外文翻譯---基于旋轉(zhuǎn)加速度微傳感器的運動監(jiān)測系統(tǒng) 英文

1、A Sport Activities Monitoring System based on Acceleration and Rotation Microelectromechanical SensorsYull Heilordt Henao Roa and Fabiano Fruett Department of Semiconductors, Instruments and Photonics, State University o

2、f Campinas Av. Albert Einstein, 400, CEP 13083-970, Campinas, SP, Brazil Phone: +55-19-35213880, heilordt@dsif.fee.unicamp.br and fabiano@dsif.fee.unicamp.brAbstract— Although there are several technological tools to aid

3、 sports training, most of them are high cost solutions and generally very specific to a particular sport, which hinders the diffusion of such technologies. This paper presents a low- cost non-invasive microcontroller Spo

4、rt Activities Monitoring System (SAMS) prototype, which is based on acceleration and rotation microelectromechanical sensors (MEMs) for obtaining biomechanical data during the athlete’s training, without leav- ing the na

5、tural environment of his activities. The sensors signals are wirelessly transmitted from the SAMS to the computer in order to process the data, through an easy and intuitive Virtual Instrument (VI) interface developed in

6、 LabVIEW?. This VI saves and displays real-time data in a graphic form. The ex- perimental results were obtained in two different environments: first we used a stationary bike and then we tested the SAMS in a professiona

7、l cycle track. The system allows the acceleration acquisition in the range form ±1,5 G until ±10 G and rotation in the span of ±50 ?/s. The maximum transmission range is about 70 m. The SAMS has a small si

8、ze (37x49x20 mm) and lightweight (40 g), making it a versatile monitoring system to aid athletes and coaches during the training, allowing refinements on the technique. The SAMS is also a suitable tool for the physical e

9、ducation research area. Keywords: accelerometer, gyroscope, sport monitoring, vir- tual instrumentation, wireless communication, real time feed- back.I. INTRODUCTIONCurrently advances on microelectronics and MEMs sen- so

10、rs, are each time smaller, with low power consumption and affordable prices making it more feasible and permitting its application on sports. Accelerometers, gyroscopes, micro- phones and cameras among others, lend thems

11、elves suitable to a wide range of sports applications [1], making possible to obtain biomechanical, physical or cognitive information from monitoring the athletes performance during their trainings or sport practices. Ne

12、w wireless communication standards like Bluetooth? and ZigbeeT M, provide a platform for network- ing sensors, that can be widely applied in the healthcare and in sports [2] since it allows data transmission without mobi

13、lity interfering. The athlete’s performance depends on the environment where he or she is being monitored [2], for example: laboratory, inside/outside training, competition or playing field conditions. In addition to tha

14、t, it is known that when feedback is provided in an appropriate manner, motor skill acquisition improves significantly. Consequently, feedback is a major factor in the improvements of sport skill performance [3]. Further

15、more, systems with immediatefeedback increase the athlete’s motivation.II. HARDWARE SYSTEM PROTOTYPEFigure 1 shows the block diagram of the Sport Activities Monitoring System (SAMS) prototype, which is divided in two boa

16、rds: the first one, has the acceleration and rotation sensors, a microcontroller, a radiofrequency module and a battery. This is the mobile part of the prototype and can be attached to the athlete’s body. The second boar

17、d, also called base station board, was adapted from a USB-RogerCom?board [4], and incorporates a radiofrequency module. This station board is directly connected to the computer’s USB port, in order to acquire the sensors

18、’ data.Fig. 1. Block diagram of the system prototype.The prototype sensors were chosen by taking into ac- count their operation range, size, energy consumption, number of axes, type of output, encapsulation and price, ke

19、eping this in mind, the accelerometers MMA7260 and MMA7261 from FreescaleT M and the gyroscopes IDG- 300 and IDG-1004 from InvenSenseT M were chosen. With regards to the microcontroller, we selected a low power, eight bi

20、t MC9S08QE128 from FreescaleT M. The radiofrequency module Xbee/XbeePro from DigiT M, and a rechargeable 3,7 V lithium prismatic battery were also selected. Accelerometers: The MMA7260 (introduced in 2005 by FreescaleT M

21、 [5]) and the MMA7261 [6] are MEM’s tri-axis acceleration sensors with selectable sensitivity (1,5/2/4/6 G), low current consumption (500 µA), sleep mode (3 µA), low voltage operation (2,2 to 3,6 V) and low cos

22、t (3,35 USD). The output voltage is ratiometric and proportional to the acceleration, this simply means that the output offset voltage and sensitivity will scale linearly with applied supply voltage.this firmware control

23、s all the process in the mobile board, including: data acquisition, optional processing, power con- sumption, and data transmission. The second part of the software, is a Virtual Instrument (VI) interface developed on La

24、bVIEW?, which is a graphical programming language that has been widely adopted throughout industry, academia, and research labs as the standard for data acquisition and instrument control software [10]. This VI allows th

25、e selec- tion of the sensors which are going to be use, select the acceleration range, enable preprocessing, along calibration, data processing, saving and displaying real time data in a graphic form over an intuitive us

26、er interface. The SAMS’ frontal panel is presented in Figure 6.Fig. 6. SAMS virtual instrument frontal panel.SAMS calibration: In order to eliminate the offset from the sensors, a calibration process was developed. This

27、pro- cess measured the gravity acceleration by each one of the accelerometer axes in three different positions by aligning the normal vector of the sensor, with the gravity vector in every position and keeping the other

28、axis without acceleration. For the calibration task, the program guides the user to align the sensor’s box in each one of the positions as shown in Figure 7. Finally, after the calculations, the offset value for every ax

29、is is saved in a file and read by the SAMS’ VI during the startup.(a) Position 1 (b) Position 2 (c) Position 3Fig. 7. SAMS mobile board calibration positions.SAMS fixation and orientations: The SAMS was encap- sulated an

30、d adapted with a fixation system to let it be easy fasten to the athlete. The axis and rotation coordinates are presented in Figure 8.IV. EXPERIMENTAL RESULTSThe experimental results were obtained in two different enviro

31、nments: first we use a stationary bike and then we tested the SAMS on a professional cycle track. In these bike test, the sensor was fixed in the right ankle of the athlete as shown in Figure 9.(a) (b)Fig. 8. SAMS mobile

32、 board axis and rotation coordinates.(a) (b)Fig. 9. Fixation in the right ankle during the testes.Stationary bike test: One of the tests with the stationary bike, was the Wingate test [11]. This is a test used to evaluat

33、e the maximum power and anaerobic capacity. The Wingate is a 30 seconds test, during it, the athlete tries to pedal as many times against a fixed resistance, aiming to generate as much power as possible in that period of

34、 time. The power generated during the 30 seconds is called the average power and a power peak usually occurs within the first 5 seconds of the test. Figure 10, 11, 12 and 13, shows the acceleration and angular velocity f

35、or each axis and the temperature, respectively.00:00 00:05 00:10 00:15 00:20 00:25 00:30-60-40-20020406080100120A c e l. [m /s ?]T empo [mm:ss]Ax(a) Ax00:00 00:05 00:10 00:15 00:20 00:25 00:30-0,4-0,3-0,2-0,10,00,10,20,3

36、0,4R o ll [? /s ]T empo [mm:ss]Roll(b) Roll (Vx)Fig. 10. Acceleration Ax and angular velocity Roll (Vx).00:00 00:05 00:10 00:15 00:20 00:25 00:30-60-40-20020406080100120A c e l. [m /s ?]T empo [mm:ss]Ay(a) Ay00:00 00:05