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

MEMSurgery: An integrated test-bed for vascular surgery

Abstract Many surgical procedures require skillful manipulations of blood vessels, especially in conventional invasive or minimally invasive surgical procedures. Current surgical methods do not allow the surgeon to receive any real time feedback of the tissue properties when operating on the vessel. As a result, the unintentional application of excessive force may damage the blood vessel. To minimize such trauma, and to study the interaction of surgical instruments with the vessel structure, we have developed an integrated surgical testbed called MEMSurgery (Microelectromechanical Sensory augmented Surgery). The test-bed integrates four elements: a) force sensors mounted on surgical appliances, b) a feedback control mechanism utilizing the intrinsic mechanical properties of the blood vessel, c) feedback of the force applied on the tissue back to the surgeon through a haptic feedback device, and d) visual feedback by a graphical computer model of the vessel. Finally, we evaluate the performance of MEMSurgery by testing the hypothesis that the combination of haptic feedback, feedback control based on vascular mechanical properties, and real-time visual representation of the vessel will help the surgeon decrease the probability of applying excess force while occluding the blood vessel. To this end, we designed a rodent experimental model to obtain the ideal minimum occlusion force (MOF). After a series of human performance studies, and subsequent comparison to direct application of force on the forceps (without feedback), the results show that the probability of applying reasonable MOF increases from 35.5% to 80%. After a brief training period, the probability increases to 90%

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

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

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)

A brain-computer interface with vibrotactile biofeedback for haptic information

<p>Abstract</p> <p>Background</p> <p>It has been suggested that Brain-Computer Interfaces (BCI) may one day be suitable for controlling a neuroprosthesis. For closed-loop operation of BCI, a tactile feedback channel that is compatible with neuroprosthetic applications is desired. Operation of an EEG-based BCI using only <it>vibrotactile feedback</it>, a commonly used method to convey haptic senses of contact and pressure, is demonstrated with a high level of accuracy.</p> <p>Methods</p> <p>A Mu-rhythm based BCI using a motor imagery paradigm was used to control the position of a virtual cursor. The cursor position was shown visually as well as transmitted haptically by modulating the intensity of a vibrotactile stimulus to the upper limb. A total of six subjects operated the BCI in a two-stage targeting task, receiving only vibrotactile biofeedback of performance. The location of the vibration was also systematically varied between the left and right arms to investigate location-dependent effects on performance.</p> <p>Results and Conclusion</p> <p>Subjects are able to control the BCI using only vibrotactile feedback with an average accuracy of 56% and as high as 72%. These accuracies are significantly higher than the 15% predicted by random chance if the subject had no voluntary control of their Mu-rhythm. The results of this study demonstrate that vibrotactile feedback is an effective biofeedback modality to operate a BCI using motor imagery. In addition, the study shows that placement of the vibrotactile stimulation on the biceps ipsilateral or contralateral to the motor imagery introduces a significant bias in the BCI accuracy. This bias is consistent with a drop in performance generated by stimulation of the contralateral limb. Users demonstrated the capability to overcome this bias with training.</p

Revisiting QRS detection methodologies for portable, wearable, battery-operated, and wireless ECG systems

Cardiovascular diseases are the number one cause of death worldwide. Currently, portable battery-operated systems such as mobile phones with wireless ECG sensors have the potential to be used in continuous cardiac function assessment that can be easily integrated into daily life. These portable point-of-care diagnostic systems can therefore help unveil and treat cardiovascular diseases. The basis for ECG analysis is a robust detection of the prominent QRS complex, as well as other ECG signal characteristics. However, it is not clear from the literature which ECG analysis algorithms are suited for an implementation on a mobile device. We investigate current QRS detection algorithms based on three assessment criteria: 1) robustness to noise, 2) parameter choice, and 3) numerical efficiency, in order to target a universal fast-robust detector. Furthermore, existing QRS detection algorithms may provide an acceptable solution only on small segments of ECG signals, within a certain amplitude range, or amid particular types of arrhythmia and/or noise. These issues are discussed in the context of a comparison with the most conventional algorithms, followed by future recommendations for developing reliable QRS detection schemes suitable for implementation on battery-operated mobile devices.Mohamed Elgendi, Björn Eskofier, Socrates Dokos, Derek Abbot