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DRIBON: A mechatronic bone drilling tool
Mechatronics 22 (2012) 1060–1066
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Mechatronics journal homepage: www.elsevier.com/locate/mechatronics
DRIBON: A mechatronic bone drilling tool Marcos Louredo, Iñaki Díaz ⇑, Jorge Juan Gil CEIT and TECNUN, University of Navarra, Paseo Manuel Lardizábal 15, 20018, San Sebastián, Spain
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Article history: Received 13 December 2011 Accepted 2 September 2012 Available online 29 September 2012 Keywords: Bone drilling Layer detection
a b s t r a c t This paper presents a new automatic mechatronic tool for bone drilling, a procedure which is currently very manual and where depth control is critical in most scenarios. The system and methods developed involve driving a rotating drill bit in an axial direction so that both the linear movement and the rotation of the drill bit are controlled and measurable for automatic drilling procedures. Control algorithms allow the system to effectively stop the drilling procedure as a response to bone layer transitions and/or breakthroughs without damaging the surrounding tissue. Validation experiments on the new bone drilling methodology and proposed system have been carried out. Ó 2012 Elsevier Ltd. All rights reserved.
1. Introduction For medical practitioners who work in today’s operating theatres, the integration of engineering and computer technology has provided a broad catalog of inventions which have enhanced surgical performance and procedural ability to a very high standard. Most surgical procedural solutions focus on systems and techniques developed to improve dexterity in surgeons, which make procedures that were not previously technically possible feasible, and to improve the quality of interventions. The present work focuses on bone-machining surgical procedures such as drilling, reaming and sawing, all of which are very common surgical interventions. More specifically, this paper focuses on bone-drilling procedures, such as the process that is performed for the repair or correction of an undesirable bone structure by affixing one or more mechanical fasteners to the bone. A typical bone structure is comprised of a dense outer layer (cortical bone), and a less dense inner portion (trabecular bone). Depending on the surgical procedure, the bone drilling process can consist of boring through the two cortical walls (i.e., from one side of the bone to the other) or only one cortical wall (i.e., into or through the trabecular bone only). Bone drilling procedures (Fig. 1) are carried out in hospitals around the world multiple times per day across most surgical disciplines, e.g., orthopedic surgery, ear surgery, maxillofacial surgery, neurosurgery, and many others. During the drilling procedure, the surgeon uses a drill or a similar device to make a hole through the bone, requiring precision and accuracy. This delicate operation must take into consideration the surrounding tissue area and the ⇑ Corresponding author. Tel.: +34 943 212 800; fax: +34 943 213 076. E-mail addresses: [email protected] (M. Louredo), [email protected] (I. Díaz), [email protected] (J.J. Gil). 0957-4158/$ - see front matter Ó 2012 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.mechatronics.2012.09.001
correct depth levels at all times. Any deviation in the drilling path, even the most minute, can damage the tissue surrounding the bone (veins, arteries, nerves, brain tissue, spinal cord, etc.), causing irreversible damage to the patient. Currently, such drilling processes are usually carried out by employing electric or pneumatic manual drilling tools. Operating these tools is very simple and similar to the drilling tools used at home to hang a picture. The surgeon can control the rotation speed of the drill bit (with a pedal, button, etc.) while exerting a certain force against the bone to make the hole. The main disadvantage of such drilling tools is that there is no way for the surgeon to estimate when the hole is completed or the desired depth is reached. Moreover, at the point of breakthrough the drill bit can be pushed further along the drilling axis due to the inertia of the drilling force. While this undesired effect may not be very important when drilling a wall at home, it can be of critical relevance when drilling a bone since the surrounding tissue can be seriously damaged. Currently, the only way to efficiently stop the drilling procedure at the desired depth is based upon the surgeon’s experience and intuition. Thus, any means of assisting the surgeon during the operation can decrease the potential for error or mishap. The present work describes a new mechatronic device and control methods to overcome current limitations of manual drilling tools. Our focus is on developing a drilling system that avoids damage to surrounding tissue in the drilling zone, offers greater precision, and heightens safety in the operating theatre. The proposed solution lies between current manual drilling tools and complex robotic platforms. The objective is to develop a new mechatronic system that is as easy to use as a manual tool but with all the precision and sensing capabilities of a robotic platform. The new drilling tool will offer surgeons performing drilling operations with high precision and safety values.
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Fig. 1. Bone drilling.
The following sections will outline related work found in literature, the new drilling system we developed, which is called DRIBON, and the experiments carried out to validate the system. The results will clearly show an improvement over previous methods in layer transition detection. The focus is on developing an automatic mechatronic tool able to provide improved results when detecting bone layer transitions. This research is limited to a proofof-concept prototype, not a final surgical device.
2. Related work Over the last decade many solutions have been proposed to improve the current art of surgical drilling. A number of solutions rely on image-based trajectory control, which involves the surgeon using X-ray images from time to ‘‘see’’ the penetration depth. This is the current approach taken by surgeons when depth control is critical. Developments in the drilling tool have included mechatronic systems that control one or both the linear and rotational movements of the drill bit, such that the surgeon only has to place the system at the correct position and orientation. These semiautomatic and automatic solutions vary depending on the methodology they follow to control the penetration depth into the bone: (i) by using predefined penetration depth values [1] or (ii) by using control algorithms that analyze the measures of different sensors coupled to the drill bit [2–4]. The present work centers on the automatic drilling tools group. Both the rotation and the linear movement of the drill bit are automatic; that is, the surgeon places the drill bit at the desired position and orientation and pushes the start button. Afterward, the system carries out the drilling procedure automatically and stops the drill bit either at the layer transition or at bone breakthrough, according to the surgeon’s requirements. An optimal control methodology should be able to move the drill bit along its trajectory in order to achieve a minimum level of protrusion of the drill bit beyond the desired point. In general, control methods to detect bone layer transitions while drilling are based on the penetration force and cutting torque measured by sensors attached to the drilling tool (i.e force/torque sensors, accelerometers, encoders, etc.). Fig. 2 shows an example of such signals during the bone drilling process. Note that both the force and torque signals present abrupt variations at the initial and final bone drilling stages in Fig. 2. Although the shapes of the signals vary for different types of bones, the abrupt variations are always present in layer transitions. In fact, the control methods and systems previously proposed in the literature differ in the way they try to detect these variations. Most of them implement detection algorithms by predefining threshold values for these variations, and when these threshold values have
Fig. 2. Force and torque signals measured while drilling a bone with a mechatronic tool.
