Prediction of Lower Extremity Movement by Cyclograms

Human gait is nowadays undergoing extensive analysis. Predictions of leg movements can be used for orthosis and prosthesis programming, and also for rehabilitation. Our work focuses on predicting human gait with the use of angle-angle diagrams, also called cyclograms. In conjunction with artificial intelligence, cyclograms offer a wide area of medical applications. We have identified cyclogram characteristics such as the slope and the area of the cyclogram for a neural network learning algorithm. Neural networks learned by cyclograms offer wide applications in prosthesis control systems

BIOFEEDBACK AS A NEUROBIOMECHANICAL ASPECT OF POSTURAL FUNCTION

The aim of the work is to elucidate if there is a significant difference between the ability to maintain balance with or without the biofeedback while standing and identify specific segments that takes place of motion solutions of postural problems. We measured postural parameters using 6 tri-axial accelerometers placed in 6 places: 2× lower leg, 2× thigh, processus spinosus vertebrae L5 and C7. Probands absolved 3 postural tasks and 3 dynamic tasks. Postural: quiet standing with feet apart with eyes open, quiet standing with feet together with eye closed, quiet standing with feet apart with eyes open and with visual biofeedback. We used system Homebalance - interactive system for providing of balance training with visual biofeedback. Results show no significant difference between C7 and L5 for task without VBF (visual biofeedback) and with VBF, but SD VPG (sum of scatter of the acceleration) for thigh and ankle show significant difference between each task on every level. We detected that in open eyes majority of probands used ankle-strategy for maintaining balance. In eyes closed they preferred knee and hip strategy. The biggest accelerations were detected in C7 in eyes closed. Due to visual biofeedback patients are more motivated and they improve their skills faster than without visual biofeedback exercise. Strategy of maintaining balance during tasks with open eyes and eyes closed is different

Prediction of Lower Extremity Movement by Cyclograms

Human gait is nowadays undergoing extensive analysis. Predictions of leg movements can be used for orthosis and prosthesis programming, and also for rehabilitation. Our work focuses on predicting human gait with the use of angle-angle diagrams, also called cyclograms. In conjunction with artificial intelligence, cyclograms offer a wide area of medical applications. We have identified cyclogram characteristics such as the slope and the area of the cyclogram for a neural network learning algorithm. Neural networks learned by cyclograms offer wide applications in prosthesis control systems

Differences in evaluation methods of trunk sway using different MoCap systems

The position of the trunk can be negatively influenced by many diseases. Several methods can be used for identifying defects in balance and coordination as a result of pathology of the musculoskeletal or nervous system. The aim of this article is to examine the relationship between the three methods used for analysis of trunk sway and compare two fundamentally different MoCap systems. We used a camera system and a 3DOF orientation tracker placed on subject’s trunk, and measured inclination (roll) and flexion (pitch) during quiet stance. Ten healthy participants in the study were measured with eyes open and closed. The pitch versus roll plots of trunk were formed, and the area of the convex hull, area of confidence ellipse and total length of the trajectory of the pitch versus roll plot were calculated. The statistical analysis was performed and strong correlation between the area of the convex hull and area of the confidence ellipse was found. Also, the results show moderate correlation between the area of the confidence ellipse and total length of the trace, and moderate correlation between the area of the convex hull and total length of the trace. In general, the different MoCap systems show different areas and lengths but lead to the same conclusions. Statistical analysis of the participants with eyes open and eye closed did not show significant difference in the areas and total lengths of the pitch versus roll plots

Hepatocellular carcinoma in Central Europe: prognostic features and survival

BACKGROUND AND AIMS—We investigated the influence of baseline characteristics of patients with hepatocellular carcinoma (HCC) on prognosis and developed a multivariate Cox model predicting survival. All patients were from Central Europe.
METHODS—All 245 patients seen at the Department of Gastroenterology and Hepatology at the University of Vienna, Austria, from July 1991 to March 1998 were included in this retrospective study. Nineteen different clinical characteristics and survival time from date of diagnosis were noted. Factors determining survival time were analysed by univariate and multivariate analysis using Cox proportional hazard regression models and a new classification model was constructed. The validity of this model was tested on an independent group of 89 patients, seen from April 1998 to September 1999.
RESULTS—Median survival in patients with HCC was 8.0 months. In a multivariate analysis bilirubin (>2 mg/dl), portal vein thrombosis, prothrombin time (<70%), alpha fetoprotein (>180 µg/l), tumour mass >50%, and enlarged lymph nodes were independent predictors of survival. A newly constructed Cox proportional hazard model (Vienna survival model for HCC=VISUM-HCC) identified three disease stages with different durations of survival (median survival stage 1, 15.2 months; stage 2, 7.2 months; and stage 3, 2.6 months; p=0.00001). Applying the VISUM-HCC survival model to patients in Okuda stage 2 identified subgroups with an excellent and very poor prognosis for which different treatment modalities should be offered.
CONCLUSIONS—Our patients with HCC had a poor median survival of eight months. Six easily measurable clinical variables were significant predictors of survival in patients with HCC. The new VISUM-HCC survival model may be useful for stratifying patients with HCC for various clinical treatment modalities.


Keywords: hepatocellular carcinoma; clinical presentation; prognostic mode