BiomedicalEngineering592 (a) The center of one patch in S A,2 (b) Initialization of its correspondence assignment in S B,1 (c) The center of one patch in S B,2 (d) Initialization of its correspondence assignment in S A,1 Fig. 6. The initialization for the mutual registration between level 2 and 1 using the assignment results at level 3 (a) (b) (c) (d) (e) (f) (g) (h) Fig. 7. The result of mutual registration between level 2 and 1, (a)(e): centers of two patches in S A,2 ; (b)(f): centers of their correspondent patches in S B,1 ; (c)(g): centers of two patches in S B,2 where most probable correspondence assignment in S B,1 of (a)(e) are their subpatches; (d)(h): centers of the correspondent patches of (c)(g) in S A,2 ; the size of the dots in (b)(d)(f)(h) represents the probability of the correspondence assignment The correspondence assignment using the graphical model based mutual registration is then carried out on them. The underlying graph topology G is selected as a random graph, in which the degree of each node is at least 5 (connected with 5 nearest neighbours) and the average degree of one node is 10. Λ ′ = Diag(σ 2 D ,σ 2 A ,σ 2 AL ) −1 in (4) is selected as σ D = d i,j A,l /4, σ A = σ AL = 20 ∘ . ∙ The results of the mutual registration at the coarsest level l = 3 and l = 2 are shown in Fig. 5. Obviously the two surfaces are already roughly aligned at the coarsest level and this shows that the proposed algorithm does not ask for any initialization. ∙ The registration result at coarser level is then used to initialize the correspondence as- signment at finer level as shown in Fig. 6. It can be observed that the number of candi- dates of each landmark at a finer level is greatly reduced due to the initialization. ∙ The advantage of the parallel mutual registration between the two surfaces can be ob- served from Fig. 7. The mutual registration can explore the shape information of two surfaces and exchange correspondence assignment information between them. This strong constraint forces the correspondent landmarks on two surfaces to mutually as- sign to each other quickly. It’s observed during the experiment the belief propagation at each level can converge in less than 10 iterations. ∙ As mentioned before, the goal of a nonrigid registration is to find optimal correspon- dence assignment between shapes. Since both surfaces are generated from the same PCA model, each landmark on a surface carries a point index in the PCA model. We take the landmarks with the same point index on the two surfaces as the ground truth of the correspondence assignment and then compute the registration error as the dis- tance between the correspondent landmark obtained by our registration algorithm and the ground truth position from prior knowledge of the PCA model. The registration error is evaluated on both shapes as 2.7 ± 2.3mm. Of course the prior correspondence knowledge may not be the ground truth but it can be regarded as a proper reference. 5. Conclusions In this paper we proposed a fully automatic scheme for nonrigid surface matching. The non- rigid surface matching is formalized as a graphical model based Bayesian inference and the belief propagation is used to achieve the optimization to find the optimal correspondence as- signment between shapes. To further reduce the computational cost and enhance the robust- ness to noise and local optima, a hierarchical mutual registration strategy is implemented so that the shape information of the two surfaces can be simultaneously explored. Experiments on randomly generated surfaces from a PCA based statistical model showed the capability of the proposed algorithm to achieve an automatic nonrigid surface registration. The proposed scheme can also be extended to incorporate other shape descriptors such as the Gaussian curvature as used in (Xiao et al., 2007) and the shape context (Belongie et al., 2002) since they can be easily modeled as local believes of each vertex in our graphical model based scheme. One limitation of the proposed algorithm lies in the way that it handles the nonrigid defor- mation. Different from the commonly used TPS based deformation energy to set constraints on the shape deformation, our algorithm encodes a nonrigid deformation by the deformation of the subparts of a shape such as the distances and angles between landmarks. It’s difficult to design a metric, which can accurately evaluate the deformation energy. Future work will be carried out to design better cost functions, which can measure the deformation energy more accurately by combining more shape information including local information such as curva- ture and deformation energies at different representation levels. 