been reached, the system assumes that the drill bit has arrived at a bone layer transition. In 1995, Brett et al. [5] were the first authors to provide a solution for an automatic drilling methodology. They proposed a control strategy for the precise drilling of flexible bone tissues during ear surgery. To detect the moment of the drill bit’s complete breakthrough, the system identified a simultaneous persistent increase of the cutting torque and a persistent decrease of the penetration force. In subsequent studies [6,7], aspects of the tool design were examined. Some design features resulted from requirements of the procedure and human anatomy; others resulted from the functioning of the tool and the processes used. The overall tool design and operation were reviewed and the requirement for a tool support was considered. A model was used to examine the influence of drill bit shape on the drilling data and its suitability for control purposes. Simultaneously, Allota et al. [8] devised a breakthrough detection technique for a mechatronic tool designed for orthopedic surgery. The authors also proposed a theoretical model to obtain the penetration force and cutting torque parameters and to detect a breakthrough by imposing an upper limit threshold to the first derivative of the penetration force. Ong and Bouazza-Marouf [9] devised a robust detection method for drill bit breakthrough when drilling into long bones. Their work looked into the fluctuation in the drilling force profiles, drilling between successive samples and drill bit rotational speeds. The method proposed by the authors, based on a modified Kalman filter, was able to convert the profiles of differences in drilling force between successive samples and/or the drill bit rotational speed into easily recognizable and more consistent profiles, allowing a robust and repeatable detection of drill bit breakthrough. In later work, Brett et al. [10,11] described a surgical robotic system for microdrilling during a stapedotomy. Information on the state of the drilling process was derived from feed force and torque sensory data with respect to time and displacement. The drilling system was automatically able to determine the unknowns
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Time delay Beginning of the drill bit breakthrough
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Fig. 3. Robotic bone drilling system developed by Lee and Shih [12,13].
of tissue thickness, hardness and flexibility. Detection of the onset of breakthrough, which is key to establishing thickness, was via the identification of features in the multiple sensory data that characterize this condition. Lee and Shih [12,13] developed a robotic bone drilling system for applications in orthopedic surgery (Fig. 3). The proposed robotic bone drilling system consisted of an inner loop fuzzy controller for robot position control, and an outer loop PD controller for feed unit force control. Moreover, breakthrough detection was a function of thrust force threshold information and trended in drill torque and feed rate. In 2008, Coulson et al. [14] presented an autonomous surgical robot system that was able to carry out the critical process of penetrating the bone tissue of the wall of the cochlea without penetrating the endosteal membrane located immediately inside the cochlea. Recently, Taylor et al. [15] presented a surgical robotic device that is able to discriminate tissue interfaces and other controlling parameters in the space in front of the drill tip. A smart tool detects the area just in front of the tool tip and is able to control the interaction with respect to the flexing tissue in order to avoid penetration or to control the extent of protrusion with respect to the position of the tissue. To interpret the drilling conditions and the conditions leading up to breakthrough at a tissue interface, a sensing scheme that discriminates between the variety of conditions posed in the drilling environment is used. An alternative detection methodology based on wavelets was presented by Colla and Allota [16]. They investigated the application of a wavelet-based controller to a mechatronic drill for orthopedic surgery. The penetration velocity of the drill was generated on the basis of a wavelet analysis of the thrust force signal and the controller fulfilled three different tasks corresponding to different specifications of the hole to be made in a long bone: (1) first cortical wall drilled, (2) second cortical wall starts, and (3) protrusion of the second cortical wall. Each of these situations corresponds to an abrupt change in the trend of a signal, which is evaluated at each sampling stage. Using a tree-structured wavelet decomposition stage, three useful output sequences are obtained: the approximation coefficients at the first decomposition level and two detail coefficients. These latter two sequences present a peak corresponding to each breakdown in the original signal. These peaks can be easily detected by a simple threshold comparator.
Another different approach found in the literature is based on fuzzy logic and neuronal networks. A novel hand-held drilling tool devoted to orthopedic surgery was presented in [17]. The drilling tool used a fuzzy logic controller to control the penetration velocity and identify the time of incipient breakthrough. The basic idea of fuzzy logic is the association of a truth value to an expression, contrary to standard logic in which any proposition can only be true or false. Kaburlasos and Petridis [18] reported the successful application of learning, classification and feature extraction techniques to the stapedotomy surgical procedure. The authors used force and torque data during drilling to estimate the thickness of the stapes bone by learning a linear mapping of force features to torque features. This learning was attained by employing the two level fuzzy lattice (2L-FL) scheme for supervised clustering. To sum up, most of the methods presented in this section have many elements in common: (i) the use of a velocity control approach for the axial movement of the drill bit, (ii) the use of a force sensor to measure the penetration force and feed the detection control algorithm, and (iii) the use of threshold values to determine layer transitions. As a result, most of the methods have similar limitations in detecting layer transitions just before protrusion: (i) the signal of the force sensor is very noisy for control purposes, and certain delay is introduced after filtering this signal and (ii) the usage of threshold values makes the effectiveness of the algorithms among different bone types difficult; moreover, depending on the sensitivity of the threshold value it causes false detections with conservative values and a lack of detection with wider margins. Fig. 4 shows the different layer transition detection points usually found by using the summarized algorithms. The main disadvantage of most detection methodologies is that layer transitions are detected after bone protrusion. The present work proposes a new control methodology for detecting layer transitions to improve the point of detection, using a specific tool design. Our focus is on finding a method that allows fast detection (just before protrusion), and whose effectiveness is not conditioned by the sensitivity of using threshold values (low false detection rate). 3. Description of the new mechatronic bone drilling tool (DRIBON) This section describes the new mechatronic system that we have developed and which we call DRIBON [19]. The system, shown in Fig. 5, consists of three main modules: the control unit, the drilling guide, and the supporting arm.
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Drilling Guide
Fig. 6. Bone drilling guide and tool.
