Haiyang Jin

State Recognition of Pedicle Drilling With Force Sensing in a Robotic Spinal Surgical System

Spinal orthopedic surgery is one of the typical high-risk surgeries. During the surgery, bone screws need to be inserted into the narrower vertebral pedicles and any failures in the screw-path-drilling process will directly hurt the important nerves and vessels of the patient. In this paper, a robotic spinal surgical system (RSSS) for assisting pedicle screw insertion surgery is proposed. The novel structural configuration of the RSSS can balance the gravity effects of the arms, and the workspace envelope of the RSSS can better fit the requirements of spinal surgery. The procedure of the screw insertion operation with the proposed RSSS is presented. To simulate the hand feel of the surgeon in surgical operations, a real-time force-sensing algorithm is developed for the screw-path-drilling process using a spherical or a twist drill. With the force sensing, five key states, including the initial state, the outer cortical state, the cancellous state, the transitional state, and the inner cortical state, are recognized. In particular, the clear recognition of the transitional zone between the cancellous bone and the inner cortical bone is very important as the drilled screw path ends in this zone. State recognition with force sensing can effectively improve the quality of the screw paths so as to enhance the quality of the spinal surgery. Experiments were carried out to verify the state recognition effects of the pedicle drilling process with force sensing.

Design and kinematic analysis of A Pedicle Screws Surgical Robot

A Pedicle Screws Surgical Robot (PSSR) can reduce the risk of spinal surgery and improve surgical precision, which plays an important role in promoting the medical care level of spinal surgery. A new type of PSSR is proposed in this paper, and the mechanical structure and its working principle are also introduced. The kinematics model of the robot is derived from D-H notation in order to obtain the forward kinematics, inverse kinematics and workspace of the robot. A control and planning algorithm for the PSSR is carried out. This study can provide the basis for the development of PSSR prototype.

A Robot-Assisted Surgical System Using a Force-Image Control Method for Pedicle Screw Insertion

Objective To introduce a robot-assisted surgical system for spinal posterior fixation that can automatically recognize the drilling state and stop potential cortical penetration with force and image information and to further evaluate the accuracy and safety of the robot for sheep vertebra pedicle screw placement. Methods The Robotic Spinal Surgery System (RSSS) was composed of an optical tracking system, a navigation and planning system, and a surgical robot equipped with a 6-DOF force/torque sensor. The robot used the image message and force signals to sense the different operation states and to prevent potential cortical penetration in the pedicle screw insertion operation. To evaluate the accuracy and safety of the RSSS, 32 screw insertions were conducted. Furthermore, six trajectories were deliberately planned incorrectly to explore whether the robot could recognize the different drilling states and immediately prevent cortical penetration. Results All 32 pedicle screws were placed in the pedicle without any broken pedicle walls. Compared with the preoperative planning, the average deviations of the entry points in the axial and sagittal views were 0.50±0.33 and 0.65±0.40 mm, and the average deviations of the angles in the axial and sagittal views were 1.9±0.82° and 1.48±1.2°. The robot successfully recognized the different drilling states and prevented potential cortical penetration. In the deliberately incorrectly planned trajectory experiments, the robot successfully prevented the cortical penetration. Conclusion These results verified the RSSS’s accuracy and safety, which supported its potential use for the spinal surgery.

Design and control strategy of robotic spinal surgical system

Spinal surgery has its specifications. Different from minimal invasive like laparoscope surgery, there is no complex operations such as sewing, cutting or clamping. It is more important for spinal surgery to locate precisely and to keep reliable during operation. Robotic spinal surgical system (RSSS) is designed upon these principles. Tracking and navigation system in RSSS ensures high positioning accuracy, and structure of robot guarantees the safety and reliability of RSSS. Moreover, with new implements in surgery, procedure of surgery must be redesigned. In this paper, we discuss a new robotic surgical system for spinal surgery, including a complete system with tracing system, navigation system, robot. Relative kinematics, control strategy are discussed and a new procedure of surgery is designed with RSSS.

State recognition of bone drilling with audio signal in Robotic Orthopedics Surgery System

Bone drilling is an important and difficult process in orthopedic surgeries. To detect the drilling state of a Robotic Orthopedic Surgery System (ROSS) in real-time, a state recognition method based on audio signals, the Acoustic Emission (AE) signals generated in drilling process, is proposed in this paper. By an analysis via power spectral density of the AE signals, an appropriate frequency band is selected for state recognition. The Exponential Mean Amplitude (EMA) and the Hurst Exponent (HE) are used to illustrate the energy characteristics and stability of the AE signals in the chosen frequency band, respectively. The recognition algorithm combines the two different features is performed on a embedded device in the experiments. Finally, the experiments are carried out to demonstrate the effectiveness of the proposed drilling state recognition method.

