Integral admittance shaping: A unified framework for active exoskeleton control

© 2015 Elsevier B.V. Current strategies for lower-limb exoskeleton control include motion intent estimation, which is subject to inaccuracies in muscle torque estimation as well as modeling error. Approaches that rely on the phases of a uniform gait cycle have proven effective, but lack flexibility to aid other kinds of movement. This research aims at developing a more versatile control that can assist the lower limbs independently of the movement attempted. Our control strategy is based on modifying the dynamic response of the human limbs, specifically their mechanical admittance. Increasing the admittance makes the lower limbs more responsive to any muscle torque generated by the human user. We present Integral Admittance Shaping, a unified mathematical framework for: (a) determining the desired dynamic response of the coupled system formed by the human limb and the exoskeleton, and (b) synthesizing an exoskeleton controller capable of achieving said response. The present control formulation focuses on single degree-of-freedom exoskeleton devices providing performance augmentation. The algorithm generates a desired shape for the frequency response magnitude of the integral admittance (torque-to-angle relationship) of the coupled system. Simultaneously, it generates an optimal feedback controller capable of achieving the desired response while guaranteeing coupled stability and passivity. The potential effects of the exoskeleton's assistance are motion amplification for the same joint torque, and torque reduction for the same joint motion. The robustness of the derived exoskeleton controllers to parameter uncertainties is analyzed and discussed. Results from initial trials using the controller on an experimental exoskeleton are presented as well

An admittance shaping controller for exoskeleton assistance of the lower extremities

We present a method for lower-limb exoskeleton control that defines assistance as a desired dynamic response for the human leg. Wearing the exoskeleton can be seen as replacing the leg's natural admittance with the equivalent admittance of the coupled system. The control goal is to make the leg obey an admittance model defined by target values of natural frequency, peak magnitude and zero-frequency response. No estimation of muscle torques or motion intent is necessary. Instead, the controller scales up the coupled system's sensitivity transfer function by means of a compensator employing positive feedback. This approach increases the leg's mobility and makes the exoskeleton an active device capable of performing net positive work on the limb. Although positive feedback is usually considered destabilizing, here performance and robust stability are successfully achieved through a constrained optimization that maximizes the system's gain margins while ensuring the desired location of its dominant poles

Integral Admittance Shaping for Exoskeleton Control

A wide variety of strategies have been developed for assisting human locomotion using powered exoskeletons. Although these strategies differ in their aims as well as the control methods employed, they have the implicit property of causing a virtual modification of the dynamic response of the human limb. We use this property of the exoskeletons action to formulate a unified control design framework called Integral Admittance Shaping, which designs exoskeleton controllers capable of producing the desired dynamic response for the assisted limb. In this framework, a virtual increase in the admittance of the limb is produced by coupling it to an exoskeleton that exhibits active behavior. Specifically, our framework shapes the magnitude profile of the integral admittance (i.e. torque-to-angle relationship) of the coupled human-exoskeleton system, such that the desired assistance is achieved. This framework also ensures that the coupled stability and passivity are guaranteed. This paper presents a formulation of Integral Admittance Shaping for single degree-of-freedom (1-DOF) exoskeleton devices. We also present experimental results on a modified version of Honda’s Stride Management Assist (SMA) device that successfully demonstrate motion amplification of the assisted hip joint during walking

Highly Sensitive C-Reactive Protein and Troponin T – Morbidity Predictor in Ischemic Stroke

