Model of Traumatic Spinal Cord Injury for Evaluating Pharmacologic Treatments in Cynomolgus Macaques (Macaca fasicularis).

Here we present the results of experiments involving cynomolgus macaques, in which a model of traumatic spinal cord injury (TSCI) was created by using a balloon catheter inserted into the epidural space. Prior to the creation of the lesion, we inserted an EMG recording device to facilitate measurement of tail movement and muscle activity before and after TSCI. This model is unique in that the impairment is limited to the tail: the subjects do not experience limb weakness, bladder impairment, or bowel dysfunction. In addition, 4 of the 6 subjects received a combination treatment comprising thyrotropin releasing hormone, selenium, and vitamin E after induction of experimental TSCI. The subjects tolerated the implantation of the recording device and did not experience adverse effects due the medications administered. The EMG data were transformed into a metric of volitional tail moment, which appeared to be valid measure of initial impairment and subsequent natural or treatment-related recovery. The histopathologic assessment demonstrated widespread axon loss at the site of injury and areas cephalad and caudad. Histopathology revealed evidence of continuing inflammation, with macrophage activation. The EMG data did not demonstrate evidence of a statistically significant treatment effect.

Mathematical modeling of laser based potato cutting and peeling.

A mathematical model is developed and validated to predict the depth of cut in potato tuber slabs as a function of laser power and travel speed. The model considers laser processing parameters such as input power, spot size and exposure time as well as the properties of the material being cut such as specific heat, thermal conductivity, surface reflectance, etc. The model also considers the phase change of water in potato and the ignition temperature of the solid portion. The composition of the potato tuber is assumed to be of water and solid. The model also assumes that the ablation process is accomplished through ejection of liquid water, debris and water vapour, and combustion of solid. A CO(2) laser operating in c.w. mode was chosen for the experimental work because water absorbs laser energy highly at 10.6 microm, and CO(2) laser units with relatively high output power are available. Slabs of potato tuber were chosen to be laser processed since potato contains high moisture and large amounts of relatively homogeneous tissue. The results of the preliminary calculations and experiments concluded that the model is able to predict the depth of cut in potato tuber parenchyma when subjected to a CO(2) laser beam.

A neural network model for reconstructing EMG signals from eight shoulder muscles: consequences for rehabilitation robotics and biofeedback.

This paper demonstrates the ability of a fully connected feed forward neural network (FFNN) using the backpropagation training algorithm to predict the electromyography (EMG) signal from eight muscles of the shoulder for both exercises not used for training and EMG signals from subjects not used for training. The network showed a good predictive ability for subjects not used for training (r(2) between 0.33 and 0.84) and for activities not used for training (r(2) between 0.56 and 0.89). This may have applications for patients, physical therapists and doctors to monitor patient performance by reviewing the level of agreement between the patient EMG and the predicted EMG. Coupled with traditional methods of evaluation, EMG can provide an excellent measure of how well a patient has responded or is responding to treatment. Incorporating robotic technology could facilitate the use of EMG as an input to an intelligent decision making algorithm used to increase or decrease the level of difficulty according to patient performance.