Supporting Arm driving pulley
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Fig. 5. The three modules of DRIBON system.
left support The Control Unit consists of a control box and a monitor or display. All the electronics are placed in this module. It acquires sensor measurements from the drilling guide, analyzes them and controls the drilling process. It also monitors drill depth and allows the surgeon to switch from an automatic to a manual procedure. Specifically, for this prototype, a dSpace DS1104 control board is used, and control algorithms run at a fixed sampling rate of 1 kHz. The Drilling Guide consists of an actuated linear carriage that is able to move a drilling tool. The control unit feeds the carriage in order to drill a hole in the bone and stop the process just before protrusion. The Supporting Arm is a standard commercial mechanism (NOGA DG61003) that is able to easily position and orient DRIBON. The proposed system has two main features that distinguish it from other drilling devices: the design solution adopted for the actuation of the linear carriage, and the detection control algorithm. The following subsections describe both parts in detail. 3.1. Description of the drilling guide Fig. 6 shows the mechatronic bone drilling tool we developed. It consists of three main parts: (1) the drill bit and motor set, (2) the feed mechanism, and (3) the body of the device. The drill bit and motor set consists of a surgical interchangeable drill bit, attached to an electric DC motor (maxon RE40 148877) that drives it at the desired speed. Both are attached to the drilling guide, which provides the axial movement to the set. An interesting feature of the DRIBON is that the drill bit and motor can be replaced with many commercial electric drilling tools, without modifying the working principle and detection capabilities of the system. Thus, the DRIBON can also be defined as an add-on element to such devices. The feed mechanism is the main component of the proposed tool. It drives the drill bit and motor in the axial drilling direction. Movement is actuated by an electric DC motor (maxon RE40 148877) and a cable-driven transmission [20]. The cable-driven transmission allows controlled movement of a linear guide (igusÒ DryLinÒ Tk-0.4-15-1,150), which holds the drill bit and motor set. Additionally, there is an optical encoder (Quantum Devices
linear guide
bearing
right shaft left shaft bearing
motor encoder
Fig. 7. Components of the drilling guide and body of the system. Table 1 Main specifications of the DRIBON. Parameter
Value
Feed workspace (axial direction) Feed displacement resolution (axial direction) Max. penetration force (continuous) Max. penetration force (peak) Max. cutting torque Rotational speed
66 mm 3.8 lm 15.3 N 51.3 N 184 m Nm 0–7500 rev/min
QD145-05, 5000 ppv) coupled to the motor to measure the movement of the drill bit in the axial direction. The main reason for using a cable transmission mechanism instead of a more commonly used lead screw is the high reversibility that the cable transmission can guarantee. This feature is essential for the developed control algorithms to detect layer transitions, and will be explained later in this paper. The last component is the body of the device. It fixes all components together (Fig. 7). For this proof-of-concept prototype, the different elements have been manufactured by a Rapid Prototype Object EDEN 3300 machine, and are made of FullcureÒ 720 material. Table 1 shows the main specifications of the device.
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Fig. 8. Control diagram for the axial displacement of the drilling guide.
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The DRIBON system works as follows: Firstly, the surgeon manually places the system at the desired position and orientation; then, he pushes the start button and activates the drill system until a bone layer transition is detected. Finally, the surgeon decides whether to go onto the next layer or finish the process. The diagram in Fig. 8 shows the axial movement control law applied to the linear guide through the DC motor and the cable transmission. The input to the system is a ramp-style position signal, with the slope being equal to the desired translational drilling speed. Then, a proportional controller is applied to the difference between the reference position of the ramp input signal and the real axial position measured by the optical encoder attached to the motor. While moving the linear guide before reaching the bone, the system smoothly follows the speed imposed by the slope of the ramp. Once drilling begins, the position error greatly increases due to the resistance encountered when the drilling movement comes up against the bone’s stiffness, and also because the controller saturates the actuation to a proper motor torque level. Note that once the motor is saturated, the control scheme works as a constant open-loop force input to the system, and the proportional controller stops commanding the displacement, but the position error keeps increasing. Simultaneous to the implementation of the actuation scheme, a detection algorithm is running at the control unit [21]. Its duty is to predict the exact moment just before the protrusion into the bone in order to stop the axial movement of the drill. To that end, the detection algorithm uses the same position error signal feed to the controller in Fig. 8. Fig. 9 shows the position reference signal, the real position measured by the encoder, and the error signal between both of them when drilling a bone with the DRIBON system. At time t = 0 s, the drill is in contact with the bone and starts the process. Due to the stiffness of the bone and the saturation of the motor, the real position lags behind the position reference, and the error signal increases as drilling time goes on. This situation remains unaltered until the bone protrusion is ready to happen (t = 125 s). Just before the protrusion into the bone, as the remaining width of the bone layer becomes very tiny, bone stiffness is reduced considerably, as is the resistance force against the movement of the drill. At that moment, and according to the implemented control movement law, the system will respond by accelerating while trying to follow the reference position, thereby minimizing the position error. The implemented detection targets this sudden acceleration to discriminate a bone layer transition. Focusing on the error signal, this variation is seen as an abrupt change in the sign of its slope, from positive to negative. This condition is implemented in the detection algorithm, imposing the detention of the axial movement of the drill as a response to a sign change of the slope of the error signal. A very important feature of the proposed algorithm is that at the detection time a very thin bone layer still remains, which the surgeon can easily break manually. This condition allows safer
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Time (s) Fig. 9. Position signals measured during the drilling process (t = 0 s bone drilling starts, t = 125 s bone protrusion starts).
drilling in critical places since the system stops the drill just before any surrounding tissue that is different to bone is reached. The prior state of the art, unlike this method, mostly detect layer transitions once bone protrusion occurs. The detection algorithm successfully detects the bone protrusion in time by employing the measurement of the optical encoder that is attached to the feeding motor. This measurement, unlike a force sensor or an accelerometer, has the advantage of having very low noise and being optimal for control purposes. Another condition for the successful implementation of the algorithm is the cable transmission used to feed the carriage. Its high reversibility allows the control scheme in Fig. 8 to be implemented, and it also allows the acceleration of the system before protrusion (Fig. 9). Although this type of transmission introduces vibration modes in system dynamics at relatively high frequency (around hundreds of Hz), drilling bones is nearly a quasi-static process (the penetration speed is very slow) and therefore, the influence of these modes is negligible, while cable pretension avoids static elongation. Finally, notice that the detection algorithm analyzes changes of tendency on the position error. Thus, the existence of error is necessary, and that is the reason why a proportional controller is used instead of a PID controller that would suppress this error and eliminate the possibility to detect the acceleration of the device. 4. Experiments This section describes several experiments carried out to validate the proposed DRIBON system. The experimental set-up for carrying out the drilling tests consists of the DRIBON system and a rigid bone holder, as shown in Fig. 10. Some limitations, which do not come into play in real drilling processes, are taken into consideration: (i) the bone is rigidly attached to a structure (rigid bone holder), (ii) no refrigeration is applied, and (iii) cooked animal bones are used. Although these considerations limit application to a real environment, they still allow the basic working principle of the detection algorithm to be validated and allow a comparison with prior state of the art that
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Fig. 12. NSK Surgic XT commercial drill coupled to the DRIBON system.