Ischemic Heart Disease is the leading cause of mortality and morbidity in the developing world. Compared to western countries the incidence of ischemic heart disease is 10 years earlier in Indian population. Urban India has more IHD burden compared to rural India. Diabetes is another global pandemic with nearly 3.4 million diabetics in the world according to 2011 WHO report. The prevalence is expected to increase in multitudes in the upcoming years with India being the diabetic capital of the world. Despite being an independent risk factor for cardiovascular events it is found is association with other cardiovascular co morbid conditions like hypertension, dyslipidemia, atherosclerosis and other metabolic syndrome. Diabetes is now being recognised as a cardiovascular disease equivalent rather than being considered as an individual risk factor. Various cardiovascular risk assessment and mortality predictor markers are available. Mean platelet volume measured by hemolysers assess platelet size and activity. Platelets produced in stressful conditions are large and reactive. It has been shown that diabetics too have larger and reactive platelets compared to non diabetics. This mean platelet volume measured has been shown to a good predictor of cardiovascular events in many studies. In our study conducted in kanyakumari government medical college hospital , Asaripallam the study population includes 100 patients admitted to ICCU with STEMI within 12 hours of onset of chest pain undergoing thrombolysis with streptokinase. Both diabetics and non diabetics were enrolled. Mean Platelet Volume was measured in these patients within half an hour of admission and before the administration of antiplatelets drugs and thrombolysis, The sample was collected in EDTA bottle and was tested within half an hour to rule out sampling error. Known diabetics and patients who were diagnosed to be diagnosed to be diabetic after admission was checked for HbA1c values for determining glycemic control. The patients were followed up for a period of 1 month and assessed for mortality and morbidity. Only patients with ST segment elevation Myocardial infarction undergoing thrombolysis with streptokinase was enrolled in this study. Patients presenting with NSTEMI and unstable angina were excluded. The main aim and objective of our study was to compare mortality and morbidity among diabetics and non diabetics presenting with STEMI using Mean platelet Volume as an indicator. In this study we conducted in our college with this limited study population,we found that • MPV was higher in diabetics compared to non diabetics. • MPV has positive correlation with overall mortality ; mortality higher with higher values of MPV. • MPV correlated with admission hemodynamic status assessed by TIMI and KILLIP score. • MPV had significant correlation with HbA1c values. • MPV can be used as a predictor of long term cardiovascular mortality

SFRP4 signalling of apoptosis and angiostasis uses nitric oxide-cGMP-permeability axis of endothelium

Nitric oxide (NO) plays a critical role in endothelial functions such as cellular migration, vascular permeability and angiogenesis. Angiogenesis, the formation of new blood vessels from "pre-existing" ones is a carefully regulated process and essential during reproduction, development and wound healing. Previously our lab group reported that Secreted Frizzled-Related Protein 4 (sFRP4) could inhibit angiogenesis in both in vitro and in vivo conditions. sFRP4 belongs to a family of secreted glycoproteins that function as antagonists of the canonical Wnt signalling pathway. Although the pro-apoptotic role of sFRP4 is well discussed in literature, little is known in regards to its anti-angiogenic property. The objective of this study was to elucidate sFRP4 implications in NO biology of the endothelium. Results demonstrate that sFRP4 causes endothelial dysfunction by suppressing NO-cGMP signaling and elevating corresponding ROS levels. The imbalance between NO and ROS levels results in apoptosis and subsequent leakiness of endothelium as confirmed in vivo (Texas red/Annxin - CAM assay) and in vitro (Monolayer permeability assay) conditions. Furthermore utilizing peptides synthesized from the CRD domain of sFRP4, our results showed that while these peptides were able to cause endothelial dysfunctions, they did not cause apoptosis of the endothelial cells. Thereby confirming that sFRP4 can mediate its anti-angiogenic effect independent of its pro-apoptotic property. In conclusion, the current study reports that sFRP4-mediated anti-angiogenesis occurs as a result of impaired NO-cGMP signaling which in turn allow for elevation of redox levels and promotion of apoptosis of endothelial cells

Protein targets in Mycobacterium tuberculosis and their inhibitors for therapeutic implications: A narrative review

Advancement in the area of anti-tubercular drug development has been full-fledged, yet, a very less number of drug molecules have reached phase II clinical trials, and therefore "End-TB" is still a global challenge. Inhibitors to specific metabolic pathways of Mycobacterium tuberculosis (Mtb) gain importance in strategizing anti-tuberculosis drug discovery. The lead compounds that target DNA replication, protein synthesis, cell wall biosynthesis, bacterial virulence and energy metabolism are emerging as potential chemotherapeutic options against Mtb growth and survival within the host. In recent times, the in silico approaches have become most promising tools in the identification of suitable inhibitors for specific protein targets of Mtb. An update in the fundamental understanding of these inhibitors and the mechanism of interaction may bring hope to future perspectives in novel drug development and delivery approaches. This review provides a collective impression of the small molecules with potential antimycobacterial activities and their target pathways in Mtb such as cell wall biosynthesis, DNA replication, transcription and translation, efflux pumps, antivirulence pathways and general metabolism. The mechanism of interaction of specific inhibitor with their respective protein targets has been discussed. The comprehensive knowledge of such an impactful area of research would essentially reflect in the discovery of novel drug molecules and effective delivery approaches. This narrative review encompasses the knowledge of emerging targets and promising chemical inhibitors that could potentially translate in to the anti-TB-drug discovery

Temperature dependence of the primary electron transfer in photosynthetic reaction centers from Rhodobacter sphaeroides

