Morsegroth3503

The assessment of lower limb oedema almost always involves measuring leg volume, and the gold-standard for this is the water displacement technique. As it is not very practical to use in a clinical routine, physicians prefer indirect methods such as anthropometric or bioimpedance measurements. In the case of "non-pitting" leg oedema, i.e. where the presence of oedema is not obvious, it may be challenging to estimate changes in leg volume using these methods separately. The combination of these two methods, however, gives interesting results, such as a new composite parameter that is much more robust and efficient than commonly used parameters.Clinical Relevance- This study demonstrates the benefit of using a composite anthropometric-impedimetric parameter to predict water displacement variations in the leg over the course of a day, rather than using parameters based solely on anthropometry or impedance. Our new parameter (C²-A²)/R0 showed a robust r² value of 61%, which is more than twice the r² values obtained using other simple or composite parameters.Recognizing human intentions from the human counterpart is very important in human-robot interaction applications. Surface electromyography(sEMG) has been considered as a potential source for motion intention because the signal represents the on-set timing and amplitude of muscle activation. It is also reported that sEMG has the advantage of knowing body movements ahead of actual movement. However, sEMG based applications suffer from electrode location variation because sEMG shows different characteristics whenever the skin condition is different. They need to recreate the estimation model if electrodes are attached to different locations or conditions. In this paper, we developed a sEMG torque estimation model for electrode location variation. A decomposition model of sEMG signals was developed to discriminate the muscle source signals for electrode location variation, and we verified this model without making a new torque estimation model. Torque estimation accuracy using the proposed method was increased by 24.8% and torque prediction accuracy was increased by 47.7% for the electrode location variation in comparison with the method without decomposition. Therefore, the proposed sEMG decomposition method showed an enhancement in torque estimation for electrode location variation.Bio-impedance analysis provides non-invasive estimation of body composition. Recently, applications based on bio-impedance measurement in skin tissue such as skin cancer diagnosis and skin composition monitoring have been studied. For scanning the electrical properties along the skin depth, the relationship between the electrode topologies and the depth sensitivity should be clarified. This work reports a systematic analysis on designing line electrode topologies to measure the bio-impedance of the skin layer at specific depth using a finite element method (FEM). Four electrodes consisting of two outer current electrodes and two inner voltage electrodes in the form of Wenner-Schlumberger array were employed on the top of a collagen layer as a skin model. The numerical results demonstrate a change in the effective depth of measurement depending on the electrode topologies, which also have a good agreement with an analytic solution. This study suggests a decision guideline for designing the electrode topologies to achieve target depth sensitivity in bio-impedance measurement of skin tissue.Clinical Relevance-This establishes the effect of electrode topologies on depth sensitivity in bio-impedance measurements in skin layer.Gastrointestinal slow wave activity is, in part, responsible for governing gut motility. Dysrhythmic slow wave activity has been associated with a number of functional motility disorders, but the mechanisms involved are poorly understood. There exist a number of transgenic small animal models with functional motility disorders. However, current slow wave mapping methods are targeted towards humans and large animals and are not readily translatable. To overcome these shortcomings, a novel electrode array was developed using photolithography. The developed photolithographic electrode array (PEA) was experimentally validated in vivo against a standard flexible printed circuit (FPC) array for comparison. Mean amplitudes of 0.13 ± 0.06 mV and 0.88 ± 0.05 mV were reported by the PEA and the FPC array, respectively. Mean signal to noise ratios (SNR) of 13.4 ± 6.4 dB and 8.3 ± 5.1 dB were achieved for the PEA and the FPC array, respectively. Our findings showed that the PEA acquired slow wave signals with higher amplitude and SNR. In this study, we showed that microfabrication techniques could be successfully implemented with optimized resolution for the investigation of normal and abnormal slow wave activity in smaller animals, which will enable a better understanding of the pathophysiological mechanisms and aid in the diagnosis and treatment of gastrointestinal motility disorders.Clinical Relevance - The ability to characterize the slow wave activity in transgenic animals with functional motility disorders would be a critical advance for the diagnosis and treatment of these disorders. Microfabrication techniques enable miniaturization of high-resolution electrode arrays suitable for mapping electrical activity in normal and transgenic small laboratory animals such as rats and mice.Intestinal motility is coordinated by myogenic, neuronal and hormonal factors. Myogenic control of motility via bioelectric slow waves (SW) has been investigated using low-resolution and high-resolution (HR) electrical mapping techniques. Due to the highly conformable and irregular surface of the gut, suboptimal coverage of HR recordings