Fig. 10. Set-up for the experiments.
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Fig. 11. Measured position signals during a drilling process, and a picture of five drilled holes. Red dots show the detection points obtained by the algorithm for each cortical wall. Dashed lines show the moment of protrusion. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
also considered similar testing conditions [8,9,12]. Further work will focus on the refinement of the algorithm and the development of a final DRIBON system that will be able to be tested in a real situation without the above restrictions.
(c)
Fig. 13. (a) Error signal measured while drilling a chicken bone with the DRIBON system and a NSK Surgic XT drill, (b) front, and (c) back photographs of a hole.
Drilling experiments were performed on cortical bones along the middle section of cooked bovine femoral shafts. The whole femur, which was stripped of all soft tissue, was clamped rigidly onto the bone holder in order to ensure that there was no system compliance. The input feed rate for the axial movement was set to 12 mm/min, and the rotational speed of the drill bit was 7500 rev/min. A 6 mm diameter surgical drill bit was used for the experiments. A set of more than 50 drilling processes were performed with the DRIBON system. All of them obtained a successful detection rate, just before bone protrusion. Fig. 11 shows the different position measures and the detection time achieved by the DRIBON system in one of the processes. The results are presented in terms of the imposed drill feed displacement (ramp signal), the real drill bit penetration displacement measured by the encoder, and the position error. In order to obtain the position signals of Fig. 11, the DRIBON system was commanded to detect the cortical wall protrusion, but to continue drilling. The picture of the bone holes, however, was taken after five experiments where DRIBON was commanded to stop the process once a layer transition was detected (the red
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dot). Note that the system is able to identify the layer transition just before protrusion (the dashed line). The picture of the bone holes shows that a very thin bone layer still remains when the system stops. Another set of 10 experiments were performed by replacing the DRIBON’s drill and motor set with a commercial drilling tool (NSK Surgic XT). Fig. 12 shows the new set-up for the experiments. In this case chicken bones were used, being more appropriate for the specific power features of the commercial drill employed. The input feed rate of the DRIBON system and the rotational speed of the commercial drill were set to the same values as in the previous experiments. Fig. 13 shows the error signal measured in one of the experiments, the breakthrough detection point (red dot) and the moment of protrusion (vertical dashed line). DRIBON, as in the previous set of experiments, was commanded to detect the layer transition, but to keep on drilling in order to reach the moment of protrusion. Additionally, the figure shows two photographs of a bone hole, one taken from the front, and the other one taken from the back side, when DRIBON was commanded to stop drilling at the detection point. Note that in this case the DRIBON system is able to automatically stop the process just before the protrusion, in the same way as in previous experiments.
5. Conclusions This work has presented a new mechatronic bone drilling tool, DRIBON. The proposed system can perform the bone drilling process automatically, and stop efficiently when a layer transition or breakthrough occurs. Both the rotation and linear movement of the drill bit are automatic, that is, the surgeon places the drill bit at the desired position and orientation and pushes the start button. Afterward, the system carries out the drilling procedure automatically and stops the drill bit at the layer transition or bone breakthrough as required by the surgeon. DRIBON avoids the use of a force sensor or an accelerometer, and relies uniquely on the measure of the linear movement of the drill bit for the detection algorithm. A specific mechanical design solution has been implemented, which, together with proper control algorithms, obtains improved results regarding detection time and feasibility. By using the position signal of the drill bit, better results can be obtained with the DRIBON system that with previous systems. The position signal is less affected by electromagnetic noise, and the control methodology used provides faster detection of the layer transitions and breakthroughs. Moreover, the proposed system can be coupled to existing commercial drilling tools without losing efficiency, since sensors used for the automatic drilling control are not directly coupled to said tools. The proposed tool can be used in any bone machining process where depth-precision is critical. Some of these procedures are: stereotactic neurosurgery, spinal milling in laminectomy, inserting screws in orthopedic surgery, cochleostomies, stapedotomies, maxillofacial surgery, etc.
Future work will focus on an approach to the real conditions found in an operating theatre, taking into account the limitations considered in this paper. References [1] Anderson W. Depth controllable and measurable medical driver devices and methods of use. Patent. US 2009/0326537 A1; 2009. [2] Allotta B. Surgical drill with bit penetration control and breakthrough detection. Patent. US 6033409; 2000. [3] Hsu Y-L, Lee S-T, Wang C-F, Chen J-W, Lin H-W, Huang T-C. Automatic bone drilling apparatus for surgery operation. Patent. US 6336931; 2002. [4] Carl AA, Adams J, Craig KC, Lavery DC, Fischer G, Anthony SR, et al. Methods and systems for controlling the operation of a tool. Patent. US 2005/0116673 A1; 2005. [5] Brett PN, Baker DA, Reyes L, Blanshard J. An automatic technique for microdrilling a stapedotomy in the flexible stapes footplate. Proc Inst Mech Eng, Part H: J Eng Med 1995;209(4):255–62. [6] Baker D, Brett P, Griffiths M, Reyes L. A mechatronic drilling tool for ear surgery: a case study of some design characteristics. Mechatronics 1996;6(4):461–77. http://dx.doi.org/10.1016/0957-4158(96)00006-2. [7] Baker D, Brett P, Griffiths M, Reyes L. Surgical requirements for the stapedotomy tool: data and safety considerations. In: 18th Annual international conference of the IEEE engineering in medicine and biology society, vol. 1; 1996. p. 214–5. http://dx.doi.org/10.1109/IEMBS.1996.656922. [8] Allotta B, Belmonte F, Bosio L, Dario P. Study on a mechatronic tool for drilling in the osteosynthesis of long bones: tool/bone interaction, modeling and experiments. Mechatronics 1996;6(4):447–59. http://dx.doi.org/10.1016/ 0957-4158(96)00005-0. [9] Ong FR, Bouazza-Marouf K. Drilling of bone: a robust automatic method for the detection of drill bit break-through. Proc Inst Mech Eng, Part H: J Eng Med 1998;212(3):209–21. http://dx.doi.org/10.1243/0954411981533999. [10] Brett P, Harrison A, Thomas T. Schemes for the identification of tissue types and boundaries at the tool point for surgical needles. IEEE Trans Inform Technol Biomed 2000;4(1):30–6. http://dx.doi.org/10.1109/4233.826856. [11] Brett PN, Baker DA, Taylor R, Griffiths MV. Controlling the penetration of flexible