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.

Energy harvesting from the cardiovascular system, or how to get a little help from yourself

Human energy harvesting is envisioned as a remedy to the weight, the size, and the poor energy density of primary batteries in medical implants. The first implant to have necessarily raised the idea of a biological power supply was the pacemaker in the early 1960s. So far, review articles on human energy harvesting have been rather unspecific and no tribute has been given to the early role of the pacemaker and the cardiovascular system in triggering research in the field. The purpose of the present article is to provide an up-to-date review of research efforts targeting the cardiovascular system as an alternative energy source for active medical implants. To this end, a chronological survey of the last 14 most influential publications is proposed. They include experimental and/or theoretical studies based on electromagnetic, piezoelectric, or electrostatic transducers harnessing various forms of energy, such as heart motion, pressure gradients, and blood flow. Technical feasibility does not imply clinical applicability: although most of the reported devices were shown to harvest an interesting amount of energy from a physiological environment, none of them were tested in vivo for a longer period of time.Human energy harvesting is envisioned as a remedy to the weight, the size, and the poor energy density of primary batteries in medical implants. The first implant to have necessarily raised the idea of a biological power supply was the pacemaker in the early 1960s. So far, review articles on human energy harvesting have been rather unspecific and no tribute has been given to the early role of the pacemaker and the cardiovascular system in triggering research in the field. The purpose of the present article is to provide an up-to-date review of research efforts targeting the cardiovascular system as an alternative energy source for active medical implants. To this end, a chronological survey of the last 14 most influential publications is proposed. They include experimental and/or theoretical studies based on electromagnetic, piezoelectric, or electrostatic transducers harnessing various forms of energy, such as heart motion, pressure gradients, and blood flow. Technical feasibility does not imply clinical applicability: although most of the reported devices were shown to harvest an interesting amount of energy from a physiological environment, none of them were tested in vivo for a longer period of time.

Coronary artery stents: influence of adaptive statistical iterative reconstruction on image quality using 64-HDCT

OBJECTIVE: The assessment of coronary stents with present-generation 64-detector row computed tomography (HDCT) scanners is limited by image noise and blooming artefacts. We evaluated the performance of adaptive statistical iterative reconstruction (ASIR) for noise reduction in coronary stent imaging with HDCT. METHODS AND RESULTS: In 50 stents of 28 patients (mean age 64 ± 10 years) undergoing coronary CT angiography (CCTA) on an HDCT scanner the mean in-stent luminal diameter, stent length, image quality, in-stent contrast attenuation, and image noise were assessed. Studies were reconstructed using filtered back projection (FBP) and ASIR-FBP composites. ASIR resulted in reduced image noise vs. FBP (P < 0.0001). Two readers graded the CCTA stent image quality on a 4-point Likert scale and determined the proportion of interpretable stent segments. The best image quality for all clinical images was obtained with 40 and 60% ASIR with significantly larger luminal area visualization compared with FBP (+42.1 ± 5.4% with 100% ASIR vs. FBP alone; P < 0.0001) while the stent length was decreased (-4.7 ± 0.9%,

Architectural Developments in Sungai Tenang, 1902-2013

This paper treats the architectural developments in Sungai Tenang since the occupation by the Netherland's Indies in 1902 until the present. During this time great changes have occurred, among them the virtual disappearance of the traditional houses with carved planks. At the same time, much of the architectural developments can be described as the evolution of a still basically Austronesian house structure. Both these changes and the continuities merit close scrutiny, since they together reflect the persistence of the house as a powerful symbolic form that is capable of expressing changing social structures and cultural values. Up to the present, architecture in Sungai Tenang, in spite of its often modern outward appearance, is still by and large vernacular in the sense that its constructive means, its symbolic forms and its uses are firmly rooted in local traditions.

Mechanical and Chemical Stability of Injection-Molded Microcantilevers Used for Sensing

Ultraviolet-ozone treatment is used as a standard surface cleaning procedure for removal of molecular organic contamination from analytical and sensing devices. Here, it is applied for injection-molded polymer microcantilevers before characterization and sensing experiments. This article examines the effects of the surface cleaning process using commercial equipment, in particular on the performance and mechanical properties of the cantilevers. It can be shown that the first chemical aging process essentially consist of the cross linking of the polymer chains together with a physical aging of the material. For longer exposure, the expected thermo-oxidative formation of carbonyl groups sets in and an exposure dependent chemical degradation can be detected. A process time of 20 min was found suitable as a trade-off between cleaning and stability

Attitudes of Swiss veterinarians towards pain and analgesia in dogs and cats.

