Response to reflected-force feedback to fingers in teleoperations

Reflected-force feedback is an important aspect of teleoperations. The objective is to determine the ability of the human operator to respond to that force. Telerobotics operation is simulated by computer control of a motor-driven device with capabilities for programmable force feedback and force measurement. A computer-controlled motor drive is developed that provides forces against the fingers as well as (angular) position control. A load cell moves in a circular arc as it is pushed by a finger and measures reaction forces on the finger. The force exerted by the finger on the load cell and the angular position are digitized and recorded as a function of time by the computer. Flexure forces of the index, long and ring fingers of the human hand in opposition to the motor driven load cell are investigated. Results of the following experiments are presented: (1) Exertion of maximum finger force as a function of angle; (2) Exertion of target finger force against a computer controlled force; and (3) Test of the ability to move to a target force against a force that is a function of position. Averaged over ten individuals, the maximum force that could be exerted by the index or long finger is about 50 Newtons, while that of the ring finger is about 40 Newtons. From the tests of the ability of a subject to exert a target force, it was concluded that reflected-force feedback can be achieved with the direct kinesthetic perception of force without the use of tactile or visual clues

A Method for 3-D Printing Patient-Specific Prosthetic Arms with High Accuracy Shape and Size

Limb amputation creates serious emotional and functional damage to the one who lost a limb. For some upper limb prosthesis users, comfort and appearance are among the desired features. The objective of this paper is to develop a streamlined methodology for prosthesis design by recreating the shape and size of an amputated arm with high accuracy through 3-D printing and silicone casting. To achieve this, the computer tomography (CT) images of the patient's affected and non-affected arms were scanned. Next, the geometry of the socket and the prosthetic arm were designed according the mirrored geometry of the non-affected arm through computer-aided design software. The support structure and the moulds were 3-D printed, and the prosthetic arm was casted with a silicone material. To validate the replication, the shape of the socket and prosthetic arm were quantitatively compared with respect to the source CT scan from the patient. The prosthetic arm was found to have high accuracy on the basis of the Dice Similarity Coefficient (DSC; 0.96), percent error (0.67%), and relative mean distance (0.34 mm, SD = 0.48 mm). Likewise, the socket achieved high accuracy based on those measures: DSC (0.95), percent error (2.97%), and relative mean distance (0.46 mm, SD = 1.70 mm) The liner, socket, and prosthetic arm were then shipped to the patient for fitting. The patient found the fit of the socket and the replication of the shape and the size of the prosthesis to be desirable. Overall, this paper demonstrates that CT imaging, computed-aided design, desktop 3-D printing, and silicone casting can achieve patient-specific cosmetic prosthetic arms with high accuracy. - 2013 IEEE.This work was supported by the NPRP Grant from the Qatar National Research Fund under Grant NPRP 7-673-2-251. The statements made herein are solely the responsibility of the authors.Scopu

Effect of temperature, relative humidity and moisture content on germination percentage of wheat stored in different storage structures

The paper presents information regarding the pattern of changes in the environmental conditions (i.e. temperature, relative humidity and moisture content) on the stored wheat in Galvanized Iron Corrugated (GIC) silo, Godown storage and CAP storage.  The grain moisture content in the silo increased from 11.20% to 17.08% wet basis (w.b.), in bag storage increased from 11.20% to 17.25%, and in CAP storage increased from 11.20% to 17.19% wet basis (w.b.) during the storage period from April 06 to November 06.  The moisture content of the wheat grain then slightly decreased during the storage period from November 06 to April 07.  The temperature of the grain inside silo was 29.30℃ while at the end of the storage period, the temperature was 42.90℃.  The initial grain temperature inside Godown storage was 29.30℃ and at the end of the storage period, it was 32.31℃.  The initial grain temperature inside CAP storage was 29.10℃ and it increased to 39.94℃ at the end of the storage period.  The relative humidity in the silo was 16.1% lower than the ambient relative humidity.  The germination percentage of grain inside the silo was decreased from 86.70% to 78.60%, in Godown storage it decreased from 86.70% to 53.30%, and in CAP storage it decreased from 86.70% to 46.60% during the storage period from April to September. Keywords: temperature, moisture content, relative humidity, germination percentage, wheat, GIC, silo, Godown, CA

‘Stick them to the cross’:Anti-trafficking apps and the production of ignorance

There is a long history of ignorance production around trafficking in human beings. A proliferation of anti-trafficking apps plays an important role in the reinforcement of this ignorance. Anti-trafficking apps work in different ways to other (mis)information tools, but there is a lack of academic research on the topic. This paper addresses this gap through an agnotological approach: focusing on how ignorance is produced and becomes productive, rather than seeing ignorance as just a lack of knowledge. We investigate how anti-trafficking apps are used to manipulate (mis)understandings of and responses to human trafficking by enabling new types of awareness raising, user participation and ignorance production. The networking of ignorance that this allows – and the integration of this into new aspects of everyday life – illustrates de Goede’s (2012) warning that “the network is problematic as a security technique…because, ultimately, it has no outside” (p. 228)

Reliability of old and new ventricular fibrillation detection algorithms for automated external defibrillators