bone tissue using the stapedotomy microdrill. Proc Inst Mech Eng, Part I: J Syst Control Eng 2004;218(5):343–51. http://dx.doi.org/10.1177/ 095965180421800502. [12] Lee W-Y, Shih C-L, Lee S-T. Force control and breakthrough detection of a bone-drilling system. IEEE/ASME Trans Mech 2004;9(1):20–9. http:// dx.doi.org/10.1109/TMECH.2004.823850. [13] Lee W-Y, Shih C-L. Control and breakthrough detection of a three-axis robotic bone drilling system. Mechatronics 2006;16(2):73–84. http://dx.doi.org/ 10.1016/j.mechatronics.2005.11.002. [14] Coulson CJ, Reid AP, Proops DW. A cochlear implantation robot in surgical practice. In: 15th International conference on mechatronics and machine vision in practice; 2008. p. 173–6. [15] Taylor R, Du X, Proops D, Reid A, Coulson C, Brett PN. A sensory-guided surgical micro-drill. Proc Inst Mech Eng, Part C: J Mech Eng Sci 2010;224(7):1531–7. http://dx.doi.org/10.1243/09544062JMES1933. [16] Colla V, Allotta B. Wavelet-based control of penetration in a mechatronic drill for orthopaedic surgery. In: IEEE international conference on robotics and automation, vol. 1; 1998. p. 711–6. http://dx.doi.org/10.1109/ ROBOT.1998.677057. [17] Allotta B, Giacalone G, Rinaldi L. A hand-held drilling tool for orthopedic surgery. IEEE/ASME Trans Mech 1997;2(4):218–29. http://dx.doi.org/10.1109/ 3516.653046. [18] Kaburlasos VG, Petridis V. Fuzzy lattice neurocomputing (fln) models. Neural Networks 2000;13(10):1145–70. http://dx.doi.org/10.1016/S0893-608. 00)00074-5. [19] Louredo M, Díaz I, Gil JJ. Método de perforación de hueso y dispositivo para llevar a cabo dicha perforación. Patent. P201100444; 2011. [20] Savall J, Martín J, Avello A. High performance linear cable transmission. J Mech Des 130 (6). http://dx.doi.org/10.1115/1.2901149. [21] Louredo M, Díaz I, Gil JJ. A robotic bone drilling methodology based on position measurements. In: IEEE RAS/EMBS international conference on biomedical robotics and biomechatronics. Roma, Italy; 2012. p. 1155-60. http://dx.doi.org/ 10.1109/BioRob.2012.6290304.
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Mechatronics journal homepage: www.elsevier.com/locate/mechatronics
DRIBON: A mechatronic bone drilling tool Marcos Louredo, Iñaki Díaz ⇑, Jorge Juan Gil CEIT and TECNUN, University of Navarra, Paseo Manuel Lardizábal 15, 20018, San Sebastián, Spain
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Article history: Received 13 December 2011 Accepted 2 September 2012 Available online 29 September 2012 Keywords: Bone drilling Layer detection
a b s t r a c t This paper presents a new automatic mechatronic tool for bone drilling, a procedure which is currently very manual and where depth control is critical in most scenarios. The system and methods developed involve driving a rotating drill bit in an axial direction so that both the linear movement and the rotation of the drill bit are controlled and measurable for automatic drilling procedures. Control algorithms allow the system to effectively stop the drilling procedure as a response to bone layer transitions and/or breakthroughs without damaging the surrounding tissue. Validation experiments on the new bone drilling methodology and proposed system have been carried out. Ó 2012 Elsevier Ltd. All rights reserved.
1. Introduction For medical practitioners who work in today’s operating theatres, the integration of engineering and computer technology has provided a broad catalog of inventions which have enhanced surgical performance and procedural ability to a very high standard. Most surgical procedural solutions focus on systems and techniques developed to improve dexterity in surgeons, which make procedures that were not previously technically possible feasible, and to improve the quality of interventions. The present work focuses on bone-machining surgical procedures such as drilling, reaming and sawing, all of which are very common surgical interventions. More specifically, this paper focuses on bone-drilling procedures, such as the process that is performed for the repair or correction of an undesirable bone structure by affixing one or more mechanical fasteners to the bone. A typical bone structure is comprised of a dense outer layer (cortical bone), and a less dense inner portion (trabecular bone). Depending on the surgical procedure, the bone drilling process can consist of boring through the two cortical walls (i.e., from one side of the bone to the other) or only one cortical wall (i.e., into or through the trabecular bone only). Bone drilling procedures (Fig. 1) are carried out in hospitals around the world multiple times per day across most surgical disciplines, e.g., orthopedic surgery, ear surgery, maxillofacial surgery, neurosurgery, and many others. During the drilling procedure, the surgeon uses a drill or a similar device to make a hole through the bone, requiring precision and accuracy. This delicate operation must take into consideration the surrounding tissue area and the ⇑ Corresponding author. Tel.: +34 943 212 800; fax: +34 943 213 076. E-mail addresses: [email protected] (M. Louredo), [email protected] (I. Díaz), [email protected] (J.J. Gil). 0957-4158/$ - see front matter Ó 2012 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.mechatronics.2012.09.001
correct depth levels at all times. Any deviation in the drilling path, even the most minute, can damage the tissue surrounding the bone (veins, arteries, nerves, brain tissue, spinal cord, etc.), causing irreversible damage to the patient. Currently, such drilling processes are usually carried out by employing electric or pneumatic manual drilling tools. Operating these tools is very simple and similar to the drilling tools used at home to hang a picture. The surgeon can control the rotation speed of the drill bit (with a pedal, button, etc.) while exerting a certain force against the bone to make the hole. The main disadvantage of such drilling tools is that there is no way for the surgeon to estimate when the hole is completed or the desired depth is reached. Moreover, at the point of breakthrough the drill bit can be pushed further along the drilling axis due to the inertia of the drilling force. While this undesired effect may not be very important when drilling a wall at home, it can be of critical relevance when drilling a bone since the surrounding tissue can be seriously damaged. Currently, the only way to efficiently stop the drilling procedure at the desired depth is based upon the surgeon’s experience and intuition. Thus, any means of assisting the surgeon during the operation can decrease the potential for error or mishap. The present work describes a new mechatronic device and control methods to overcome current limitations of manual drilling tools. Our focus is on developing a drilling system that avoids damage to surrounding tissue in the drilling zone, offers greater precision, and heightens safety in the operating theatre. The proposed solution lies between current manual drilling tools and complex robotic platforms. The objective is to develop a new mechatronic system that is as easy to use as a manual tool but with all the precision and sensing capabilities of a robotic platform. The new drilling tool will offer surgeons performing drilling operations with high precision and safety values.
