Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: An adaptive neuro-fuzzy inference system (ANFIS) with a supervisory control system (SCS) was used to predict the occurrence of gait events using the electromyographic (EMG) activity of lor extremity muscles in the child with cerebral palsy (CP). This is anticipated to form the basis of a control algorithm for the application of electrical stimulation (ES) to leg or ankle muscles in an attempt to improve walking ability. Either surface or percutaneous intramuscular electrodes re used to record the muscle activity from the quadriceps muscles, with concurrent recording of the gait cycle performed using a VICON motion analysis system for validation of the ANFIS with SCS. Using one EMG signal and its derivative from each leg as its inputs, the ANFIS with SCS was able to predict all gait events in seven out of the eight children, with an average absolute time differential beten the VICON recording and the ANFIS prediction of less than 30 ms. Overall accuracy in predicting gait events ranged from 98.6% to 95.3% (root mean-squared error beten 0.7 and 1.5). Application of the ANFIS with the SCS to the prediction of gait events using EMG data collected two months after the initial data demonstrated comparable results, with no significant differences beten gait event detection times. The accuracy rate and robustness of the ANFIS with SCS with two EMG signals suggests its applicability to ES control.
['Richard T. Lauer', 'Brian T. Smith', 'Randal R. Betz']
I am writing a research paper on a idea Application of a neuro-fuzzy network for gait event detection using electromyography in the child with Cerebral palsy
[{"from": "human", "value": "I am writing a research paper on a idea Application of a neuro-fuzzy network for gait event detection using electromyography in the child with Cerebral palsy"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: An adaptive neuro-fuzzy inference system (ANFIS) with a supervisory control system (SCS) was used to predict the occurrence of gait events using the electromyographic (EMG) activity of lor extremity muscles in the child with cerebral palsy (CP). This is anticipated to form the basis of a control algorithm for the application of electrical stimulation (ES) to leg or ankle muscles in an attempt to improve walking ability. Either surface or percutaneous intramuscular electrodes re used to record the muscle activity from the quadriceps muscles, with concurrent recording of the gait cycle performed using a VICON motion analysis system for validation of the ANFIS with SCS. Using one EMG signal and its derivative from each leg as its inputs, the ANFIS with SCS was able to predict all gait events in seven out of the eight children, with an average absolute time differential beten the VICON recording and the ANFIS prediction of less than 30 ms. Overall accuracy in predicting gait events ranged from 98.6% to 95.3% (root mean-squared error beten 0.7 and 1.5). Application of the ANFIS with the SCS to the prediction of gait events using EMG data collected two months after the initial data demonstrated comparable results, with no significant differences beten gait event detection times. The accuracy rate and robustness of the ANFIS with SCS with two EMG signals suggests its applicability to ES control."}]