This paper presents a new highly accurate gait phase detection system using wearable wireless ultrasonic sensors, which can be used in gait analysis or rehabilitation applications. The gait phase detection system uses the foot displacement information during walking to extract the following gait phases: heel-strike, heel-off, toe-off, and mid-swing. The displacement of foot-mounted ultrasonic sensor is obtained from several passive anchors placed at known locations by employing local spherical positioning technique, which is further enhanced by the combination of recursive Newton-Gauss method and Kalman Filter. The algorithm performance is examined by comparing with a commercial optical motion tracking system with ten healthy subjects and two foot injured subjects. Accurate estimates of gait cycle (with an error of -0.02 ±0.01 s), stance phase(with an error of 0.04±0.03 s), and swing phase (with an error of -0.05±0.03 s) compared to the reference system are obtained. We have also investigated the influence of walking velocities on the performance of the proposed gait phase detection algorithm. Statistical analysis shows that there is no significant difference between both systems during different walking speeds. Moreover, we have tested and discussed the possibility of the proposed system for clinical applications by analyzing the experimental results for both healthy and injured subjects. The experiments show that the estimated gait phases have the potential to become indicators for sports and rehabilitation engineering.

Techniques that could be used to monitor human motion precisely are helpful in various applications such as rehabilitation, gait analysis, and athletic performance analysis. This paper focuses on the 3-D foot trajectory measurements based on a wearable wireless ultrasonic sensor network. The system consists of an ultrasonic transmitter (mobile) and several receivers (anchors) with fixed known positions. In order not to restrict the movement of subjects, a radio frequency (RF) module is used for wireless data transmission. The RF module also provides the synchronization clock between mobile and anchors. The proposed system measures the time-of-arrival (TOA) of the ultrasonic signal from mobile to anchors. Together with the knowledge of the anchor's position, the absolute distance that the signal travels can be computed. Then, the range information defines a circle centered at this anchor with radius equal to the measured distance, and the mobile resides within the intersections of several such circles. Based on the TOA-based tracking technique, the 3-D foot trajectories are validated against a camera-based motion capture system for ten healthy subjects walking on a treadmill at slow, normal, and fast speeds. The experimental results have shown that the ultrasonic system has sufficient accuracy of net root-mean-square error ( 4.2 cm) for 3-D displacement, especially for foot clearance with accuracy and standard deviation ( 0.62 ±7.48 mm) compared to the camera-based motion capture system. The small form factor and lightweight feature of the proposed system make it easy to use. Such a system is also much lower in cost compared to the camera-based tracking system.

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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In this paper, a low-cost motion analysis system using a wireless ultrasonic sensor network is proposed and investigated. A methodology has been developed to extract spatial-temporal gait parameters including stride length, stride duration, stride velocity, stride cadence, and stride symmetry from 3D foot displacements estimated by the combination of spherical positioning technique and unscented Kalman filter. The performance of this system is validated against a camera-based system in the laboratory with 10 healthy volunteers. Numerical results show the feasibility of the proposed system with average error of 2.7% for all the estimated gait parameters. The influence of walking speed on the measurement accuracy of proposed system is also evaluated. Statistical analysis demonstrates its capability of being used as a gait assessment tool for some medical applications.