Conference Paper

Ambulatory Measurement and Analysis of the Lower Limb 3D Posture Using Wearable Sensor System

DOI: 10.1109/ICMA.2009.5245982 Conference: Mechatronics and Automation, 2009. ICMA 2009. International Conference on
Source: IEEE Xplore


An original approach for ambulatory measurement and analysis of lower limb 3D gait posture was presented, and a wearable sensor system was developed according to the approach. To explicate the lower limb posture, thigh orientation angles were calculated based on a virtual sensor at the hip joint and double analog inertial sensors (MAG3) on the thigh; Knee joint angle in sagittal plane was calculated with combination of angular accelerations and angular velocities measured by two MAG3 on the thigh and shank on the basis of the virtual-sensor based algorithm. The developed wearable sensor system was evaluated on the lower limb. Without integration of angular acceleration or angular velocity for the thigh orientation angles and the knee joint angle, the calculated result was not distorted by offset and drift. Using virtual sensors at the hip joint and the knee joint were more simple, practical and effective than fixing physical sensors at these joints. Compared with the result from the reference system, the measured result with the developed wearable sensor system was feasible to do gait analysis for the patients in the daily life, and the method can also be used in other conditions such as measuring rigid segment posture with less sensors and high degree of accuracy.

1 Follower
17 Reads
  • Source
    • "Apparently, these techniques can lead to very poor results unless a tight mechanical setup is used to restrict the motion. A tempting alternative is to mount the sensors with a predefined orientation towards the segment or joint, as in [4] and [5]. But besides the fact that this is hard to realize for some applications, e.g. "
    [Show abstract] [Hide abstract]
    ABSTRACT: We consider 6d inertial measurement units (IMU) attached to rigid bodies, e.g. human limb segments or links of a robotic manipulator, which are connected by hinge joints and spheroidal joints. Novel methods for joint axis estimation and joint position estimation are presented that exploit the kinematic constraints induced by these two types of joints. The presented methods do not require any knowledge about the sensor units' positions or orientations and do not include integration, i.e. they are insensitive to measurement bias. By means of a three-links simulation model, the estimation algorithms are validated and convergence is analyzed. Finally, the algorithms are tested using experimental data from IMU-based human gait analysis.
    Control Applications (CCA), 2012 IEEE International Conference on; 01/2012
  • [Show abstract] [Hide abstract]
    ABSTRACT: Tracking the orientation or attitude of an object has many applications in various research fields. This paper presents a tracking system which estimates the orientation of an object using an angular rate sensor, accelerometer, and magnetometer. For the combined usage of the sensors, the Kalman filter and the Factored Quaternion Algorithm (FQA) are applied to the proposed system. We also propose a method to eliminate the drift effect of the angular rate sensor in static state. The experimental results show that the proposed tracking system can estimate an accurate rotation of an object and can eliminate the drift effect in static state. I. INTRODUCTION Real-time tracking an object is one of the important issues in the field of robotics. Generally, tracking is defined as the observation of a moving object and the supply of the timely ordered sequence of the respective location data of a model. The tracking system is categorized into two types: the optical tracking system and the inertial and magnetic tracking system. Optical tracking system determines the position and the orientation of an object by using multiple cameras and markers. This system measures position and orientation of an object from the relative movement of markers. Some markerless tracking approaches using the optical sensors are also proposed in recent years. However, the optical sensors are fixed outside of an object to observe the object. Therefore, the optical tracking system has the range limitation and cannot observe the object hidden by obstacles. Another category of the object tracking system is the inertial and magnetic tracking system using the Inertial Measurement Unit (IMU) and the magnetometer. IMU is an electronic device that measures the angular rate, orientation, and the acceleration of gravity using the combination of an angular rate sensor and accelerometer. A magnetometer is an instrument to measure the magnetic field in nature. IMU and the magnetometer are small in size and lightweight, and it is possible to build with low cost. When tracking an object, IMU and the magnetometer have no range limitations and are free from obstacles. These sensors can measure the orientation, angular rate, and acceleration of an object in real-time. The tracking system proposed in this paper also uses in an angular rate sensor, accelerometer, and a magnetometer. For the combined use of an angular rate sensor, accelerometer, and magnetometer, the Kalman filter and the Factored Quaternion Algorithm (FQA)(3) are applied to the proposed system. Kalman filter is used to estimate accurate
    01/2011; DOI:10.1109/ICMA.2011.5985957
  • [Show abstract] [Hide abstract]
    ABSTRACT: The current trends in wearable sensor technology suggest that, in the next decade or so, garments will commonly include some form of biometric/biopotential measurement system and will be of great value for gathering ambulatory metadata for remote diagnosis. In parallel, the introduction of new powerful mixed-signal devices will enhance the possibility of garments including cost-effective biopotential measurements, over the classical analog signal conditioning configurations. This paper presents the use of a recently introduced ASIC device (ADS1298) for measuring ECG, EEG and EMG data, towards developing a multimodal biopotential measurement system. Two programmable analog filter configurations are tested for comparison. The results show that adjusting the analog filters to accommodate different biopotentials is an unfeasible task in comparison with the ASIC device, which proved useful for measuring common biopotentials: ECG, EMG and EEG, and thus is more suitable for wearable sensor applications.
    Electronics, Robotics and Automotive Mechanics Conference (CERMA), 2012 IEEE Ninth; 01/2012
Show more

Similar Publications