BACKGROUND: A pivotal component in automated external defibrillators (AEDs) is the detection of ventricular fibrillation by means of appropriate detection algorithms. In scientific literature there exists a wide variety of methods and ideas for handling this task. These algorithms should have a high detection quality, be easily implementable, and work in real time in an AED. Testing of these algorithms should be done by using a large amount of annotated data under equal conditions. METHODS: For our investigation we simulated a continuous analysis by selecting the data in steps of one second without any preselection. We used the complete BIH-MIT arrhythmia database, the CU database, and the files 7001 – 8210 of the AHA database. All algorithms were tested under equal conditions. RESULTS: For 5 well-known standard and 5 new ventricular fibrillation detection algorithms we calculated the sensitivity, specificity, and the area under their receiver operating characteristic. In addition, two QRS detection algorithms were included. These results are based on approximately 330 000 decisions (per algorithm). CONCLUSION: Our values for sensitivity and specificity differ from earlier investigations since we used no preselection. The best algorithm is a new one, presented here for the first time

P and R Wave Detection in Complete Congenital Atrioventricular Block

Complete atrioventricular block (type III AVB) is characterized by an absence of P wave transmission to ventricles. This implies that QRS complexes are generated in an autonomous way and are not coordinated with P waves. This work introduces a new algorithm for the detection of P waves for this type of pathology using non-invasive electrocardiographic surface leads. The proposed algorithm is divided into three stages. In the first stage, the R waves located by a QRS detector are used to generate the RR series and time references for the other stages of the algorithm. In the second stage, the ventricular activity (QT segment) is removed by using an adaptive filter that obtains an averaged pattern of the QT segment. In the third stage, a new P wave detector is applied to the residual signal obtained after QT cancellation in order to detect P wave locations and get the PP time series. Eight Holter records from patients with congenital type III AVB were used to verify the proposed algorithm. Although further improvements should be made to improve the algorithm¿s performance, the results obtained show high average values of sensitivity (90.52 %) and positive prediction (90.98%)

Guiding Brain Tumor Resection Using Surface-Enhanced Raman Scattering Nanoparticles and a Hand-Held Raman Scanner

The current difficulty in visualizing the true extent of malignant brain tumors during surgical resection represents one of the major reasons for the poor prognosis of brain tumor patients. Here, we evaluated the ability of a hand-held Raman scanner, guided by surface-enhanced Raman scattering (SERS) nanoparticles, to identify the microscopic tumor extent in a genetically engineered RCAS/tv-a glioblastoma mouse model. In a simulated intraoperative scenario, we tested both a static Raman imaging device and a mobile, hand-held Raman scanner. We show that SERS image-guided resection is more accurate than resection using white light visualization alone. Both methods complemented each other, and correlation with histology showed that SERS nanoparticles accurately outlined the extent of the tumors. Importantly, the hand-held Raman probe not only allowed near real-time scanning, but also detected additional microscopic foci of cancer in the resection bed that were not seen on static SERS images and would otherwise have been missed. This technology has a strong potential for clinical translation because it uses inert gold-silica SERS nanoparticles and a hand-held Raman scanner that can guide brain tumor resection in the operating room

Real Time QRS Detection Based on M-ary Likelihood Ratio Test on the DFT Coefficients

This paper shows an adaptive statistical test for QRS detection of electrocardiography (ECG) signals. The method is based on a M-ary generalized likelihood ratio test (LRT) defined over a multiple observation window in the Fourier domain. The motivations for proposing another detection algorithm based on maximum a posteriori (MAP) estimation are found in the high complexity of the signal model proposed in previous approaches which i) makes them computationally unfeasible or not intended for real time applications such as intensive care monitoring and (ii) in which the parameter selection conditions the overall performance. In this sense, we propose an alternative model based on the independent Gaussian properties of the Discrete Fourier Transform (DFT) coefficients, which allows to define a simplified MAP probability function. In addition, the proposed approach defines an adaptive MAP statistical test in which a global hypothesis is defined on particular hypotheses of the multiple observation window. In this sense, the observation interval is modeled as a discontinuous transmission discrete-time stochastic process avoiding the inclusion of parameters that constraint the morphology of the QRS complexes.This work has received research funding from the Spanish government (www.micinn.es) under project TEC2012 34306 (DiagnoSIS, Diagnosis by means of Statistical Intelligent Systems, 70K€) and projects P09-TIC-4530 (300K€) and P11-TIC-7103 (156K€) from the Andalusian government (http://www.juntadeandalucia.es/organismo​s/economiainnovacioncienciayempleo.html)

Bearing signal separation enhancement with application to helicopter transmission system

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.Bearing vibration signal separation is essential for fault detection of gearboxes, especially where the vibration is nonstationary, susceptible to background noise, and subjected to an arduous transmission path from the source to the receiver. This paper presents a methodology for improving fault detection via a series of vibration signal processing techniques, including signal separation, synchronous averaging (SA), spectral kurtosis (SK), and envelope analysis. These techniques have been tested on experimentally obtained vibration data acquired from the transmission system of a CS-29 Category A helicopter gearbox operating under different bearing damage conditions. Results showed successful enhancement of bearing fault detection on the second planetary stage of the gearbo