6. References Cootes, T., Taylor, C.: Statistical models of appearance for computer vision. Technical report, University of Manchester, U.K. (2004) Xu, C., Yezzi, A., Prince, J.: A summary of geometric level-set analogues for a general class of parametric active contour and surface models (2001) Lee, S.M., Abbott, A.L., Clark, N.A., Araman, P.A.: A shape representation for planar curves by shape signature harmonic embedding. In: CVPR06. (2006) 1940 – 1947 Roy, A.S., Gopinath, A., Rangarajan, A.: Deformable density matching for 3d non-rigid regis- tration of shapes. In: MICCAI 2007. (2007) 942–949 Jiang, Y.F., Xie, J., Sun, D.Q., Tsui, H.: Shape registration by simultaneously optimizing repre- sentation and transformation. In: MICCAI 2007. (2007) 809–817 AutomaticMutualNonrigidRegistrationofDenseSurfaceModels byGraphicalModelbasedInference 593 (a) The center of one patch in S A,2 (b) Initialization of its correspondence assignment in S B,1 (c) The center of one patch in S B,2 (d) Initialization of its correspondence assignment in S A,1 Fig. 6. The initialization for the mutual registration between level 2 and 1 using the assignment results at level 3 (a) (b) (c) (d) (e) (f) (g) (h) Fig. 7. The result of mutual registration between level 2 and 1, (a)(e): centers of two patches in S A,2 ; (b)(f): centers of their correspondent patches in S B,1 ; (c)(g): centers of two patches in S B,2 where most probable correspondence assignment in S B,1 of (a)(e) are their subpatches; (d)(h): centers of the correspondent patches of (c)(g) in S A,2 ; the size of the dots in (b)(d)(f)(h) represents the probability of the correspondence assignment The correspondence assignment using the graphical model based mutual registration is then carried out on them. The underlying graph topology G is selected as a random graph, in which the degree of each node is at least 5 (connected with 5 nearest neighbours) and the average degree of one node is 10. Λ ′ = Diag(σ 2 D ,σ 2 A ,σ 2 AL ) −1 in (4) is selected as σ D = d i,j A,l /4, σ A = σ AL = 20 ∘ . ∙ The results of the mutual registration at the coarsest level l = 3 and l = 2 are shown in Fig. 5. Obviously the two surfaces are already roughly aligned at the coarsest level and this shows that the proposed algorithm does not ask for any initialization. ∙ The registration result at coarser level is then used to initialize the correspondence as- signment at finer level as shown in Fig. 6. It can be observed that the number of candi- dates of each landmark at a finer level is greatly reduced due to the initialization. ∙ The advantage of the parallel mutual registration between the two surfaces can be ob- served from Fig. 7. The mutual registration can explore the shape information of two surfaces and exchange correspondence assignment information between them. This strong constraint forces the correspondent landmarks on two surfaces to mutually as- sign to each other quickly. It’s observed during the experiment the belief propagation at each level can converge in less than 10 iterations. ∙ As mentioned before, the goal of a nonrigid registration is to find optimal correspon- dence assignment between shapes. Since both surfaces are generated from the same PCA model, each landmark on a surface carries a point index in the PCA model. We take the landmarks with the same point index on the two surfaces as the ground truth of the correspondence assignment and then compute the registration error as the dis- tance between the correspondent landmark obtained by our registration algorithm and the ground truth position from prior knowledge of the PCA model. The registration error is evaluated on both shapes as 2.7 ± 2.3mm. Of course the prior correspondence knowledge may not be the ground truth but it can be regarded as a proper reference. 5. Conclusions In this paper we proposed a fully automatic scheme for nonrigid surface matching. The non- rigid surface matching is formalized as a graphical model based Bayesian inference and the belief propagation is used to achieve the optimization to find the optimal correspondence as- signment between shapes. To further reduce the computational cost and enhance the robust- ness to noise and local optima, a hierarchical mutual registration strategy is implemented so that the shape information of the two surfaces can be simultaneously explored. Experiments on randomly generated surfaces from a PCA based statistical model showed the capability of the proposed algorithm to achieve an automatic nonrigid surface registration. The proposed scheme can also be extended to incorporate other shape descriptors such as the Gaussian curvature as used in (Xiao et al., 2007) and the shape context (Belongie et al., 2002) since they can be easily modeled as local believes of each vertex in our graphical model based scheme. One limitation of the proposed algorithm lies in the way that it handles the nonrigid defor- mation. Different from the commonly used TPS based deformation energy to set constraints on the shape deformation, our algorithm encodes a nonrigid deformation by the deformation of the subparts of a shape such as the distances and angles between landmarks. It’s difficult to design a metric, which can accurately evaluate the deformation energy. Future work will be carried out to design better cost functions, which can measure the deformation energy more accurately by combining more shape information including local information such as curva- ture and deformation energies at different representation levels. 