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Fig. 1. Bone drilling.
The following sections will outline related work found in literature, the new drilling system we developed, which is called DRIBON, and the experiments carried out to validate the system. The results will clearly show an improvement over previous methods in layer transition detection. The focus is on developing an automatic mechatronic tool able to provide improved results when detecting bone layer transitions. This research is limited to a proofof-concept prototype, not a final surgical device.
2. Related work Over the last decade many solutions have been proposed to improve the current art of surgical drilling. A number of solutions rely on image-based trajectory control, which involves the surgeon using X-ray images from time to ‘‘see’’ the penetration depth. This is the current approach taken by surgeons when depth control is critical. Developments in the drilling tool have included mechatronic systems that control one or both the linear and rotational movements of the drill bit, such that the surgeon only has to place the system at the correct position and orientation. These semiautomatic and automatic solutions vary depending on the methodology they follow to control the penetration depth into the bone: (i) by using predefined penetration depth values [1] or (ii) by using control algorithms that analyze the measures of different sensors coupled to the drill bit [2–4]. The present work centers on the automatic drilling tools group. Both the rotation and the linear movement of the drill bit are automatic; that is, the surgeon places the drill bit at the desired position and orientation and pushes the start button. Afterward, the system carries out the drilling procedure automatically and stops the drill bit either at the layer transition or at bone breakthrough, according to the surgeon’s requirements. An optimal control methodology should be able to move the drill bit along its trajectory in order to achieve a minimum level of protrusion of the drill bit beyond the desired point. In general, control methods to detect bone layer transitions while drilling are based on the penetration force and cutting torque measured by sensors attached to the drilling tool (i.e force/torque sensors, accelerometers, encoders, etc.). Fig. 2 shows an example of such signals during the bone drilling process. Note that both the force and torque signals present abrupt variations at the initial and final bone drilling stages in Fig. 2. Although the shapes of the signals vary for different types of bones, the abrupt variations are always present in layer transitions. In fact, the control methods and systems previously proposed in the literature differ in the way they try to detect these variations. Most of them implement detection algorithms by predefining threshold values for these variations, and when these threshold values have
Fig. 2. Force and torque signals measured while drilling a bone with a mechatronic tool.
been reached, the system assumes that the drill bit has arrived at a bone layer transition. In 1995, Brett et al. [5] were the first authors to provide a solution for an automatic drilling methodology. They proposed a control strategy for the precise drilling of flexible bone tissues during ear surgery. To detect the moment of the drill bit’s complete breakthrough, the system identified a simultaneous persistent increase of the cutting torque and a persistent decrease of the penetration force. In subsequent studies [6,7], aspects of the tool design were examined. Some design features resulted from requirements of the procedure and human anatomy; others resulted from the functioning of the tool and the processes used. The overall tool design and operation were reviewed and the requirement for a tool support was considered. A model was used to examine the influence of drill bit shape on the drilling data and its suitability for control purposes. Simultaneously, Allota et al. [8] devised a breakthrough detection technique for a mechatronic tool designed for orthopedic surgery. The authors also proposed a theoretical model to obtain the penetration force and cutting torque parameters and to detect a breakthrough by imposing an upper limit threshold to the first derivative of the penetration force. Ong and Bouazza-Marouf [9] devised a robust detection method for drill bit breakthrough when drilling into long bones. Their work looked into the fluctuation in the drilling force profiles, drilling between successive samples and drill bit rotational speeds. The method proposed by the authors, based on a modified Kalman filter, was able to convert the profiles of differences in drilling force between successive samples and/or the drill bit rotational speed into easily recognizable and more consistent profiles, allowing a robust and repeatable detection of drill bit breakthrough. In later work, Brett et al. [10,11] described a surgical robotic system for microdrilling during a stapedotomy. Information on the state of the drilling process was derived from feed force and torque sensory data with respect to time and displacement. The drilling system was automatically able to determine the unknowns
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Time delay Beginning of the drill bit breakthrough
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Fig. 3. Robotic bone drilling system developed by Lee and Shih [12,13].
of tissue thickness, hardness and flexibility. Detection of the onset of breakthrough, which is key to establishing thickness, was via the identification of features in the multiple sensory data that characterize this condition. Lee and Shih [12,13] developed a robotic bone drilling system for applications in orthopedic surgery (Fig. 3). The proposed robotic bone drilling system consisted of an inner loop fuzzy controller for robot position control, and an outer loop PD controller for feed unit force control. Moreover, breakthrough detection was a function of thrust force threshold information and trended in drill torque and feed rate. In 2008, Coulson et al. [14] presented an autonomous surgical robot system that was able to carry out the critical process of penetrating the bone tissue of the wall of the cochlea without penetrating the endosteal membrane located immediately inside the cochlea. Recently, Taylor et al. [15] presented a surgical robotic device that is able to discriminate tissue interfaces and other controlling parameters in the space in front of the drill tip. A smart tool detects the area just in front of the tool tip and is able to control the interaction with respect to the flexing tissue in order to avoid penetration or to control the extent of protrusion with respect to the position of the tissue. To interpret the drilling conditions and the conditions leading up to breakthrough at a tissue interface, a sensing scheme that discriminates between the variety of conditions posed in the drilling environment is used. An alternative detection methodology based on wavelets was presented by Colla and Allota [16]. They investigated the application of a wavelet-based controller to a mechatronic drill for orthopedic surgery. The penetration velocity of the drill was generated on the basis of a wavelet analysis of the thrust force signal and the controller fulfilled three different tasks corresponding to different specifications of the hole to be made in a long bone: (1) first cortical wall drilled, (2) second cortical wall starts, and (3) protrusion of the second cortical wall. Each of these situations corresponds to an abrupt change in the trend of a signal, which is evaluated at each sampling stage. Using a tree-structured wavelet decomposition stage, three useful output sequences are obtained: the approximation coefficients at the first decomposition level and two detail coefficients. These latter two sequences present a peak corresponding to each breakdown in the original signal. These peaks can be easily detected by a simple threshold comparator.
