Research On Evaluation And Analysis Method Of Muscle Strength Based On Deep Learning

With the development of artificial intelligence,wireless sensors have become the main equipment of human-computer interaction platform,which makes people’s quality of life improved.Wireless sensors can detect human posture information,which not only plays an important role in industry,but also plays an important role in the field of rehabilitation medicine.Wireless sensor has the advantages of strong perception ability,as an important part of human-computer interaction platform,wireless sensor has become a hot research direction in electrical engineering field.Five action types are defined,one of them is a correct action,and the other four are false actions.Identifying whether the action is correct is the core task of the system.The system helps the trainer to train intelligently through body movement recognition.This The API of wireless sensor is analyzed,and the method of data acquisition and storage of human motion signal is studied.According to the movement characteristics of the trainer,the data set of the trainer is input into the CNN network,the CNN network classifies the data set and then completes the action recognition.There were five volunteers,five hundred sets of data were collected,four hundred datasets were used for training and validation,and another 100 datasets were used for testing.Experimental results show that the average recognition rate of the test data set is more than 95%.When the trainer exercises correctly,the system conducts muscle work analysis on the trainer,and the training effect of trainers was evaluated systematically.If the trainer does not train correctly,the system instructs the trainer to correct his training until the trainer has trained the movement correctly.