6. References Cootes, T., Taylor, C.: Statistical models of appearance for computer vision. Technical report, University of Manchester, U.K. (2004) Xu, C., Yezzi, A., Prince, J.: A summary of geometric level-set analogues for a general class of parametric active contour and surface models (2001) Lee, S.M., Abbott, A.L., Clark, N.A., Araman, P.A.: A shape representation for planar curves by shape signature harmonic embedding. In: CVPR06. (2006) 1940 – 1947 Roy, A.S., Gopinath, A., Rangarajan, A.: Deformable density matching for 3d non-rigid regis- tration of shapes. In: MICCAI 2007. (2007) 942–949 Jiang, Y.F., Xie, J., Sun, D.Q., Tsui, H.: Shape registration by simultaneously optimizing repre- sentation and transformation. In: MICCAI 2007. (2007) 809–817 BiomedicalEngineering594 Belongie, S., Malik, J., Puzicha, J.: Shape matching and object recognition using shape con- texts. IEEE Transactions on Pattern Analyis and Machine Intelligence 24 (2002) 509– 522 Jain, V., Zhang, H.: Robust 3d shape correspondence in the spectral domain. In: International Conference on Shape Modeling and Applications(SMI). (2006) Coughlan, J., Ferreira, S.: Finding deformable shapes using loopy belief propagation. In: ECCV’02. (2002) 453–468 Caetano, T.S., Caeli, T., Barone, D.A.C.: An optimal probabilistic graphical model for point set matching. Technical Report Technical Report TR 04-03, University of Alberta, Edmonton, Alberta Canada (2004) Rangarajan, A., Coughlan, J., Yuille, A.L.: A bayesian network framework for relational shape matching. In: ICCV’03. (2003) 671–678 Zhang, L., Seitz, S.M.: Parameter estimation for mrf stereo. In: CVPR’05. (2005) 288–295 Sun, J., Zheng, N.N., Shum, H.Y.: Stereo matching using belief propagation. IEEE Transactions on Pattern Analysis and Machine Interlligence 25 (2003) 1–14 Xiao, P.D., Barnes, N., Caetano, T., Lieby, P.: An MRF and Gaussian curvature based shape representation for shape matching. In: CVPR07. (2007) 17–22 Gibbs, A.L.: Bounding the convergence time of the gibbs sampler in bayesian image restroat- ion. Biometrika 87(4) (2000) 749–766 McEliece, R.J., MacKay, D.J.C., Cheng, J.F.: Turbo decoding as an instance of pearl’s ”be- liefpropagation” algorithm. IEEE Journal on Selected Areas in Communications 16 (1998) 140–152 IntelligentandPersonalisedHydrocephalusTreatmentandManagement 595 IntelligentandPersonalisedHydrocephalusTreatmentandManagement LinaMomani,AbdelRahmanAlkharabshehandWaleedAl-Nuaimy X Intelligent and Personalised Hydrocephalus Treatment and Management Lina Momani, Abdel Rahman Alkharabsheh and Waleed Al-Nuaimy University of Liverpool United Kingdom 1. Introduction Personalised healthcare is primarily concerned with the devolution of patient monitoring and treatment from the hospital to the home. Solutions, such as body-worn sensors for clinical and healthcare monitoring, improve the quality of life by offering patients greater independence. Such solutions can go beyond monitoring to active intervention and treatment based on sensory measurement and patient feedback, effectively taking healthcare out of the hospital environment. Such personalised healthcare solutions play an increasingly important role in delivering high quality and cost-effective healthcare. The realisation of truly autonomous systems for the personalised treatment of physiological disorders such as hydrocephalus is closer than ever. This chapter is concerned with the spreading of awareness, particularly among the biomedical engineering community e.g. organisations, companies, physicians and patients, about the possibilities that current technology offers in the area of intelligent and personalised hydrocephalus implants that seek to autonomously manage the symptoms and treat the causes in a manner specifically tuned to the individual patient. This chapter provides an insight into the workings of such a system, its pros and cons and how it can dramatically reduce patient suffering and long hospitalisation periods while increasing the quality of care that is provided. 1.1 Hydrocephalus The human brain is surrounded by a fluid called the cerebrospinal fluid (CSF), that protects it from physical injury, keeps its tissue moist and transports the products of metabolism. This fluid is constantly produced in the parenchyma at rate of approximately 20ml.h −1 and drained through granulations near the sagittal sinus. If the rate of CSF absorption or drainage is consistently less than the rate of production (for a variety of reasons), the ventricles expand causing the brain to become compressed, leading to the disorder known as hydrocephalus (ASBAH, 2009), as shown in Fig. 1. 33 BiomedicalEngineering596 (a) (b) Fig. 1. Schematic drawing for brain in (a) normal and (b) hydrocephalus cases, showing enlarged ventricles. This leads to an elevation of the pressure exerted by the cranium on the brain tissue, cerebrospinal fluid, and the brain’s circulating blood volume, referred to as intracranial pressure (ICP), and manifest itself in symptoms such as headache, vomiting, nausea or coma. ICP is a dynamic phenomenon constantly fluctuating in response to activities such as exercise, coughing, straining, arterial pulsation, and respiratory cycle. ICP is measured in millimeters of mercury (mmHg) and, at rest, is normally 7-15 mmHg for a supine adult, and becomes negative (averaging -10 mmHg) in the vertical position (Steiner & Andrews, 2006). Hydrocephalic patients may experience pressures of up to 120 mmHg. If left untreated, elevated ICP may lead to serious problems in the brain. 