Another different approach found in the literature is based on fuzzy logic and neuronal networks. A novel hand-held drilling tool devoted to orthopedic surgery was presented in [17]. The drilling tool used a fuzzy logic controller to control the penetration velocity and identify the time of incipient breakthrough. The basic idea of fuzzy logic is the association of a truth value to an expression, contrary to standard logic in which any proposition can only be true or false. Kaburlasos and Petridis [18] reported the successful application of learning, classification and feature extraction techniques to the stapedotomy surgical procedure. The authors used force and torque data during drilling to estimate the thickness of the stapes bone by learning a linear mapping of force features to torque features. This learning was attained by employing the two level fuzzy lattice (2L-FL) scheme for supervised clustering. To sum up, most of the methods presented in this section have many elements in common: (i) the use of a velocity control approach for the axial movement of the drill bit, (ii) the use of a force sensor to measure the penetration force and feed the detection control algorithm, and (iii) the use of threshold values to determine layer transitions. As a result, most of the methods have similar limitations in detecting layer transitions just before protrusion: (i) the signal of the force sensor is very noisy for control purposes, and certain delay is introduced after filtering this signal and (ii) the usage of threshold values makes the effectiveness of the algorithms among different bone types difficult; moreover, depending on the sensitivity of the threshold value it causes false detections with conservative values and a lack of detection with wider margins. Fig. 4 shows the different layer transition detection points usually found by using the summarized algorithms. The main disadvantage of most detection methodologies is that layer transitions are detected after bone protrusion. The present work proposes a new control methodology for detecting layer transitions to improve the point of detection, using a specific tool design. Our focus is on finding a method that allows fast detection (just before protrusion), and whose effectiveness is not conditioned by the sensitivity of using threshold values (low false detection rate). 3. Description of the new mechatronic bone drilling tool (DRIBON) This section describes the new mechatronic system that we have developed and which we call DRIBON [19]. The system, shown in Fig. 5, consists of three main modules: the control unit, the drilling guide, and the supporting arm.
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Drilling Guide
Fig. 6. Bone drilling guide and tool.
Supporting Arm driving pulley
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Fig. 5. The three modules of DRIBON system.
left support The Control Unit consists of a control box and a monitor or display. All the electronics are placed in this module. It acquires sensor measurements from the drilling guide, analyzes them and controls the drilling process. It also monitors drill depth and allows the surgeon to switch from an automatic to a manual procedure. Specifically, for this prototype, a dSpace DS1104 control board is used, and control algorithms run at a fixed sampling rate of 1 kHz. The Drilling Guide consists of an actuated linear carriage that is able to move a drilling tool. The control unit feeds the carriage in order to drill a hole in the bone and stop the process just before protrusion. The Supporting Arm is a standard commercial mechanism (NOGA DG61003) that is able to easily position and orient DRIBON. The proposed system has two main features that distinguish it from other drilling devices: the design solution adopted for the actuation of the linear carriage, and the detection control algorithm. The following subsections describe both parts in detail. 3.1. Description of the drilling guide Fig. 6 shows the mechatronic bone drilling tool we developed. It consists of three main parts: (1) the drill bit and motor set, (2) the feed mechanism, and (3) the body of the device. The drill bit and motor set consists of a surgical interchangeable drill bit, attached to an electric DC motor (maxon RE40 148877) that drives it at the desired speed. Both are attached to the drilling guide, which provides the axial movement to the set. An interesting feature of the DRIBON is that the drill bit and motor can be replaced with many commercial electric drilling tools, without modifying the working principle and detection capabilities of the system. Thus, the DRIBON can also be defined as an add-on element to such devices. The feed mechanism is the main component of the proposed tool. It drives the drill bit and motor in the axial drilling direction. Movement is actuated by an electric DC motor (maxon RE40 148877) and a cable-driven transmission [20]. The cable-driven transmission allows controlled movement of a linear guide (igusÒ DryLinÒ Tk-0.4-15-1,150), which holds the drill bit and motor set. Additionally, there is an optical encoder (Quantum Devices
linear guide
bearing
right shaft left shaft bearing
motor encoder
Fig. 7. Components of the drilling guide and body of the system. Table 1 Main specifications of the DRIBON. Parameter
Value
Feed workspace (axial direction) Feed displacement resolution (axial direction) Max. penetration force (continuous) Max. penetration force (peak) Max. cutting torque Rotational speed
66 mm 3.8 lm 15.3 N 51.3 N 184 m Nm 0–7500 rev/min
QD145-05, 5000 ppv) coupled to the motor to measure the movement of the drill bit in the axial direction. The main reason for using a cable transmission mechanism instead of a more commonly used lead screw is the high reversibility that the cable transmission can guarantee. This feature is essential for the developed control algorithms to detect layer transitions, and will be explained later in this paper. The last component is the body of the device. It fixes all components together (Fig. 7). For this proof-of-concept prototype, the different elements have been manufactured by a Rapid Prototype Object EDEN 3300 machine, and are made of FullcureÒ 720 material. Table 1 shows the main specifications of the device.
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Fig. 8. Control diagram for the axial displacement of the drilling guide.
