Shaojie Su

A Visual-Aided Wireless Monitoring System Design for Total Hip Replacement Surgery

To improve the positioning accuracy of implants in Total Hip Replacement (THR) surgeries, a visual-aided wireless monitoring system for THR surgery is proposed in this paper. This system aims to measure and display the contact distribution and relative pose between femoral head and acetabulum prosthesis during the surgery to help surgeons obtain accurate position of implants. The system consists of two parts: the Sensors Array Measuring System (SAMS) and the display part. The SAMS is composed of a sensors array (including contact sensors and an image sensor), signal conditioning circuits, a low power microcontroller (MCU), and a low-power transceiver. The SAMS is designed to estimate the relative pose of femoral head component to acetabular component. The display part processes the data from sensors and demonstrates the contact distribution and the pose of the prothesis during the surgery in 3-D graphics. The two parts of the system communicate with each other on an RF link at the band of 400 MHz. The signal conditioning circuits have been designed and fabricated in 0.18 μm CMOS process. Testing results show that the resolution of the signal conditioning circuits is 60.1 μ Vpp (1.35g) with ±100 mVpp input. The chip can operate under 1.2-to-3.6 V supply voltage for single battery applications with 116-160 μ A current consumption. The system has been verified by the simulation with rotation quaternion and translation vector. The experimental results show that the contact distribution and relative pose of the two components could be measured and demonstrated in real time. The relative error of rotation is less than 8% and the actual relative error of translation is less than 10%.

Monocular Vision- and IMU-Based System for Prosthesis Pose Estimation During Total Hip Replacement Surgery

The average age of population increases worldwide, so does the number of total hip replacement surgeries. Total hip replacement, however, often involves a risk of dislocation and prosthetic impingement. To minimize the risk after surgery, we propose an instrumented hip prosthesis that estimates the relative pose between prostheses intraoperatively and ensures the placement of prostheses within a safe zone. We create a model of the hip prosthesis as a ball and socket joint, which has four degrees of freedom (DOFs), including 3-DOF rotation and 1-DOF translation. We mount a camera and an inertial measurement unit (IMU) inside the hollow ball, or “femoral head prosthesis,” while printing customized patterns on the internal surface of the socket, or “acetabular cup.” Since the sensors were rigidly fixed to the femoral head prosthesis, measuring its motions poses a sensor ego-motion estimation problem. By matching feature points in images of the reference patterns, we propose a monocular vision based method with a relative error of less than 7% in the 3-DOF rotation and 8% in the 1-DOF translation. Further, to reduce system power consumption, we apply the IMU with its data fused by an extended Kalman filter to replace the camera in the 3-DOF rotation estimation, which yields a less than 4.8% relative error and a 21.6% decrease in power consumption. Experimental results show that the best approach to prosthesis pose estimation is a combination of monocular vision-based translation estimation and IMU-based rotation estimation, and we have verified the feasibility and validity of this system in prosthesis pose estimation.

Design of a computer-aided visual system for Total Hip Replacement surgery

To improve the accuracy of implant placement in Total Hip Replacement (THR) surgeries, this paper proposes a computer-aided visual system for THR which is composed of a customized acetabular cup, a multi-sensor femoral head trial and a computer for data processing and display. The customized trial is of the same size as the real prosthesis. An image sensor, a gyroscope and an e-compass (including an accelerometer and a magnetometer) are adopted in the femoral head trial. Reference patterns are designed and printed on the internal surface of the cup, whose images are taken by the image sensor for estimation of relative pose and position between the femoral head trial and the acetabulum cup. Two methods of pose estimation are adopted in this system: one based on images and the other based on motion data from gyroscope and e-compass. The efficient perspective-n-point (EPNP) algorithm is used in the image-based pose estimation and achieves a rotation relative error of less than 8% and a translation relative error of less than 10%. The complementary algorithm is adopted in the motion-based pose estimation to smooth the results. Experimental results verified the proposed system.

Estimation of the relative pose of the femoral and acetabular components in a visual aided system for total hip replacement surgeries

In total hip replacement (THR) surgeries, the placement of the femoral and acetabular components within the safe zone is not guaranteed when using the freehand technique of operation. To improve the accuracy of the positioning, a visual aided system for THR which estimates and displays the relative pose of femoral and acetabular components is proposed. The system is composed of a dedicated femoral head trial with a miniature camera set inside the femoral head and a acetabular prosthesis trial with designated patterns placed on the internal surface of the liner. By analyzing the liner images taken by the camera, a set of correspondences between the 3D points and their 2D projections can be established. Then the relative pose is estimated using the correspondences as input. Finally, the result is displayed in 3D graphics in vivo. The system has been evaluated under the simulation with rotation quaternion and translation vector and the experimental results have validated the effectiveness of the proposed method.

