基于加速度计和弯曲传感器的手指运动姿态监测（英文）
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摘要
针对动态测量关节角度的需要,本文设计了两种手指运动姿态监测方法.第1种方法是通过基于MEMS技术的三轴加速度计ADXL330对近侧指间关节的运动姿态进行监测.ADXL330是通过每一敏感轴所感知的重力加速度分量来实现这一功能.为验证该方法的可行性,设计了步进电机控制的能在竖直平面内转动的装置.对比传感器的输出和电机转动的角度,结果表明:动态条件下,其绝对误差为1°~3°,相对误差为2%~6%.第2种方法是通过弯曲传感器在弯曲时输出电阻的变化来监测手指的运动姿态.实验结果表明:在一定的允许误差范围内,三轴加速度计ADXL330和弯曲传感器都能用于监测手指运动姿态.
In order to dynamically measure the joint angle,two detection methods for finger motion were designed. The first method uses three-axis accelerometer ADXL330 based on MEMS technology to monitor the proximal interphalangeal joint( PIP joint) motion. The accelerometer ADXL330 realizes this function through the gravitational acceleration component of every sensitive axis. To verify the feasibility of the proposed scheme,a rotating device was designed which could be controlled by the stepper motor and could rotate in the vertical plane. Considering the output voltage of the accelerometer and the rotating angle of the stepper motor,the results show that the absolute error and relative error mainly ranges between 1 ° —3 ° and 2% —6%,respectively,under dynamic conditions. The second method uses a flex sensor to monitor finger motion attitude. The sensor works under the principle that it produces output resistance change when bent. The experimental results show that both the three-axis accelerometer ADXL330 and the flex sensor can be applied to monitor the motion attitude of human fingers within a range of errors.
In order to dynamically measure the joint angle,two detection methods for finger motion were designed. The first method uses three-axis accelerometer ADXL330 based on MEMS technology to monitor the proximal interphalangeal joint( PIP joint) motion. The accelerometer ADXL330 realizes this function through the gravitational acceleration component of every sensitive axis. To verify the feasibility of the proposed scheme,a rotating device was designed which could be controlled by the stepper motor and could rotate in the vertical plane. Considering the output voltage of the accelerometer and the rotating angle of the stepper motor,the results show that the absolute error and relative error mainly ranges between 1 ° —3 ° and 2% —6%,respectively,under dynamic conditions. The second method uses a flex sensor to monitor finger motion attitude. The sensor works under the principle that it produces output resistance change when bent. The experimental results show that both the three-axis accelerometer ADXL330 and the flex sensor can be applied to monitor the motion attitude of human fingers within a range of errors.
引文
[1]Hao Liguo,Zhu Yanfeng,Zhao Lingyun.Body motion recognition based on acceleration sensor[C]//Electronic Measurement and Instruments International Conference.Chengdu,China,2011,1:142-145.
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[9]Flores M B H,Siloy C M B,Oppus C,et al.User-oriented finger-gesture glove controller with hand movement virtualization using flex sensors and a digital accelerometer[C]//Nanotechnology,Information Technology International Conference.Palawan,Philippines,2014:1-4.
[10]Meng Weiguo.The characteristics and applications of threeaxis accelerometer ADXL330[J].Foreign Electronic Components,2007,2:47-50(in Chinese).
[11]Hou Wensheng,Dai Jiaman,Zheng Xiaolin,et al.The detection of forearm’s motion attitude based on the accelerometer[J].Sensors and Microsystem,2009,28(1):106-108(in Chinese).
[12]Fu Yujin,Yuan Kui,Zhu Haibing,et al.Motion modeling and software system design for CAS-Glove data glove[J].Journal of System Simulation,2004,16(4):660-662(in Chinese).
[13]Orengo G,Lagati S,Saggio G.Modeling wearable bend sensor behavior for human motion capture[J].IEEE Sensors Journal,2014,14(7):2307-2316.
[2]Zhu Rong,Zhou Zhaoying,Yu Ting,et al.Micro measurement system for tracking human body motion[J].Journal of Tsinghua University:Science and Technology,2003,43(11):1464-1467,1471(in Chinese).
[3]Oscar D L,Alfredo J P,Miguel A L.Centinela:A human activity recognition system based on acceleration and vital sign data[J].Pervasive and Mobile Computing,2012,8(5):717-729.
[4]Lorussi F,Scilingo E P,Tesconi M,et al.Strain sensing fabric for hand posture and gesture monitoring[J].IEEE Trans Inf Technol Biomed,2005,9(3):372-381.
[5]Dipietro L,Sabatini A M,Dario P.A survey of glove-based systems and their applications[J].IEEE Transactions on Systems,Man and Cybernetics,Part C(Applications and Reviews),2008,38(4):461-482.
[6]Qin Yong,Zang Xizhe,Wang Xiaoyu,et al.Research of attitude estimation system using MEMS inertial sensors[J].Chinese Journal of Sensors and Actuators,2007,20(2):288-301(in Chinese).
[7]Wang Xiaoli,Liu Yongmei.Classification analysis and development trends of the wearable devices[J].Melliand China,2015(5):58-60(in Chinese).
[8]Li Yang.A new generation of smart terminal:The wearable devices[J].High-Technology&Industrialization,2013,209:82-85(in Chinese).
[9]Flores M B H,Siloy C M B,Oppus C,et al.User-oriented finger-gesture glove controller with hand movement virtualization using flex sensors and a digital accelerometer[C]//Nanotechnology,Information Technology International Conference.Palawan,Philippines,2014:1-4.
[10]Meng Weiguo.The characteristics and applications of threeaxis accelerometer ADXL330[J].Foreign Electronic Components,2007,2:47-50(in Chinese).
[11]Hou Wensheng,Dai Jiaman,Zheng Xiaolin,et al.The detection of forearm’s motion attitude based on the accelerometer[J].Sensors and Microsystem,2009,28(1):106-108(in Chinese).
[12]Fu Yujin,Yuan Kui,Zhu Haibing,et al.Motion modeling and software system design for CAS-Glove data glove[J].Journal of System Simulation,2004,16(4):660-662(in Chinese).
[13]Orengo G,Lagati S,Saggio G.Modeling wearable bend sensor behavior for human motion capture[J].IEEE Sensors Journal,2014,14(7):2307-2316.
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