BP change prediction RMSE of reference models by 6-7% (p <0.022). Ear STT together with pulse width reduced the diastolic BP change prediction RMSE of the reference model by 13% (p=0.003).

The two PPG fast upstroke time intervals can offer some added value in cuff-less BP trending.

This study offers important information towards achieving non-invasive and passive BP monitoring without a cuff.
This study offers important information towards achieving non-invasive and passive BP monitoring without a cuff.Quantitative assessment of myocardial stiffness is crucial to understand and evaluate cardiac biomechanics and function. Despite the recent progresses of ultrasonic shear wave elastography, quantitative evaluation of myocardial stiffness still remains a challenge because of strong elastic anisotropy. In this paper we introduce a smart ultrasound approach for non-invasive real-time quantification of shear wave velocity (SWV) and elastic fractional anisotropy (FA) in locally transverse isotropic elastic medium such as the myocardium. The approach relies on a simultaneous multidirectional evaluation of the SWV without a prior knowledge of the fiber orientation. We demonstrated that it can quantify accurately SWV in the range of 1.5 to 6 m/s in transverse isotropic medium (FA less then 0.7) using numerical simulations. Experimental validation was performed on calibrated phantoms and anisotropic ex vivo tissues. A mean absolute error of 0.22 m/s was found when compared to gold standard measurements. Finally, in vivo feasibility of myocardial anisotropic stiffness assessment was evaluated in four healthy volunteers on the antero-septo basal segment and on anterior free wall of the right ventricle (RV) in end-diastole. A mean longitudinal SWV of 1.08 0.20 m/s was measured on the RV wall and 1.74 0.51 m/s on the Septal wall with a good intra-volunteer reproducibility (0.18 m/s). This approach has the potential to become a clinical tool for the quantitative evaluation of myocardial stiffness and diastolic function.Biological macromolecule drugs or biologics are not suited for commonly preferred oral delivery due to their intrinsic instability and physical, chemical, or immunological barriers to the gastrointestinal tract. Ingestible capsule robots (ICR) have become a versatile platform, including use for drug delivery applications for various gastrointestinal pathologies with future potential for systemic drug delivery. In this work, a tissue attachment mechanism (TAM) for a drug delivery ICR is introduced that can facilitate a non-invasive systemic delivery of unaltered biologics via direct injection through the insensate layers of the small intestine. The main prerequisite for achieving systemic drug delivery via this device is to have strong tissue attachment of the TAM. This study aimed to optimize the attachment success rate for drug delivery and characterize attachment duration in vivo. A fractional factorial approach was used in vivo to identify and optimize factors that most influence attachment of the TAM to maximize attachment rate. Multiple in vivo optimization levels were performed using the small intestine of anesthetized pigs, and an attachment success rate of 92% was achieved. Optimal TAMs were surgically placed in vivo to determine the duration of attachment following anesthetization and surgery recovery. The average in vivo attachment duration was 32.29.4 hours. This work establishes a device for consistent and reliable attachment duration, making the TAM a suitable candidate for a 24-hour systemic drug delivery platform.
The speed of sound (SoS) has great potential as a quantitative imaging biomarker since it is sensitive to pathological changes in tissues. In this paper, a target-aware deep neural (TAD) network reconstructing an SoS image quantitatively from pulse-echo phase-shift maps gathered from a single conventional ultrasound probe is presented.

In the proposed TAD network, the reconstruction process is guided by feature maps created from segmented target images for accuracy and contrast. In addition, the feature extraction process utilizes phase difference information instead of direct pulse-echo radio frequency (RF) data for robust image reconstruction against noise in the pulse-echo data.

The TAD network outperforms the fully convolutional network in root mean square error (RMSE), contrast-to-noise ratio (CNR), and structural similarity index (SSIM) in the presence of nearby reflectors. The measured RMSE and CNR are 5.4 m/s and 22 dB, respectively with the tissue attenuation coefficient of 2 dB/cm/MHz, which are 72% and 13 dB improvement over the state of the art design in RMSE and CNR, respectively.
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