Pose measurement of Anterior Pelvic Plane based on inertial measurement unit in total hip replacement surgeries

In Total Hip Replacement (THR), inaccurate measurement of Anterior Pelvic Plane (APP), which is usually used as a reference plane, will lead to malposition of the acetabular prosthesis. As a result, the risk of impingement, dislocation and wear will increase and the safe range of motion will be limited. In order to acquire the accurate pose of APP, a measurement system is designed in this paper, which includes two parts: one is used to estimate the initial pose of APP and the other is used to trail dynamic motion of APP. Both parts are composed of an Inertial Measurement Unit (IMU) and magnetometer sensors. An Extended Kalman Filter (EKF) is adopted to fuse the data from IMU and the magnetometer sensors to estimate the orientation of the pelvis. The test results show that the error angle between calculated axis and true axis of the pelvis in geodetic coordinate frame is less than 1.2 degree, which meets the requirement of the surgery.In Total Hip Replacement (THR), inaccurate measurement of Anterior Pelvic Plane (APP), which is usually used as a reference plane, will lead to malposition of the acetabular prosthesis. As a result, the risk of impingement, dislocation and wear will increase and the safe range of motion will be limited. In order to acquire the accurate pose of APP, a measurement system is designed in this paper, which includes two parts: one is used to estimate the initial pose of APP and the other is used to trail dynamic motion of APP. Both parts are composed of an Inertial Measurement Unit (IMU) and magnetometer sensors. An Extended Kalman Filter (EKF) is adopted to fuse the data from IMU and the magnetometer sensors to estimate the orientation of the pelvis. The test results show that the error angle between calculated axis and true axis of the pelvis in geodetic coordinate frame is less than 1.2 degree, which meets the requirement of the surgery.

A wirelessly monitoring system design for Total Hip Replacement surgery

This paper presents a wirelessly monitoring system for Total Hip Replacement (THR) surgery. This system aims to measure and display the attitude and position of femoral head of prosthetic implant during the surgery. The system consists of two parts: the Sensors Array Measuring System (SAMS) and the display part. The SAMS is composed of a sensors array, signal conditioning circuits, a low power Micro Control Unit (MCU), and a low-power transceiver. The SAMS is designed to measure the contact distribution of the sensors array (which is on the surface of the femoral head) between the surface of the femoral head and the acetabulum of the prosthesis. The data is transmitted wirelessly by a low power transceiver. The display part demonstrates the contact distribution and the attitude of the prothesis in-vivo in 3-D images. The two parts of the system communicate with each other on a RF link at the band of 400MHz. The signal conditioning circuits have been designed and fabricated in 0.18μm CMOS process. The tested results show that the resolution of the signal conditioning circuits is 60.1μVpp (1.35g) with ±100mVpp input and the chip can operate under 1.2V to 3.6V voltage supply for single battery application with 116-160μA power current consumption. The system has been validated by experimental results.

Color based segmentation in monocular system for prosthesis pose estimation during total hip replacement surgery

Safe-zone in total hip replacements (THR) means that the acetabular cup is placed within 30 to 50° of abduction and 5 to 25° of anteversion. To help surgeons with prosthesis placement into the safe zone and real-time prosthesis pose estimation, a femoral head prosthesis with a camera mounted inside is designed. To ensure the validity of this monocular vision based system in blood covered situation, an RGB color based segmentation method is proposed in this paper. Customized patterns are printed on the inner surface of acetabular cup. When put into the acetabular cup, the femoral head prosthesis will keep collecting images of the customized patterns. Relative pose between the prostheses is then calculated by matching feature points between frames. Since blood is red in color, we extract red channel of the image sequence for processing to ensure high contrast between the patterns and background. Top-hat preprocessing is also applied to eliminate influence of uneven illumination. Experiment results show the mean error of the monocular vision based pose estimation is 1.426°, which is within tolerance compared to the range of safe zone. The RGB color based segmentation achieves a pattern recognition rate as high as 94.1% in blood covered situation, which is 4 times of that of ordinary method.