1.2 Current Treatment Since the 1960s the usual treatment for hydrocephalus is to insert a shunting device in the patient’s CSF system. This is simply a device which diverts the accumulated CSF around the obstructed pathways and returns it to the bloodstream, thus reducing ICP, and alleviating the symptoms of hydrocephalus. It consists of a flexible tube with a valve to control the rate of drainage and prevent back-flow. These valves are passive mechanical devices that open and close depending on either the differential pressure or flow. Although there are various valve technologies and approaches, they all essentially do the same thing, which is to attempt to passively control the symptoms of hydrocephalus by assisting the body’s natural drainage system. The valve is usually chosen by the surgeon on the grounds of experience, cost and personal preference. Despite shunting developments, shunting can have complications, with different types of shunts seemingly associated with different types of complications. Shunt complications can be very serious and become life threatening if not discovered and treated early. However, due to their passive mode of operation, shunt malfunctions are generally not detected before they manifest clinically. These can be divided into issues of under-drainage, over-drainage and infection. Over-drainage and under-drainage are typical drawbacks of such shunts, where CSF is either drained in excess or less than needed, which could cause dramatic effects on the patient such as brain damage. The common cause for these two drawbacks might be an inappropriate opening/closing of the valve in respect of the duration or the timing. In other words, valve open for too short/too long periods or it opens/closes at the right timing. Under-drainage is usually due to blockage of the upper or lower tubes of the shunt by in- growing tissue, though it can also be caused by the shunt breaking or its parts becoming disconnected from each other. The rate of blockage can be as high as 20% in the first year after insertion, decreasing to approximately 5% per year (Casey, et al., 1997), therefore, the clinical presentation of shunt blockage is usually dominated by signs of raised pressure as the brain fluid (CSF) builds up. As ICP is not readily measurable, interferences must be drawn from the symptoms presented. Sometimes the symptoms come on quickly over hour or days, but occasionally they may develop over many weeks with intermittent headache, and tiredness, change in behaviour or deterioration in schoolwork. Diagnosing shunt blockage is not always straightforward. In fact, parents can be as successful at diagnosing shunt blockage as GPs and paediatricians. Whilst additional investigations such as CT scans, X-rays and a shunt taps may help, a definitive diagnosis is sometimes only possible through surgery (ASBAH, 2009). In the case of over-drainage, the shunt allows CSF to drain from the ventricles more quickly than it is produced. If this happens suddenly, then the ventricles in the brain collapse, tearing delicate blood vessels on the outside of the brain and causing a haemorrhage. This can be trivial or it can cause symptoms similar to those of a stroke. If the over-drainage is more gradual, the ventricles collapse gradually to become slit-like. This often interferes with shunt function causing the opposite problem, high CSF pressure, to reappear. The symptoms of over-drainage can be very similar to those of under-drainage though there are important differences. Difficulty in diagnosing over-/under-drainage can make treatment of this complication particularly frustrating for patients and their families. It may be necessary to monitor ICP, often over 24 hours. This can be done using an external pressure monitor in the scalp connected to a recorder. Early ICP monitoring is recommended when the clinician is unable to assess the neurological examination accurately. The main concerns are the risks of infection, bleeding, device accuracy and drift of measurement over time. Thus to avoid these risks, a research work is undergoing to develop implanted pressure sensors for short and long term monitoring interrogated by telemetry (Hodgins et al., 2008). Studies have shown that the use of an ‘antisyphon device', a small button inserted into the shunt tubing, will often solve the over-drainage problem, but this does not always work. A ‘programmable' or adjustable shunt is intended to allow adjustment of the working pressure of the valve without operation. The valve contains magnets, which allow the setting to be changed by laying a second magnetic device on the scalp. This is undoubtedly useful where the need for a valve of a different pressure arises, but the adjustable valve is no less prone to over-drainage than any other and it cannot be used to treat this condition (Casey et al., 1997). IntelligentandPersonalisedHydrocephalusTreatmentandManagement 597 (a) (b) Fig. 1. Schematic drawing for brain in (a) normal and (b) hydrocephalus cases, showing enlarged ventricles. This leads to an elevation of the pressure exerted by the cranium on the brain tissue, cerebrospinal fluid, and the brain’s circulating blood volume, referred to as intracranial pressure (ICP), and manifest itself in symptoms such as headache, vomiting, nausea or coma. ICP is a dynamic phenomenon constantly fluctuating in response to activities such as exercise, coughing, straining, arterial pulsation, and respiratory cycle. ICP is measured in millimeters of mercury (mmHg) and, at rest, is normally 7-15 mmHg for a supine adult, and becomes negative (averaging -10 mmHg) in the vertical position (Steiner & Andrews, 2006). Hydrocephalic patients may experience pressures of up to 120 mmHg. If left untreated, elevated ICP may lead to serious problems in the brain. 