The primary electron transfer (ET) in reaction centers (RC) of Rhodobacter sphaeroides is investigated as a function of temperature with femtosecond time resolution. For temperatures from 300 to 25 K the ET to the bacteriopheophytin is characterized by a biphasic time dependence. The two time constants of τ1=3.5±0.4 ps and τ2=1.2±0.3 ps at T=300 K decrease continously with temperature to values of τ1=1.4±0.3 ps and τ2=0.3±0.15 ps at 25 K. The experimental results indicate that the ET is not thermally activated and that the same ET mechanisms are active at room and low temperatures. All observations are readily rationalized by a two-step ET model with the monomeric bacteriochlorophyll as a real electron carrier

Automated Glaucoma Detection Using Hybrid Feature Extraction in Retinal Fundus Images

Glaucoma is one of the most common causes of blindness. Robust mass screening may help to extend the symptom-free life for affected patients. To realize mass screening requires a cost-effective glaucoma detection method which integrates well with digital medical and administrative processes. To address these requirements, we propose a novel low cost automated glaucoma diagnosis system based on hybrid feature extraction from digital fundus images. The paper discusses a system for the automated identification of normal and glaucoma classes using higher order spectra (HOS), trace transform (TT), and discrete wavelet transform (DWT) features. The extracted features are fed to a support vector machine (SVM) classifier with linear, polynomial order 1, 2, 3 and radial basis function (RBF) in order to select the best kernel for automated decision making. In this work, the SVM classifier, with a polynomial order 2 kernel function, was able to identify glaucoma and normal images with an accuracy of 91.67%, and sensitivity and specificity of 90% and 93.33%, respectively. Furthermore, we propose a novel integrated index called Glaucoma Risk Index (GRI) which is composed from HOS, TT, and DWT features, to diagnose the unknown class using a single feature. We hope that this GRI will aid clinicians to make a faster glaucoma diagnosis during the mass screening of normal/glaucoma images

Approximation Algorithms for the Directed k-Tour and k-Stroll Problems

We consider two natural generalizations of the Asymmetric Traveling Salesman problem: the k-Stroll and the k-Tour problems. The input to the k-Stroll problem is a directed n-vertex graph with nonnegative edge lengths, an integer k, and two special vertices s and t. The goal is to find a minimum-length s-t walk, containing at least k distinct vertices. The k-Tour problem can be viewed as a special case of k-Stroll, where s = t. That is, the walk is required to be a tour, containing some pre-specified vertex s. When k = n, the k-Stroll problem becomes equivalent to Asymmetric Traveling Salesman Path, and k-Tour to Asymmetric Traveling Salesman. Our main result is a polylogarithmic approximation algorithm for the k-Stroll problem. Prior to our work, only bicriteria (O(log 2 k), 3)-approximation algorithms have been known, producing walks whose length is bounded by 3OPT, while the number of vertices visited is Ω(k / log 2 k). We also show a simple O(log 2 n / log log n)-approximation algorithm for the k-Tour problem. The best previously known approximation algorithms achieved min(O(log 3 k), O(log 2 n · log k / log log n))-approximation in polynomial time, and O(log 2 k)-approximation in quasipolynomial time.

GRMA: Generalized Range Move Algorithms for the efficient optimization of MRFs

Markov Random Fields (MRF) have become an important tool for many vision applications, and the optimization of MRFs is a problem of fundamental importance. Recently, Veksler and Kumar et al. proposed the range move algorithms, which are some of the most successful optimizers. Instead of considering only two labels as in previous move-making algorithms, they explore a large search space over a range of labels in each iteration, and significantly outperform previous move-making algorithms. However, two problems have greatly limited the applicability of range move algorithms: 1) They are limited in the energy functions they can handle (i.e., only truncated convex functions); 2) They tend to be very slow compared to other move-making algorithms (e.g., �-expansion and ��-swap). In this paper, we propose two generalized range move algorithms (GRMA) for the efficient optimization of MRFs. To address the first problem, we extend the GRMAs to more general energy functions by restricting the chosen labels in each move so that the energy function is submodular on the chosen subset. Furthermore, we provide a feasible sufficient condition for choosing these subsets of labels. To address the second problem, we dynamically obtain the iterative moves by solving set cover problems. This greatly reduces the number of moves during the optimization.We also propose a fast graph construction method for the GRMAs. Experiments show that the GRMAs offer a great speedup over previous range move algorithms, while yielding competitive solutions