IMU-based Real-time Pose Measurement system for Anterior Pelvic Plane in Total Hip Replacement Surgeries

With the aging of population, the number of Total Hip Replacement Surgeries (THR) increased year by year. In THR, inaccurate position of the implanted prosthesis may lead to the failure of the operation. In order to reduce the failure rate and acquire the real-time pose of Anterior Pelvic Plane (APP), we propose a measurement system in this paper. The measurement system includes two parts: Initial Pose Measurement Instrument (IPMI) and Real-time Pose Measurement Instrument (RPMI). IPMI is used to acquire the initial pose of the APP, and RPMI is used to estimate the real-time pose of the APP. Both are composed of an Inertial Measurement Unit (IMU) and magnetometer sensors. To estimate the attitude of the measurement system, the Extended Kalman Filter (EKF) is adopted in this paper. The real-time pose of the APP could be acquired together with the algorithm designed in the paper. The experiment results show that the Root Mean Square Error (RMSE) is within 1.6 degrees, which meets the requirement of THR operations.With the aging of population, the number of Total Hip Replacement Surgeries (THR) increased year by year. In THR, inaccurate position of the implanted prosthesis may lead to the failure of the operation. In order to reduce the failure rate and acquire the real-time pose of Anterior Pelvic Plane (APP), we propose a measurement system in this paper. The measurement system includes two parts: Initial Pose Measurement Instrument (IPMI) and Real-time Pose Measurement Instrument (RPMI). IPMI is used to acquire the initial pose of the APP, and RPMI is used to estimate the real-time pose of the APP. Both are composed of an Inertial Measurement Unit (IMU) and magnetometer sensors. To estimate the attitude of the measurement system, the Extended Kalman Filter (EKF) is adopted in this paper. The real-time pose of the APP could be acquired together with the algorithm designed in the paper. The experiment results show that the Root Mean Square Error (RMSE) is within 1.6 degrees, which meets the requirement of THR operations.

Orientation and depth estimation for femoral components using image sensor, magnetometer and inertial sensors in THR surgeries

Malposition of the acetabular and femoral component has long been recognized as an important cause of dislocation after total hip replacement (THR) surgeries. In order to help surgeons improve the positioning accuracy of the components, a visual-aided system for THR surgeries that could estimate orientation and depth of femoral component is proposed. The sensors are fixed inside the femoral prosthesis trial and checkerboard patterns are printed on the internal surface of the acetabular prosthesis trial. An extended Kalman filter is designed to fuse the data from inertial sensors and the magnetometer orientation estimation. A novel image processing algorithm for depth estimation is developed. The algorithms have been evaluated under the simulation with rotation quaternion and translation vector and the experimental results shows that the root mean square error (RMSE) of the orientation estimation is less then 0.05 degree and the RMSE for depth estimation is 1mm. Finally, the femoral head is displayed in 3D graphics in real time to help surgeons with the component positioning.Malposition of the acetabular and femoral component has long been recognized as an important cause of dislocation after total hip replacement (THR) surgeries. In order to help surgeons improve the positioning accuracy of the components, a visual-aided system for THR surgeries that could estimate orientation and depth of femoral component is proposed. The sensors are fixed inside the femoral prosthesis trial and checkerboard patterns are printed on the internal surface of the acetabular prosthesis trial. An extended Kalman filter is designed to fuse the data from inertial sensors and the magnetometer orientation estimation. A novel image processing algorithm for depth estimation is developed. The algorithms have been evaluated under the simulation with rotation quaternion and translation vector and the experimental results shows that the root mean square error (RMSE) of the orientation estimation is less then 0.05 degree and the RMSE for depth estimation is 1mm. Finally, the femoral head is displayed in 3D graphics in real time to help surgeons with the component positioning.

Smart trail with camera and inertial measurement unit for intraoperative estimation of hip range of motion in total hip replacement surgery

To minimize the risk of prosthetic impingement after total hip replacement (THR), a novel smart trial is proposed for intraoperative estimation of hip range of motion (ROM) in THR surgery. The smart trial is used to examine the stability, range of motions and risk of dislocation during the surgery, relocate hip implants, and finally will be replaced by real implant prosthesis. The smart trial is composed of a customized femoral head trial with a camera and an inertial measurement unit (IMU) inside, and a customized acetabular cup trial with reference patterns printed on the internal surface. A depth estimation algorithm based on images taken by the camera is designed for the detection of critical regions where impingement or dislocation is about to happen, and an extended Kalman filter is designed for the fusion of the data from IMU to acquire better orientation estimation accuracy. This paper is proof of concept with limited validation through an experimental setup. Simulation results show that the root mean square error (RMSE) of the depth estimation is 1mm and that of the orientation estimation is less than 0.05 degree. The hip ROM is displayed in 3-D mode in real time.