1.2 Current Treatment Since the 1960s the usual treatment for hydrocephalus is to insert a shunting device in the patient’s CSF system. This is simply a device which diverts the accumulated CSF around the obstructed pathways and returns it to the bloodstream, thus reducing ICP, and alleviating the symptoms of hydrocephalus. It consists of a flexible tube with a valve to control the rate of drainage and prevent back-flow. These valves are passive mechanical devices that open and close depending on either the differential pressure or flow. Although there are various valve technologies and approaches, they all essentially do the same thing, which is to attempt to passively control the symptoms of hydrocephalus by assisting the body’s natural drainage system. The valve is usually chosen by the surgeon on the grounds of experience, cost and personal preference. Despite shunting developments, shunting can have complications, with different types of shunts seemingly associated with different types of complications. Shunt complications can be very serious and become life threatening if not discovered and treated early. However, due to their passive mode of operation, shunt malfunctions are generally not detected before they manifest clinically. These can be divided into issues of under-drainage, over-drainage and infection. Over-drainage and under-drainage are typical drawbacks of such shunts, where CSF is either drained in excess or less than needed, which could cause dramatic effects on the patient such as brain damage. The common cause for these two drawbacks might be an inappropriate opening/closing of the valve in respect of the duration or the timing. In other words, valve open for too short/too long periods or it opens/closes at the right timing. Under-drainage is usually due to blockage of the upper or lower tubes of the shunt by in- growing tissue, though it can also be caused by the shunt breaking or its parts becoming disconnected from each other. The rate of blockage can be as high as 20% in the first year after insertion, decreasing to approximately 5% per year (Casey, et al., 1997), therefore, the clinical presentation of shunt blockage is usually dominated by signs of raised pressure as the brain fluid (CSF) builds up. As ICP is not readily measurable, interferences must be drawn from the symptoms presented. Sometimes the symptoms come on quickly over hour or days, but occasionally they may develop over many weeks with intermittent headache, and tiredness, change in behaviour or deterioration in schoolwork. Diagnosing shunt blockage is not always straightforward. In fact, parents can be as successful at diagnosing shunt blockage as GPs and paediatricians. Whilst additional investigations such as CT scans, X-rays and a shunt taps may help, a definitive diagnosis is sometimes only possible through surgery (ASBAH, 2009). In the case of over-drainage, the shunt allows CSF to drain from the ventricles more quickly than it is produced. If this happens suddenly, then the ventricles in the brain collapse, tearing delicate blood vessels on the outside of the brain and causing a haemorrhage. This can be trivial or it can cause symptoms similar to those of a stroke. If the over-drainage is more gradual, the ventricles collapse gradually to become slit-like. This often interferes with shunt function causing the opposite problem, high CSF pressure, to reappear. The symptoms of over-drainage can be very similar to those of under-drainage though there are important differences. Difficulty in diagnosing over-/under-drainage can make treatment of this complication particularly frustrating for patients and their families. It may be necessary to monitor ICP, often over 24 hours. This can be done using an external pressure monitor in the scalp connected to a recorder. Early ICP monitoring is recommended when the clinician is unable to assess the neurological examination accurately. The main concerns are the risks of infection, bleeding, device accuracy and drift of measurement over time. Thus to avoid these risks, a research work is undergoing to develop implanted pressure sensors for short and long term monitoring interrogated by telemetry (Hodgins et al., 2008). Studies have shown that the use of an ‘antisyphon device', a small button inserted into the shunt tubing, will often solve the over-drainage problem, but this does not always work. A ‘programmable' or adjustable shunt is intended to allow adjustment of the working pressure of the valve without operation. The valve contains magnets, which allow the setting to be changed by laying a second magnetic device on the scalp. This is undoubtedly useful where the need for a valve of a different pressure arises, but the adjustable valve is no less prone to over-drainage than any other and it cannot be used to treat this condition (Casey et al., 1997). BiomedicalEngineering598 One of the obvious reasons for such drawbacks is the inability of such shunts to autonomously respond to the dynamic environment. Inaccuracies and long term drift are also considered among the drawbacks of such shunts. This is mainly due to the fact that these shunts are (typically, but not always) regulated according to the differential pressure across the valves, which differs from intracranial pressure in the brain. 