Cardiogoniometric parameters for detection of coronary artery disease at rest as a function of stenosis localization and distribution

Cardiogoniometry (CGM), a spatiotemporal electrocardiologic 5-lead method with automated analysis, may be useful in primary healthcare for detecting coronary artery disease (CAD) at rest. Our aim was to systematically develop a stenosis-specific parameter set for global CAD detection. In 793 consecutively admitted patients with presumed non-acute CAD, CGM data were collected prior to elective coronary angiography and analyzed retrospectively. 658 patients fulfilled the inclusion criteria, 405 had CAD verified by coronary angiography; the 253 patients with normal coronary angiograms served as the non-CAD controls. Study patients--matched for age, BMI, and gender--were angiographically assigned to 8 stenosis-specific CAD categories or to the controls. One CGM parameter possessing significance (P < .05) and the best diagnostic accuracy was matched to one CAD category. The area under the ROC curve was .80 (global CAD versus controls). A set containing 8 stenosis-specific CGM parameters described variability of R vectors and R-T angles, spatial position and potential distribution of R/T vectors, and ST/T segment alterations. Our parameter set systematically combines CAD categories into an algorithm that detects CAD globally. Prospective validation in clinical studies is ongoing.

A robotic system to train activities of daily living in a virtual environment

In the past decade, several arm rehabilitation robots have been developed to assist neurological patients during therapy. Early devices were limited in their number of degrees of freedom and range of motion, whereas newer robots such as the ARMin robot can support the entire arm. Often, these devices are combined with virtual environments to integrate motivating game-like scenarios. Several studies have shown a positive effect of game-playing on therapy outcome by increasing motivation. In addition, we assume that practicing highly functional movements can further enhance therapy outcome by facilitating the transfer of motor abilities acquired in therapy to daily life. Therefore, we present a rehabilitation system that enables the training of activities of daily living (ADL) with the support of an assistive robot. Important ADL tasks have been identified and implemented in a virtual environment. A patient-cooperative control strategy with adaptable freedom in timing and space was developed to assist the patient during the task. The technical feasibility and usability of the system was evaluated with seven healthy subjects and three chronic stroke patients.

High-resolution esophageal long-term ECG allows detailed atrial wave morphology analysis in case of atrial ectopic beats

Detection of arrhythmic atrial beats in surface ECGs can be challenging when they are masked by the R or T wave, or do not affect the RR-interval. Here, we present a solution using a high-resolution esophageal long-term ECG that offers a detailed view on the atrial electrical activity. The recorded ECG shows atrial ectopic beats with long coupling intervals, which can only be successfully classified using additional morphology criteria. Esophageal high-resolution ECGs provide this information, whereas surface long-term ECGs show poor atrial signal quality. This new method is a promising tool for the long-term rhythm monitoring with software-based automatic classification of atrial beats.

Comfort of two shoulder actuation mechanisms for arm therapy exoskeletons: a comparative study in healthy subjects

Robotic exoskeletons can be used to study and treat patients with neurological impairments. They can guide and support the human limb over a large range of motion, which requires that the movement trajectory of the exoskeleton coincide with the one of the human arm. This is straightforward to achieve for rather simple joints like the elbow, but very challenging for complex joints like the human shoulder, which is comprised by several bones and can exhibit a movement with multiple rotational and translational degrees of freedom. Thus, several research groups have developed different shoulder actuation mechanism. However, there are no experimental studies that directly compare the comfort of two different shoulder actuation mechanisms. In this study, the comfort and the naturalness of the new shoulder actuation mechanism of the ARMin III exoskeleton are compared to a ball-and-socket-type shoulder actuation. The study was conducted in 20 healthy subjects using questionnaires and 3D-motion records to assess comfort and naturalness. The results indicate that the new shoulder actuation is slightly better than a ball-and-socket-type actuation. However, the differences are small, and under the tested conditions, the comfort and the naturalness of the two tested shoulder actuations do not differ a lot.

Improving backdrivability in geared rehabilitation robots

Many rehabilitation robots use electric motors with gears. The backdrivability of geared drives is poor due to friction. While it is common practice to use velocity measurements to compensate for kinetic friction, breakaway friction usually cannot be compensated for without the use of an additional force sensor that directly measures the interaction force between the human and the robot. Therefore, in robots without force sensors, subjects must overcome a large breakaway torque to initiate user-driven movements, which are important for motor learning. In this technical note, a new methodology to compensate for both kinetic and breakaway friction is presented. The basic strategy is to take advantage of the fact that, for rehabilitation exercises, the direction of the desired motion is often known. By applying the new method to three implementation examples, including drives with gear reduction ratios 100-435, the peak breakaway torque could be reduced by 60-80%.

