Validation and application of a computational model for wrist and hand movements using surface markers

A kinematic model is presented based on surface marker placement generating wrist, metacarpal arch, fingers and thumb movements. Standard calculations are used throughout the model and then applied to the specified marker placement. A static trial involving eight unimpaired participants was carried out to assess inter-rater reliability. The standard deviations across the data were comparable to manual goniometers. In addition, a test retest trial of ten unimpaired participants is also reported to illustrate the variability of movement at the wrist joint, metacarpal arch, and index finger as an example of model output when repeating the same task many times. Light and heavyweight versions of the tasks are assessed and characteristics of individual movement strategies presented. The participant trial showed moderate correlation in radial/ulnar deviation of the wrist ( = 0 65), and strong correlation in both metacarpal arch joints ( = 075 and = 085), the MCP ( = 079), and PIP ( = 087) joints of the index finger. The results indicate that individuals use repeated strategies of movement when lifting light and heavyweight versions of the same object, but showed no obvious repeated pattern of movement across the population

Chromosomal location of human genes encoding major heat-shock protein HSP70

The HSP70 family of heat-shock proteins constitutes the major proteins synthesized in response to elevated temperatures and other forms of stress. In eukaryotes members of the HSP70 family also include a protein similar if not identical to bovine brain uncoating ATPase and glucose-regulated proteins. An intriguing relation has been established between expression of heat-shock proteins and transformation in mammalian cells. Elevated levels of HSP70 are found in some transformed cell lines, and viral and cellular gene products that are capable of transforming cells in vitro can also stimulate transcription of HSP70 genes. To determine the organization of this complex multigene family in the human genome, we used complementary approaches: Southern analysis and protein gels of Chinese hamster-human somatic cell hybrids, and in situ hybridization to human chromosomes. We demonstrate that functional genes encoding HSP70 proteins map to human chromosomes 6, 14, 21, and at least one other chromosome .Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/45535/1/11188_2005_Article_BF01534692.pd

ExploreASL: an image processing pipeline for multi-center ASL perfusion MRI studies

Arterial spin labeling (ASL) has undergone significant development since its inception, with a focus on improving standardization and reproducibility of its acquisition and quantification. In a community-wide effort towards robust and reproducible clinical ASL image processing, we developed the software package ExploreASL, allowing standardized analyses across centers and scanners.The procedures used in ExploreASL capitalize on published image processing advancements and address the challenges of multi-center datasets with scanner-specific processing and artifact reduction to limit patient exclusion. ExploreASL is self-contained, written in MATLAB and based on Statistical Parameter Mapping (SPM) and runs on multiple operating systems. The toolbox adheres to previously defined international standards for data structure, provenance, and best analysis practice.ExploreASL was iteratively refined and tested in the analysis of >10,000 ASL scans using different pulse-sequences in a variety of clinical populations, resulting in four processing modules: Import, Structural, ASL, and Population that perform tasks, respectively, for data curation, structural and ASL image processing and quality control, and finally preparing the results for statistical analyses on both single-subject and group level. We illustrate ExploreASL processing results from three cohorts: perinatally HIV-infected children, healthy adults, and elderly at risk for neurodegenerative disease. We show the reproducibility for each cohort when processed at different centers with different operating systems and MATLAB versions, and its effects on the quantification of gray matter cerebral blood flow.ExploreASL facilitates the standardization of image processing and quality control, allowing the pooling of cohorts to increase statistical power and discover between-group perfusion differences. Ultimately, this workflow may advance ASL for wider adoption in clinical studies, trials, and practice

Power management of an artificial hand

Power management of an artificial han

Can Iterative Learning Control be used in the Re-education of Upper Limb Function, Mediated by Functional Electrical Stimulation (FES)?

Introduction There is a body of clinical evidence to support the use of FES to improve motor control (De Kroon et al. 2002) and theoretical support from neurophysiology (Burridge & Ladouceur 2001) and motor learning research (Schmidt & Lee 1999). Iterative learning control has its origins in the control of processes that repetitively perform a task with a view to improving accuracy. The classic example is the area of trajectory following in robotics but can it be usefully applied to neurological rehabilitation? Method To answer this question, the ability of 10 patients to track a 2 D pattern using a robot arm, over a number of trials is being tested. We are designing an algorithm to control FES of appropriate muscles in terms of timing and amplitude to improve tracking. Subsequently the stimulation will be reduced to encourage optimal voluntary contribution to the task. To achieve this, a model is being created using unimpaired subjects to identify activation patterns with respect to joint positions. This will inform when we need to apply stimulation (although we expect patients to differ due to spasticity). In the initial phase surface EMGs have been collected from triceps, biceps, anterior deltoid, upper, middle and lower trapezius and pectoralis major during 9 reaching tasks. The EMG data will identify which muscles to control, be used in the controller, and to compare differences between stroke and unimpaired subjects. The next phase involves collecting data using the robot both with and without stimulation and then applying different control algorithms. Results Surface EMG results and analysis from 10 unimpaired subjects will be presented. Preliminary analysis on EMGs from 8 subjects shows evidence that reciprocal inhibition of upper trapezius occurs during maximum reach. If successful the concept could be used for other neurological conditions such as cerebral palsy and incomplete spinal injury. References Burridge, J. H. & Ladouceur, M. 2001, "Clinical and therapeutic applications of neuromuscular stimulation: A review of current use and speculation into future developments", Neuromodulation, vol. 4, no. 4, pp. 147-154. De Kroon, J. R., van der Lee, J. H., Izerman, M. J., & Lankhorst, G. J. 2002, "Therapeutic electrical stimulation to improve motor control and functional abilities of the upper extremity after stroke: a systematic review", Clinical Rehabilitation, vol. 16, pp. 350-360. Schmidt, R. A. & Lee, T. D. 1999, Motor control and learning a behavioural emphasis. 3rd Edition Human Kinetics Part 3 Motor Learning