1.3 Motivations Beside their documented drawbacks (Aschoff, 2001; Schley, 2004), shunts do not suit many hydrocephalus patients. This can be realised from the considerable high shunt revision and failure rates (between 30% and 40% of all shunts placed in paediatric patients fail within 1 year (Albright et al., 1988; Villavicencio et al., 2003; Piatt et al.,1993; Piatt,1995) and it is not uncommon for patients to have multiple shunt revisions within their lifetime). Shunt insertion explicitly changes the CSF dynamics in patients with hydrocephalus, causing many to improve clinically. However, the relationship between a changed hydrodynamic state and improved clinical performance is not fully known. Therefore, further research in this area is an important challenge for the hydrocephalus research community, where development of better methods for assessment of CSF dynamic parameters as well as studies to test hypotheses on relationships between CSF dynamics and outcome after shunting is targeted. The aims are for a better understanding of hydrocephalus pathophysiology and to find new predictive tests. Furthermore, the shunt designers had changed the shunt goal to have the option of re- establishing shunt independence step by step. This means that the statement of Hemmer “once a shunt, always a shunt” is no longer true. Nevertheless, most patients seem to be only partially shunt-dependent, i.e. their natural drainage system still functions to some extent. The degree of shunt-dependence may range from 1% to 100%, thus draining 30-50% of CSF production may be sufficient to keep the ICP within physiological ranges, and only a few need full drainage (Aschoff, 2001). Thus the current generation of shunts do not help patients overcome the underlying problems, but on the contrary, they tend to encourage the patients to become fully shunt dependent. Research has shown however, that in some cases, shunt dependence could be reduced to less than 1% (Aschoff, 2001) which could even allow the eventual removal of the shunt (Takahashi, 2001). It is envisaged that the next generation of shunts should be able to achieve a controlled shunt arrest in the long run. The future will bring other options related to the control of CSF production and absorption. Perhaps different valve designs will be more effective in long-term treatment and eventually the development of “smart” shunts. These will be able to react to intracranial physiology and will drain CSF in response to these changes in intracranial dynamics, rather than drain on a continuous basis (Jones & Klinge, 2008). To address the lack of personalised treatment, the difficulty in diagnosing shunt faults, the high rate of shunt revisions, the high shunt dependency, and the lack of full understanding of shunt effect on the intracranial hydrodynamics, a personalised hydrocephalus shunting system needs to be developed. This would be tasked with the following:  Frequent non-invasive monitoring of intracranial hydrodynamics to improve treatment outcome.  Responding to patient symptoms and ICP readings by adjusting treatment.  Controlling the flow of CSF through a valve of the shunting system.  Attempting to wean patient off the treatment (shunting system).  Wirelessly reprogramming the implanted shunting system.  Instant diagnosis of the shunting system and detection of any fault in the early stages. By having such system, the hospitalisation periods and patient suffering and inconvenience are reduced, the quality of treatment is improved and better understanding of intracranial hydrodynamics is established thanks to the valuable resource of ICP data. 1.4 Recent Advances In order to achieve such a system, a mechatronic valve is needed which is electrically controlled via software. In this shunting system, the patient could play a vital role in feeding back his/her dissatisfaction, i.e. due to symptoms, regarding the treatment. In 2005, Miethke claimed patent to a hydrocephalus valve with an electric actuating system comprising a time control system to open and close it (Miethke, 2005). The claim was that such valve would allow improved adaptation to the situation existing in a patient in the case of a hydrocephalus valve. The intervention of a mechatronic valve provides the opportunity for different shunting systems to be developed. This type of valve can be controlled by software that can vary in its complexity and intelligence. The controlling methods could vary from a simple program that lacks any intelligence to very sophisticated and intelligent program. Despite ICP monitoring currently being an invasive procedure, patients with hydrocephalus may need repeated episodes of monitoring months or years apart. This is a result of problems arising in which ICP readings are needed for diagnosis. The invasive nature of ICP monitoring has motivated researchers to develop a telemetric implantable pressure sensor for short- and long-term monitoring of ICP with high accuracy (Hodgins et al., 2008). Such sensor was mainly used for monitoring ICP wirelessly by the physician who could manually adjust the valve settings accordingly. The remainder of the chapter is structured as follows: Section 2 describes the intelligent and personalised shunting system, illustrates its novelty, and lists its functions. In Section 3, the advantages and limitations of the shunting system are identified. Section 4 summaries a quick walkthrough of the shunting system, while Sections 5 and 6 present the future directions and conclusions, respectively. IntelligentandPersonalisedHydrocephalusTreatmentandManagement 599 One of the obvious reasons for such drawbacks is the inability of such shunts to autonomously respond to the dynamic environment. Inaccuracies and long term drift are also considered among the drawbacks of such shunts. This is mainly due to the fact that these shunts are (typically, but not always) regulated according to the differential pressure across the valves, which differs from intracranial pressure in the brain. 