Fitness Running Guidance System Based On Smartphone

Because fitness running is not affected by time,place and season,it takes less time and is efficient.It has become the main exercise program for all citizens.A number of fitness running systems based on smart phone have emerged in the market.These systems use the GPS,acceleration,direction,magnetic force,gyroscopeand rotation vector sensors of the smartphone to output signals related to movement status.After processing,they can acquire the exercise data such as the Step frequency,step length,acceleration and speed of the running.Based on this,it provides functions such as the preservation,statistics,display and sharing of sports data.These systems have certain guiding functions,which are mainly reflected in the aspects of fitness running data acquisition,fitness running process modeling,and fitness running plan generation.In order to improve the effectiveness of exercise,to avoid the physical and mental harm caused by excessive exercise.How to provide a precise,safe,scientific,personalized and instructive fitness running system has always been a major difficulty in fitness training.To solve this problem,this paper collects individual fitness running data based on sensors built in smart phones,and performs differential evolution modeling of its fitness running process.Finally,a fitness running plan generation method is designed based on an evolutionary optimization algorithm for comprehensive ranking evaluation.Based on this,research is conducted.A more accurate,scientific,safe and effective fitness running Guidance System based on smart phone is proposed.The main work of this article is as follows:(1)A method of Multi-sensor of Smartphone and Median Filter for Speed Data Acquisition in Fitness Running(MM4SA)is proposed.The MM4SA method uses a median filter to filter impulse noise generated by the intermittent attitude change of the mobile phone to the triaxial acceleration signal,and combines the direction signals output by the direction sensor to filter the gravity component contained in the triaxial acceleration of the mobile phone.(2)A Differential Evolution Algorithm(DE)is designed.The DE algorithm can search for a better fitness running model in the huge model space defined by Cheng and Scalzi.(3)A Genetic Algorithm based on Comprehensive Ranking Evaluation(RGA)method based on comprehensive ranking evaluation was designed.The RGA algorithm can search out a safe and effective fitness running plan.(4)Ten college students were recruited for fitness running and their speed and heart rate data were collected during the exercise.Some experimental comparison of this method with Brzostowski's and Aung Feng's equal person method was conducted.The experimental results show that those methods can obtain more accurate speed data and fitness running model than Brzostowski and Ang Fengpin's method.And the fintness running plan obtained by our method is safer and more effective than the Ang Fengpin's method.