The Research For The Evaluation Method Of Skeletal Muscle Movement Based On The Multi-modal Information

With the development of science and technology, human communication havetransformed from a theoretical concept to actual product, giving full play to theadvantage of wireless, networking as well as information technology and realizing thewhole process of tracking and health services, human communication network is oneof the most direct and reliable monitoring methods for the dynamic information ofhuman life, the use of digital medical technology can improve people’s quality of life.With the rapid development of information technology, mechanical, electrical andmedical imaging and other sophisticated quantitative classification which mayprovide rehabilitation assessment tools are being paid more and more attention. Dueto the importance and complexity of skeletal muscle to accomplish a specific functionin the process, the use of electrical, mechanical, acoustic and other means ofquantitative research on skeletal motion model to carry out in-depth research will helpto systematically understand the dysfunction of muscle movement.As the complexity and diversity of human muscle movement, the study ofmuscle function and features during exercise is a complex and difficult task,especially how to conduct a variety and multi-level study on the single internal bodymuscle in order to obtain integrated information is still remaining to be solved. Inaddition, as the muscle composition is very complex, it’s a difficult and hot researchfor prompting a quantitative analysis to evaluate the functional role of skeletal muscle.Therefore, the multi-modal approach combined different signal characteristics duringmuscle activity, it has an extremely important role and significance to apply thisresearch on the evaluation of skeletal muscle by quantitative analysis in medicinestudies, especially in the field of rehabilitation medicine, with this method we canhelp doctors develop a simple and accurate rehabilitation programs depending on thedifferent patient, thereby improving recovery rates of patients to achieve the ultimategoal of a low-cost health.In this paper, we have realized the multi-modal signal evaluation method bycombining the existed extract biometric signal processing methods as well asclassification methods at home and abroad, firstly integrated the two muscle movement signals namely Electromyography and Ultrasonography, then applied inassessing motor dysfunction in patients while do some simple exercises, gained theaccurate curve of the normal limb and abnormal limb for further identification,eventually helped doctors come up with effective state muscle rehabilitation programs,realizing a simple and efficient diagnosis and treatment. In order to achieve theserequirements, we have designed a practical experimental program, collected data incooperation hospitals, for each different type of signal we used differentpreprocessing method; Then we designed and done the signal analysis, especially inthe ultrasonic signal processing, we proposed a real-time as well as automaticalgorithm to track the morphological parameters of skeletal muscle such as musclethickness; At last obtained muscle movement characteristic curve of ultrasoundimages; according to the signal extracted features and motion, we integrated the twosignals and selected the appropriate classification to realize the identification;Combined with the actual state of the patient’s muscle motion state and clinical trials,to verify the feasibility of the method. At last, the experimental results show that theproposed method can effectively evaluate the patient’s functional status of musclemovement, and it plays an auxiliary role in clinical care, the study of human musclemovement also has important significance.