A survey was performed to evaluate the use of perioperative analgesia in dogs and cats by veterinary practitioners. Questions were grouped in seven sections recording personal data, education in veterinary analgesia, general ideology regarding treatment of perioperative pain, personal experience, assessment, and use of main analgesics to treat perioperative pain. A total of 258 received forms were analyzed. Based on 5 questions, 88 % showed excellent motivation to use perioperative pain therapy. The main reason declared for the use of analgesics was to relieve the patient from pain (64.1 %). Most veterinarians reported to routinely administer analgesics before (71 - 96 %) or after (2 - 23 %) surgery. The most used analgesics were non-steroidal anti-inflammatory drugs (carprofen, meloxicam) and opioids (butorphanol, buprenorphine). Animals were routinely evaluated for pain after recovery. Only 43.8 % of veterinarians declared to use loco-regional anaesthesia. Swiss veterinarians appear to recognize well the need for perioperative pain treatment. However, weakness was shown in evaluating pain severity, distinguishing between opioid classes, and using loco-regional anaesthesia.

Image registration for triggered and non-triggered DTI of the human kidney: Reduced variability of diffusion parameter estimation

BACKGROUND: To investigate if non-rigid image-registration reduces motion artifacts in triggered and non-triggered diffusion tensor imaging (DTI) of native kidneys. A secondary aim was to determine, if improvements through registration allow for omitting respiratory-triggering. METHODS: Twenty volunteers underwent coronal DTI of the kidneys with nine b-values (10-700 s/mm2 ) at 3 Tesla. Image-registration was performed using a multimodal nonrigid registration algorithm. Data processing yielded the apparent diffusion coefficient (ADC), the contribution of perfusion (FP ), and the fractional anisotropy (FA). For comparison of the data stability, the root mean square error (RMSE) of the fitting and the standard deviations within the regions of interest (SDROI ) were evaluated. RESULTS: RMSEs decreased significantly after registration for triggered and also for non-triggered scans (P < 0.05). SDROI for ADC, FA, and FP were significantly lower after registration in both medulla and cortex of triggered scans (P < 0.01). Similarly the SDROI of FA and FP decreased significantly in non-triggered scans after registration (P < 0.05). RMSEs were significantly lower in triggered than in non-triggered scans, both with and without registration (P < 0.05). CONCLUSION: Respiratory motion correction by registration of individual echo-planar images leads to clearly reduced signal variations in renal DTI for both triggered and particularly non-triggered scans. Secondarily, the results suggest that respiratory-triggering still seems advantageous.J. Magn. Reson. Imaging 2014. (c) 2014 Wiley Periodicals, Inc.

Patient-Specific Semi-Supervised Learning for Postoperative Brain Tumor Segmentation

In contrast to preoperative brain tumor segmentation, the problem of postoperative brain tumor segmentation has been rarely approached so far. We present a fully-automatic segmentation method using multimodal magnetic resonance image data and patient-specific semi-supervised learning. The idea behind our semi-supervised approach is to effectively fuse information from both pre- and postoperative image data of the same patient to improve segmentation of the postoperative image. We pose image segmentation as a classification problem and solve it by adopting a semi-supervised decision forest. The method is evaluated on a cohort of 10 high-grade glioma patients, with segmentation performance and computation time comparable or superior to a state-of-the-art brain tumor segmentation method. Moreover, our results confirm that the inclusion of preoperative MR images lead to a better performance regarding postoperative brain tumor segmentation.

Interactive Segmentation of MR Images from Brain Tumor Patients

Medical doctors often do not trust the result of fully automatic segmentations because they have no possibility to make corrections if necessary. On the other hand, manual corrections can introduce a user bias. In this work, we propose to integrate the possibility for quick manual corrections into a fully automatic segmentation method for brain tumor images. This allows for necessary corrections while maintaining a high objectiveness. The underlying idea is similar to the well-known Grab-Cut algorithm, but here we combine decision forest classification with conditional random field regularization for interactive segmentation of 3D medical images. The approach has been evaluated by two different users on the BraTS2012 dataset. Accuracy and robustness improved compared to a fully automatic method and our interactive approach was ranked among the top performing methods. Time for computation including manual interaction was less than 10 minutes per patient, which makes it attractive for clinical use.