A wearable wireless sensor network for human limbs monitoring

Low, Kay Soon; Lee, Guo Xiong; Taher, Tawfiq

doi:10.1109/imtc.2009.5168662

Cited by 17 publications

(11 citation statements)

References 16 publications

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“…In our research, an ambulatory and unrestrained measurement system based on a wearable wireless sensor network for tracking the human arm motion has been proposed and developed. The wearable wireless sensor network system based on accelerometers was developed in 2008 and reported in 2009 [93]. At that time, most of the inertial based sensors in the market such as the Xsens MTx were wired and cumbersome.…”

Section: Development Of a Wearable Wireless Sensor Network For Arm Momentioning

confidence: 99%

Unrestrained Measurement of Arm Motion Based on a Wearable Wireless Sensor Network

Lee

Low

Taher

2010

IEEE Trans. Instrum. Meas.

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Measurement of human body motion has a myriad of applications ranging from gaming, rehabilitation, animation, virtual reality, sports science and surveillance. Existing methods of motion tracking include visual, mechanical, magnetic and inertial tracking. Visual methods require line of sight and suffer from the notorious occlusion problem. For the existing mechanical or inertial tracking methods, they have cumbersome wirings which hinder the natural movements. In this thesis, a wearable wireless sensor network using inertial/ magnetic sensors is developed to overcome the limitations of these existing methods. Using tri-axial accelerometer as the sole sensor will lead to singularity when the heading axis is vertical, restricting measurement of orientation to half a vertical plane. A new factorized quaternion approach is proposed in this research to overcome this deficiency with consideration of anatomical and sensor constraints. Different from the conventional approach based on single angle-axis quaternion, the proposed approach factorizes the quaternion into two principal axis quaternions corresponding to two equivalent arm motions. This allows for the implementation of anatomical arm constraints that match the range of arm motion and reduces the ambiguity in solutions. In addition, the singularities arising from the use of tri-axial accelerometers can be detected and resolved for a transient state. A novel algorithm based on elevation and heading angles is also proposed to determine the orientation of a sensor node equipped with tri-axial accelerometer, gyroscope and magnetometer. Compared to Euler angles, the fixed elevation and heading angles are independent on the temporal order of rotations. In addition, the fixed elevation and heading angles are observable and thus more intuitively visualized.

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Section: Development Of a Wearable Wireless Sensor Network For Arm Momentioning

confidence: 99%

Unrestrained Measurement of Arm Motion Based on a Wearable Wireless Sensor Network

Lee

Low

Taher

2010

IEEE Trans. Instrum. Meas.

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“…However, inaccuracies could arise due to unwanted rotation of the device during free fall. From the sinusoidal relationship of λ˜Y and λ˜Z with respect to the tilt angle θ as in (21) and (22), it is observed that an estimate of λYo and λZo can be determined by taking the mean value of λ˜Y and λ˜Z over a 360…”

Section: Calibrationmentioning

confidence: 99%

“…• . From the figure, it is observed that the ADC value for the Y -and Z-axes follows sine and cosine waves as in (21) and (22), respectively. The corresponding estimated 0g offsets λˆYo and λˆZo are determined to be 127.8889 and 125.9306, respectively.…”

Section: Calibrationmentioning

confidence: 99%

“…It is based on the medium-access control and physical layers of the IEEE 802.15.4 specification for low-rate wireless personal area networks. A detail discussion on the choice of wireless standard, protocol, and the implementation of the wireless platform is given in [22]. During operation, the accelerometer on each sensor node will measure the three-axis (XY Z) acceleration.…”

Section: Introductionmentioning

confidence: 99%

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Unrestrained Measurement of Arm Motion Based on a Wearable Wireless Sensor Network

Sreenivasulu¹,

Subbarao²

2012

IJIPVS

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Techniques that could precisely monitor human motion are useful in applications such as rehabilitation, virtual reality, sports science, and surveillance. Most of the existing systems require wiring that restrains the natural movement. To overcome this limitation, a wearable wireless sensor network using accelerometers has been developed in this paper to determine the arm motion in the sagittal plane. The system provides unrestrained movements and improves its usability. The lightweight and compact size of the developed sensor node makes its attachment to the limb easy. Experimental results have shown that the system has good accuracy and response rate when compared with a goniometer.

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“…The proposed system only requires the measurement of the absolute distance between two points on body. Hence, the proposed system is simpler compared to other approaches used in [11] and [69]. Apart from mean error and standard deviation analysis, we also evaluate the PCC values between the goniometer results and angles estimated by the proposed system, shown in Fig.…”

Section: Comparison Of Proposed Approach With Goniometer Measurementsmentioning

confidence: 99%

Wearable human motion tracking and analysis system based on wireless sensor network

Qi¹

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Measurement of human body movement has become a widely used clinical tool for evaluating and quantifying musculoskeletal functions based on the information from kinematic and kinetic data. It has a myriad of applications ranging from rehabilitation to gait analysis. Existing methods of motion tracking include visual, mechanical, magnetic and inertial tracking. Visual systems are more sensitive to changes in light, clutter and shadow. For mechanical and inertial tracking systems, they may be cumbersome which hinder the natural movements. In this thesis, we first developed a wearable motion tracking system using ultra wideband (UWB) radios, and then a low-cost motion analysis system using wireless ultrasonic sensor network was proposed to overcome the limitations of these existing methods. The first part of the thesis describes a new method for measuring and monitoring human body joint angles, which uses wearable UWB transceivers mounted on body segments. This work is motivated by the high accuracy of UWB technology in ranging and positioning, which makes it a promising candidate for human motion monitoring. The model is based on providing a high ranging accuracy (inter-sensor distance) between a pair of transceivers placed on the adjacent segments of the joint centre of rotation. The measured distance is then used to compute the joint angles based on the law of cosines. The proposed joint angle measurement system used only one pair of transceivers to measure the flexion/extension angles in the sagittal plane. The performance of the method was compared with a flexible goniometer by simultaneously measuring joint flexion-extension angles at different angular velocities, ranging between 8 • /s and 90 • /s.

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A wearable wireless sensor network for human limbs monitoring

Cited by 17 publications

References 16 publications

Unrestrained Measurement of Arm Motion Based on a Wearable Wireless Sensor Network

Unrestrained Measurement of Arm Motion Based on a Wearable Wireless Sensor Network

Unrestrained Measurement of Arm Motion Based on a Wearable Wireless Sensor Network

Wearable human motion tracking and analysis system based on wireless sensor network

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