1.3 Motivations Beside their documented drawbacks (Aschoff, 2001; Schley, 2004), shunts do not suit many hydrocephalus patients. This can be realised from the considerable high shunt revision and failure rates (between 30% and 40% of all shunts placed in paediatric patients fail within 1 year (Albright et al., 1988; Villavicencio et al., 2003; Piatt et al.,1993; Piatt,1995) and it is not uncommon for patients to have multiple shunt revisions within their lifetime). Shunt insertion explicitly changes the CSF dynamics in patients with hydrocephalus, causing many to improve clinically. However, the relationship between a changed hydrodynamic state and improved clinical performance is not fully known. Therefore, further research in this area is an important challenge for the hydrocephalus research community, where development of better methods for assessment of CSF dynamic parameters as well as studies to test hypotheses on relationships between CSF dynamics and outcome after shunting is targeted. The aims are for a better understanding of hydrocephalus pathophysiology and to find new predictive tests. Furthermore, the shunt designers had changed the shunt goal to have the option of re- establishing shunt independence step by step. This means that the statement of Hemmer “once a shunt, always a shunt” is no longer true. Nevertheless, most patients seem to be only partially shunt-dependent, i.e. their natural drainage system still functions to some extent. The degree of shunt-dependence may range from 1% to 100%, thus draining 30-50% of CSF production may be sufficient to keep the ICP within physiological ranges, and only a few need full drainage (Aschoff, 2001). Thus the current generation of shunts do not help patients overcome the underlying problems, but on the contrary, they tend to encourage the patients to become fully shunt dependent. Research has shown however, that in some cases, shunt dependence could be reduced to less than 1% (Aschoff, 2001) which could even allow the eventual removal of the shunt (Takahashi, 2001). It is envisaged that the next generation of shunts should be able to achieve a controlled shunt arrest in the long run. The future will bring other options related to the control of CSF production and absorption. Perhaps different valve designs will be more effective in long-term treatment and eventually the development of “smart” shunts. These will be able to react to intracranial physiology and will drain CSF in response to these changes in intracranial dynamics, rather than drain on a continuous basis (Jones & Klinge, 2008). To address the lack of personalised treatment, the difficulty in diagnosing shunt faults, the high rate of shunt revisions, the high shunt dependency, and the lack of full understanding of shunt effect on the intracranial hydrodynamics, a personalised hydrocephalus shunting system needs to be developed. This would be tasked with the following:  Frequent non-invasive monitoring of intracranial hydrodynamics to improve treatment outcome.  Responding to patient symptoms and ICP readings by adjusting treatment.  Controlling the flow of CSF through a valve of the shunting system.  Attempting to wean patient off the treatment (shunting system).  Wirelessly reprogramming the implanted shunting system.  Instant diagnosis of the shunting system and detection of any fault in the early stages. By having such system, the hospitalisation periods and patient suffering and inconvenience are reduced, the quality of treatment is improved and better understanding of intracranial hydrodynamics is established thanks to the valuable resource of ICP data. 1.4 Recent Advances In order to achieve such a system, a mechatronic valve is needed which is electrically controlled via software. In this shunting system, the patient could play a vital role in feeding back his/her dissatisfaction, i.e. due to symptoms, regarding the treatment. In 2005, Miethke claimed patent to a hydrocephalus valve with an electric actuating system comprising a time control system to open and close it (Miethke, 2005). The claim was that such valve would allow improved adaptation to the situation existing in a patient in the case of a hydrocephalus valve. The intervention of a mechatronic valve provides the opportunity for different shunting systems to be developed. This type of valve can be controlled by software that can vary in its complexity and intelligence. The controlling methods could vary from a simple program that lacks any intelligence to very sophisticated and intelligent program. Despite ICP monitoring currently being an invasive procedure, patients with hydrocephalus may need repeated episodes of monitoring months or years apart. This is a result of problems arising in which ICP readings are needed for diagnosis. The invasive nature of ICP monitoring has motivated researchers to develop a telemetric implantable pressure sensor for short- and long-term monitoring of ICP with high accuracy (Hodgins et al., 2008). Such sensor was mainly used for monitoring ICP wirelessly by the physician who could manually adjust the valve settings accordingly. The remainder of the chapter is structured as