Comparison of electromyographic activity of quadriceps muscle in persons with unilateral traumatic transtibial amputation using patellar tendon bearing supracondylar endoskeletal prosthesis with the unaffected limb in weight bearing positions.

Abstract Purpose: comparison of electromyographic activity of quadriceps muscle in persons with unilateral traumatic transtibial amputation using patellar tendon bearing supracondylar endoskeletal prosthesis with the unaffected limb in weight bearing positions. Method: 30 individuals  aged 18-60 years were assessed using surface electromyography with functional level K3 according to K-level functional assessment scale to compare the activity of quadriceps of affected side using patellar tendon bearing supracondylar endoskeletal prosthesis with the unaffected side. The data was analysed using paired t-test. Result:  There was a significant difference in the activity of VMO and VLO muscles of the quadriceps in high sitting positions. There was also a significant difference in the activity of VMO muscle in single limb stance and bipedal stance. However, there was no significant difference between the activity of VLO muscle in bipedal stance but there was reduced activity of VLO muscle in the prosthetic limb in single limb stance. Conclusion: The quadriceps activity was reduced in the affected limb in high sitting position, single  limb stance and bipedal stance. However, no difference in the muscle activity was noted in VLO muscle in bipedal stance. Keywords: trans tibial amputation, patellar tendon bearing supracondylar prosthetis, surface electromyography.&nbsp

Comparison of electromyographic activity of quadriceps muscle in persons with unilateral traumatic transtibial amputation using patellar tendon bearing supracondylar endoskeletal prosthesis with the unaffected limb in weight bearing positions.

Abstract Purpose: comparison of electromyographic activity of quadriceps muscle in persons with unilateral traumatic transtibial amputation using patellar tendon bearing supracondylar endoskeletal prosthesis with the unaffected limb in weight bearing positions. Method: 30 individuals  aged 18-60 years were assessed using surface electromyography with functional level K3 according to K-level functional assessment scale to compare the activity of quadriceps of affected side using patellar tendon bearing supracondylar endoskeletal prosthesis with the unaffected side. The data was analysed using paired t-test. Result:  There was a significant difference in the activity of VMO and VLO muscles of the quadriceps in high sitting positions. There was also a significant difference in the activity of VMO muscle in single limb stance and bipedal stance. However, there was no significant difference between the activity of VLO muscle in bipedal stance but there was reduced activity of VLO muscle in the prosthetic limb in single limb stance. Conclusion: The quadriceps activity was reduced in the affected limb in high sitting position, single  limb stance and bipedal stance. However, no difference in the muscle activity was noted in VLO muscle in bipedal stance. Keywords: trans tibial amputation, patellar tendon bearing supracondylar prosthetis, surface electromyography.&nbsp

SIGN LANGUAGE RECOGNITION USING IMAGE PROCESSING

we have proposed a method for real time Hand Gesture Recognition and feature extraction using a web camera. In this approach, the image is captured through webcam attached to the system. First the input image is preprocessed and threshold is used to remove noise from image and smoothen the image. After this apply region filling to fill holes in the gesture or the object of interest. This helps in improving the classification and recognition step. Then select the biggest blob (biggest binary linked object) in the image and remove all small object, this is done to remove extra unwanted objects or noise from image. When the preprocessing is complete the image is passed on to feature extraction phase.The test image is classified in nearest neighbor’s class in training set. The classification results are displayed to user and through the windows text to speech API gesture is translated into speech as well. The training data set of images that is used has 5 gestures, each with 50 variations of a single gesture with different lighting conditions. The purpose of this is to improve the accuracy of classification