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The DRIBON system works as follows: Firstly, the surgeon manually places the system at the desired position and orientation; then, he pushes the start button and activates the drill system until a bone layer transition is detected. Finally, the surgeon decides whether to go onto the next layer or finish the process. The diagram in Fig. 8 shows the axial movement control law applied to the linear guide through the DC motor and the cable transmission. The input to the system is a ramp-style position signal, with the slope being equal to the desired translational drilling speed. Then, a proportional controller is applied to the difference between the reference position of the ramp input signal and the real axial position measured by the optical encoder attached to the motor. While moving the linear guide before reaching the bone, the system smoothly follows the speed imposed by the slope of the ramp. Once drilling begins, the position error greatly increases due to the resistance encountered when the drilling movement comes up against the bone’s stiffness, and also because the controller saturates the actuation to a proper motor torque level. Note that once the motor is saturated, the control scheme works as a constant open-loop force input to the system, and the proportional controller stops commanding the displacement, but the position error keeps increasing. Simultaneous to the implementation of the actuation scheme, a detection algorithm is running at the control unit [21]. Its duty is to predict the exact moment just before the protrusion into the bone in order to stop the axial movement of the drill. To that end, the detection algorithm uses the same position error signal feed to the controller in Fig. 8. Fig. 9 shows the position reference signal, the real position measured by the encoder, and the error signal between both of them when drilling a bone with the DRIBON system. At time t = 0 s, the drill is in contact with the bone and starts the process. Due to the stiffness of the bone and the saturation of the motor, the real position lags behind the position reference, and the error signal increases as drilling time goes on. This situation remains unaltered until the bone protrusion is ready to happen (t = 125 s). Just before the protrusion into the bone, as the remaining width of the bone layer becomes very tiny, bone stiffness is reduced considerably, as is the resistance force against the movement of the drill. At that moment, and according to the implemented control movement law, the system will respond by accelerating while trying to follow the reference position, thereby minimizing the position error. The implemented detection targets this sudden acceleration to discriminate a bone layer transition. Focusing on the error signal, this variation is seen as an abrupt change in the sign of its slope, from positive to negative. This condition is implemented in the detection algorithm, imposing the detention of the axial movement of the drill as a response to a sign change of the slope of the error signal. A very important feature of the proposed algorithm is that at the detection time a very thin bone layer still remains, which the surgeon can easily break manually. This condition allows safer
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drilling in critical places since the system stops the drill just before any surrounding tissue that is different to bone is reached. The prior state of the art, unlike this method, mostly detect layer transitions once bone protrusion occurs. The detection algorithm successfully detects the bone protrusion in time by employing the measurement of the optical encoder that is attached to the feeding motor. This measurement, unlike a force sensor or an accelerometer, has the advantage of having very low noise and being optimal for control purposes. Another condition for the successful implementation of the algorithm is the cable transmission used to feed the carriage. Its high reversibility allows the control scheme in Fig. 8 to be implemented, and it also allows the acceleration of the system before protrusion (Fig. 9). Although this type of transmission introduces vibration modes in system dynamics at relatively high frequency (around hundreds of Hz), drilling bones is nearly a quasi-static process (the penetration speed is very slow) and therefore, the influence of these modes is negligible, while cable pretension avoids static elongation. Finally, notice that the detection algorithm analyzes changes of tendency on the position error. Thus, the existence of error is necessary, and that is the reason why a proportional controller is used instead of a PID controller that would suppress this error and eliminate the possibility to detect the acceleration of the device. 4. Experiments This section describes several experiments carried out to validate the proposed DRIBON system. The experimental set-up for carrying out the drilling tests consists of the DRIBON system and a rigid bone holder, as shown in Fig. 10. Some limitations, which do not come into play in real drilling processes, are taken into consideration: (i) the bone is rigidly attached to a structure (rigid bone holder), (ii) no refrigeration is applied, and (iii) cooked animal bones are used. Although these considerations limit application to a real environment, they still allow the basic working principle of the detection algorithm to be validated and allow a comparison with prior state of the art that
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Fig. 12. NSK Surgic XT commercial drill coupled to the DRIBON system.
Fig. 10. Set-up for the experiments.
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Fig. 11. Measured position signals during a drilling process, and a picture of five drilled holes. Red dots show the detection points obtained by the algorithm for each cortical wall. Dashed lines show the moment of protrusion. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
also considered similar testing conditions [8,9,12]. Further work will focus on the refinement of the algorithm and the development of a final DRIBON system that will be able to be tested in a real situation without the above restrictions.
(c)
Fig. 13. (a) Error signal measured while drilling a chicken bone with the DRIBON system and a NSK Surgic XT drill, (b) front, and (c) back photographs of a hole.
Drilling experiments were performed on cortical bones along the middle section of cooked bovine femoral shafts. The whole femur, which was stripped of all soft tissue, was clamped rigidly onto the bone holder in order to ensure that there was no system compliance. The input feed rate for the axial movement was set to 12 mm/min, and the rotational speed of the drill bit was 7500 rev/min. A 6 mm diameter surgical drill bit was used for the experiments. A set of more than 50 drilling processes were performed with the DRIBON system. All of them obtained a successful detection rate, just before bone protrusion. Fig. 11 shows the different position measures and the detection time achieved by the DRIBON system in one of the processes. The results are presented in terms of the imposed drill feed displacement (ramp signal), the real drill bit penetration displacement measured by the encoder, and the position error. In order to obtain the position signals of Fig. 11, the DRIBON system was commanded to detect the cortical wall protrusion, but to continue drilling. The picture of the bone holes, however, was taken after five experiments where DRIBON was commanded to stop the process once a layer transition was detected (the red
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dot). Note that the system is able to identify the layer transition just before protrusion (the dashed line). The picture of the bone holes shows that a very thin bone layer still remains when the system stops. Another set of 10 experiments were performed by replacing the DRIBON’s drill and motor set with a commercial drilling tool (NSK Surgic XT). Fig. 12 shows the new set-up for the experiments. In this case chicken bones were used, being more appropriate for the specific power features of the commercial drill employed. The input feed rate of the DRIBON system and the rotational speed of the commercial drill were set to the same values as in the previous experiments. Fig. 13 shows the error signal measured in one of the experiments, the breakthrough detection point (red dot) and the moment of protrusion (vertical dashed line). DRIBON, as in the previous set of experiments, was commanded to detect the layer transition, but to keep on drilling in order to reach the moment of protrusion. Additionally, the figure shows two photographs of a bone hole, one taken from the front, and the other one taken from the back side, when DRIBON was commanded to stop drilling at the detection point. Note that in this case the DRIBON system is able to automatically stop the process just before the protrusion, in the same way as in previous experiments.
5. Conclusions This work has presented a new mechatronic bone drilling tool, DRIBON. The proposed system can perform the bone drilling process automatically, and stop efficiently when a layer transition or breakthrough occurs. Both the rotation and linear movement of the drill bit are automatic, that is, the surgeon places the drill bit at the desired position and orientation and pushes the start button. Afterward, the system carries out the drilling procedure automatically and stops the drill bit at the layer transition or bone breakthrough as required by the surgeon. DRIBON avoids the use of a force sensor or an accelerometer, and relies uniquely on the measure of the linear movement of the drill bit for the detection algorithm. A specific mechanical design solution has been implemented, which, together with proper control algorithms, obtains improved results regarding detection time and feasibility. By using the position signal of the drill bit, better results can be obtained with the DRIBON system that with previous systems. The position signal is less affected by electromagnetic noise, and the control methodology used provides faster detection of the layer transitions and breakthroughs. Moreover, the proposed system can be coupled to existing commercial drilling tools without losing efficiency, since sensors used for the automatic drilling control are not directly coupled to said tools. The proposed tool can be used in any bone machining process where depth-precision is critical. Some of these procedures are: stereotactic neurosurgery, spinal milling in laminectomy, inserting screws in orthopedic surgery, cochleostomies, stapedotomies, maxillofacial surgery, etc.
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