may occur. In this study we designed and developed an inflatable cuff as a platform to apply even pressure across the intestinal surface to achieve consistent and reliable recordings. The inflatable cuff and a HR electrode array were applied in vivo to demonstrate the reliability of SW signal acquisition over a range of inflatable pressures (0 - 5 mm Hg). The frequency, amplitude, percentage of viable signals and signal to noise ratio metrics of the SW signals were computed and compared. Overall, with an increase in inflatable pressure from 0 to 5 mm Hg, the frequency did not change, but the amplitude of the SWs decreased from 0.10 to 0.07 mV. The noise levels were consistent across the range of inflatable pressure levels and the percentage of viable SW recordings improved significantly from 57% to 74% after application of 1 mm Hg of pressure. The inflatable and conformable cuff presented in this study provides a reliable platform for HR mapping of bioelectrical events in the intestines and other conformable organs.Clinical Relevance- This framework improves the quality and reliability of bioelectrical high-resolution recordings obtained from the small intestine. In the future, these recordings will improve our understanding of the pathophysiological mechanisms governing intestinal motility disorders and may provide clinicians with new strategies for diagnosis and treatment.The objective of this study was to elucidate the dynamic mechanism of infant tongue movement during sucking. We developed an integrated device with sensors for three-dimensional force measurements applied by the tongue to an artificial nipple. Three mini-size built-in cantilever sensors were installed in each of three sides of the regular hexagonal prism (nine sensors in total) inside the artificial nipple. Signals from the force sensors were amplified and displayed on a PC monitor via USB in real time. We conducted measurements using the system and confirmed that signals were outputted from all nine sensors. The output waveforms and force distributions showed that the force applied was larger at the nipple tip than at the nipple root and moved from the nipple root to the nipple tip.Continuous monitoring of cardiac parameters such as blood pressure (BP) and pulse transit time (PTT) from wearable devices can improve the diagnosis and management of the cardiovascular disease. Continuous monitoring of these parameters depends on monitoring arterial pulse wave based on the blood volume changes in the artery using non-invasive sensors such as bio-impedance (Bio-Z). PTT and BP monitoring require the measurement of multiple pulse signals along the artery through the placement of multiple sensors within a small distance. Conventionally, these Bio-Z sensors are excited by a single shared current source, which results in low directivity and distortion of pulse signal due to the interaction of the different sensors together. For a localized pulse sensing, each sensor should focus on a certain point on the artery to provide the most accurate arterial pulse wave, which improves PTT and BP readings. In this paper, we propose a multi-source multi-frequency method for multi-sensor Bio-Z measurement that relies on using separate current sources for each sensor with different frequencies to allow the separation of these signals in the frequency domain, which results in isolation in the spatial domain. The effectiveness of the new method was demonstrated by a reduction in the inter-beat-interval (IBI) root mean square error (RMSE) by 19% and an increase of average PTT by 15% compared to the conventional method.Energy expenditure (EE) estimation is an important factor in tracking personal activity and preventing chronic diseases, such as obesity and diabetes. The challenge is to provide accurate EE estimations in free-living environment through portable and unobtrusive devices. In this paper, we present an experimental study to estimate energy expenditure during sitting, standing and treadmill walking using a smartwatch. We introduce a novel methodology, which aims to improve the EE estimation by first separating sedentary (sitting and standing) and non-sedentary (walking) activities, followed by estimating the walking speeds and then calculating the energy expenditure using advanced machine learning based regression models. selleck inhibitor Ten young adults participated in the experimental trials. Our results showed that combining activity type and walking speed information with the acceleration counts substantially improved the accuracy of regression models for estimating EE. On average, the activity-based models provided 7% better EE estimation than the traditional acceleration-based models.Functional status of patients is an important concept in clinical trials. It subsumes functional capacity, which is traditionally estimated by exercise tests, and functional performance, which is often estimated by questionnaires. Objectively measured physical activity by means of wearables devices containing accelerometers (PA) have recently been proposed as a novel and advantageous way to estimate physical status including capacity and performance. There is nonetheless insufficient evidence of the association between PA and traditional ways to estimate functional status. In the ACTIVATE clinical trial, cycle ergometry tests were performed multiple times in all 267 patients, PA was measured for a week prior to each cycle ergometry test, and questionnaires were answered daily during the same week. Pearson's correlation tests and clustering analysis revealed that PA, physical activity experience as assessed by questionnaires, and exercise endurance time as measured by the cycle ergometry test, are largely independent.