ARMin: a robot for patient-cooperative arm therapy

Task-oriented, repetitive and intensive arm training can enhance arm rehabilitation in patients with paralyzed upper extremities due to lesions of the central nervous system. There is evidence that the training duration is a key factor for the therapy progress. Robot-supported therapy can improve the rehabilitation allowing more intensive training. This paper presents the kinematics, the control and the therapy modes of the arm therapy robot ARMin. It is a haptic display with semi-exoskeleton kinematics with four active and two passive degrees of freedom. Equipped with position, force and torque sensors the device can deliver patient-cooperative arm therapy taking into account the activity of the patient and supporting him/her only as much as needed. The haptic display is combined with an audiovisual display that is used to present the movement and the movement task to the patient. It is assumed that the patient-cooperative therapy approach combined with a multimodal display can increase the patient's motivation and activity and, therefore, the therapeutic progress.

Energy harvesting through arterial wall deformation: design considerations for a magneto-hydrodynamic generator

As the complexity of active medical implants increases, the task of embedding a life-long power supply at the time of implantation becomes more challenging. A periodic renewal of the energy source is often required. Human energy harvesting is, therefore, seen as a possible remedy. In this paper, we present a novel idea to harvest energy from the pressure-driven deformation of an artery by the principle of magneto-hydrodynamics. The generator relies on a highly electrically conductive fluid accelerated perpendicularly to a magnetic field by means of an efficient lever arm mechanism. An artery with 10 mm inner diameter is chosen as a potential implantation site and its ability to drive the generator is established. Three analytical models are proposed to investigate the relevant design parameters and to determine the existence of an optimal configuration. The predicted output power reaches 65 μW according to the first two models and 135 μW according to the third model. It is found that the generator, designed as a circular structure encompassing the artery, should not exceed a total volume of 3 cm3.

Robot-aided neurorehabilitation of the upper extremities

Task-oriented repetitive movements can improve muscle strength and movement co-ordination in patients with impairments due to neurological lesions. The application of robotics and automation technology can serve to assist, enhance, evaluate and document the rehabilitation of movements. The paper provides an overview of existing devices that can support movement therapy of the upper extremities in subjects with neurological pathologies. The devices are critically compared with respect to technical function, clinical applicability, and, if they exist, clinical outcomes.

Manipulations to reduce simulator-related transient adverse health effects during simulated driving

User comfort during simulated driving is of key importance, since reduced comfort can confound the experiment and increase dropout rates. A common comfort-affecting factor is simulator-related transient adverse health effect (SHE). In this study, we propose and evaluate methods to adapt a virtual driving scene to reduce SHEs. In contrast to the manufacturer-provided high-sensory conflict scene (high-SCS), we developed a low-sensory conflict scene (low-SCS). Twenty young, healthy participants drove in both the high-SCS and the low-SCS scene for 10 min on two different days (same time of day, randomized order). Before and after driving, participants rated SHEs by completing the Simulator Sickness Questionnaire (SSQ). During driving, several physiological parameters were recorded. After driving in the high-SCS, the SSQ score increased in average by 129.4 (122.9 %, p = 0.002) compared to an increase of 5.0 (3.4 %, p = 0.878) after driving in the low-SCS. In the low-SCS, skin conductance decreased by 13.8 % (p < 0.01) and saccade amplitudes increased by 16.1 % (p < 0.01). Results show that the investigated methods reduce SHEs in a younger population, and the low-SCS is well accepted by the users. We expect that these measures will improve user comfort.

Time-varying signal analysis to detect high-altitude periodic breathing in climbers ascending to extreme altitude.

This work investigates the performance of cardiorespiratory analysis detecting periodic breathing (PB) in chest wall recordings in mountaineers climbing to extreme altitude. The breathing patterns of 34 mountaineers were monitored unobtrusively by inductance plethysmography, ECG and pulse oximetry using a portable recorder during climbs at altitudes between 4497 and 7546 m on Mt. Muztagh Ata. The minute ventilation (VE) and heart rate (HR) signals were studied, to identify visually scored PB, applying time-varying spectral, coherence and entropy analysis. In 411 climbing periods, 30-120 min in duration, high values of mean power (MP(VE)) and slope (MSlope(VE)) of the modulation frequency band of VE, accurately identified PB, with an area under the ROC curve of 88 and 89%, respectively. Prolonged stay at altitude was associated with an increase in PB. During PB episodes, higher peak power of ventilatory (MP(VE)) and cardiac (MP(LF)(HR) ) oscillations and cardiorespiratory coherence (MP(LF)(Coher)), but reduced ventilation entropy (SampEn(VE)), was observed. Therefore, the characterization of cardiorespiratory dynamics by the analysis of VE and HR signals accurately identifies PB and effects of altitude acclimatization, providing promising tools for investigating physiologic effects of environmental exposures and diseases.

A Flow Trace Generator using Graph-based Traffic Classification Techniques

We propose a novel methodology to generate realistic network flow traces to enable systematic evaluation of network monitoring systems in various traffic conditions. Our technique uses a graph-based approach to model the communication structure observed in real-world traces and to extract traffic templates. By combining extracted and user-defined traffic templates, realistic network flow traces that comprise normal traffic and customized conditions are generated in a scalable manner. A proof-of-concept implementation demonstrates the utility and simplicity of our method to produce a variety of evaluation scenarios. We show that the extraction of templates from real-world traffic leads to a manageable number of templates that still enable accurate re-creation of the original communication properties on the network flow level.