Model-based state recognition of bone drilling with robotic orthopedic surgery system

Screw path drilling is an important process among many orthopedic surgeries. To guarantee the safety and correctness of this process, a model-based drilling state recognition method is proposed in this paper. The thrust force in the drilling process is modeled based on an accurate 3D bone model restructured by means of Micro-CT images. In theoretical modeling of the thrust force, the resistance and the elasticity of the bone tissues are considered. The cutting energy and elastic modulus are defined as the material parameters in the theoretical model, which are identified via a least square method. Some key parameters are proposed to support the state recognition: the peak forces in the first and the second cortical layers, the average force in the cancellous layer and the thickness of each layer. Based on these key parameters in the model, a state recognition strategy with a robotic orthopedic surgery system is proposed to recognize the switch position of each layer. Experiments are performed to demonstrate the effectiveness of the modeling approach and the state recognition method.

Intraoperative control for robotic spinal surgical system with audio and torque sensing

In pedicle screw insertion surgeries, the most dangerous part is the screw path drilling process. In current surgeries, surgeons guarantee not to drill through the vertebra by their haptic and auditory sense and experience. In this paper, an intraoperative real-time control method for a Robotic Spinal Surgical System (RSSS) with state sensing is proposed. A drilling state recognition with Audio-Torque fusion is developed. The short-time average drilling torque and its amplitude are used to construct a reference torque, and classify the drilling states. Aim to audio signals, Support Vector Machine (SVM) is used to classify the patterns, and Mel-frequency cepstral coefficients (MFCC) is extracted to train the mode and predict testing samples. By setting a different priority level for each sensor, the fusion information is for precise intraoperative control in the screw path drilling.

Intraoperative state recognition of a bone-drilling system with image-force fusion

In pedicle screw insertion surgeries, the drilling process of the screw path is very critical to decide the success of the surgery, as the hole is drilled on a very narrow area on the vertebral pedicle. In current manual surgeries, surgeons perform operation with monitoring the medical images in navigation system and sensing operation force. To simulate these abilities, in this paper, a bone-drilling state recognition algorithm and the related system based on image-force fusion are proposed. The short-time average magnitude of thrust force, the average energy of thrust force and their gradients are used to recognize drilling state and judge whether the drilling position is appropriate. For medical image information, the preoperatively scanned medical images are combined with the real-time position information of the operation tool. And the boundary of test bone, which is used to limit the drilling motion, is found depending on the drilling direction. Fusing recognition results based on thrust force and medical images, the final recognized results are modified to be more accurate and safer to control the drilling process.

Kinematics and cooperative control of a robotic spinal surgery system

Spinal surgery is considered a high-risk surgery. To improve the accuracy, stability, and safety of such operations, we report the development of a novel six-degrees-of-freedom Robotic Spinal Surgical System that can assist surgeons in performing transpedicular surgery, one of the most common spinal surgeries. After optimization performed using Response Surface Methodology, the largest available workspace of the robot is determined and is found to easily cover the entire operation area. Cooperative control and navigation-based active control are implemented for different processes of the operation. We propose a hybrid control approach based on the speed and torque interface at the joint level. In this mode, the robot is compliant in Cartesian space, benefitting both the accuracy and efficiency of the operation. A comprehensive assessment index, combining the subjective and objective criteria in terms of positioning and operation efficiency, is proposed to compare the performance of cooperative control in speed mode, torque mode, and hybrid control mode. Active fine adjustment experiments are carried out to verify the positioning accuracy, and the results are found to satisfy the requirements of operation. As an application example, a pedicle screw insertion experiment is performed on a pig vertebral bone, demonstrating the effectiveness of our system.

Accuracy analysis and calibration of a parallel guidance device for minimal invasive spinal surgery

In this paper a medical robot based on a 3-RPS parallel platform is presented for providing correct screw path in transpedicular fixation surgery. For improving the accuracy of the robot, a calibration approach for 3-RPS with CMM (Coordinate Measuring Instrument) data is developed. Sensitivity analysis of the error source had been done with Monte-Carlo techniques. The results show that the length errors of the joint-links are main contribution to the output error of the 3-RPS parallel manipulator; and the secondary factor is the radius error of the static and the moving platform. Based on above analysis, the calibration model of the inverse kinematics was established and the mono-branched calibration method was used. The presented method has high identification accuracy for length error of the chain. Based on the identification parameters, the results show that the method can improve the 3-RPS output accuracy.