follows: Section 2 describes the intelligent and personalised shunting system, illustrates its novelty, and lists its functions. In Section 3, the advantages and limitations of the shunting system are identified. Section 4 summaries a quick walkthrough of the shunting system, while Sections 5 and 6 present the future directions and conclusions, respectively. BiomedicalEngineering600 2. Intelligent and Personalised Shunting System The new generation of shunting systems are expected to overcome the drawbacks and limitations of the current shunting systems. A novel intelligent telemetric system is developed for the improved management and treatment of hydrocephalus. The intelligent system would autonomously manage the CSF flow, personalise the management of CSF flow through involving real-time intracranial pressure readings and patient’s feedback, and responding to them. It also would autonomously manage and personalise the treatment of hydrocephalus, thus providing treatment that is personalised, goal-driven and reactive as well as pro-active, which gradually reduce shunt dependence and eventually establish a controlled arrest of the shunt. In addition, it would be able to monitor performance of its components, thus minimising the shunt revisions, and establish distant treatment database (e.g. computer-based patient record) and exchange treatment information, by regularly reporting the patient’s record to the physician. All these qualities can only be attained by a multi-agent approach (Momani, et al., 2008). This would also involve replacing a passive valve (commonly used in hydrocephalus shunts) with a mechatronic valve controlled by an intelligent microcontroller that wirelessly communicates with a separate smart hand-held device. The system is illustrated in Fig. 2. This shunting system would consist of two subsystems; implantable and external (patient device). The implanted subsystem would mainly consist of ultra low power commercial microcontroller, mechatronic valve, pressure sensor and low power transceiver. This implantable shunting system would wirelessly communicate with a hand-held smartphone operated by the patient, or on the patient’s behalf by a clinician or guardian. This device would have a graphical user interface and an RF interface to communicate with the user and the implantable wireless shunt respectively. This system would also enable a physician to monitor and modify the treatment parameters wirelessly, thus reducing, if not eliminating, the need for shunt revision operations. Once implanted, such a system could lead not only to better treatment of the users of such shunts, but also allow the dynamics of this disease and the effect of shunting to be understood in greater depth. An intelligent system, e.g. (Momani et al., 2008) , can be used to autonomously regulate the mechatronic valve according to a time-based schedule and update it based on the intracranial pressure that is measured when needed. In such system, ICP readings and other sensory inputs such as patient feedback would help in tuning the treatment and enabling the intervention of the medical practitioner to update and manually adapt the schedule. This would result in a personalised and intelligent CSF management, which leads to every patient having different management schedule according to his/her personal conditions. 2.1 Novelty The idea of using a pressure sensor integrated into a shunt system for monitoring ICP and interrogated by telemetry is not in itself a novel idea (Ginggen, 2007; Jeong et al., 2004; Miesel & Stylos, 2001), where ICP readings used by the physician to monitor the Fig. 2. Schematic diagram of the intelligent and personalised shunting system. performance of the implanted shunt. However, the novelty in this work is in having an implantable shunting system that utilise these readings in addition to patient input as a direct feedback to instantaneously and even autonomously manage the shunt, i.e. analyse the feedback, diagnose any shunt faults and accordingly regulate the opening of a mechatronic valve. Thus an element of intelligence and personalisation would be added to the mechatronic shunting system by enabling real-time reconfiguration of the shunt parameters based on the patient’s response and the ICP readings. 2.2 Strategy and Approach The mechatronic valve is controlled by a time based schedule. The schedule would be simply the distribution of the valve state (open/close) over time. Such schedule would incur many disadvantages e.g. over-/under-drainage, if its selection is arbitrary. In order to optimise the usefulness of such a valve, its schedule should be selected in way that delivers a personalised treatment for each specific patient. Achieving such a goal is not an easy task [...]... Stumbling Reactions in Man; Significance of Proprioceptive and Pre-programmed Mechanisms J Physiol 386:149 -163 626 Biomedical Engineering Hagane Y, Yu W, Katane T, Sekine M, Tamura T, Saitou O (2006) Detecting Perturbation Occurrence during Walking 11th ICPE, International Conference on Precision Engineering Kawamoto H., Kanbe S, Sankai Y (2003) Power AssistMethod for HAL-3 Estimating Operator's Intension... biological Engineering & Computing, Vol 37, 633638 Yamasaki T, Nomura T, Sato S (2003) Possible function roles of phase resetting during walking Biological Cybernetics, 88, 468-496 Yu W, Ikemoto Y (2007) An artificial reflex improves the perturbation-resistance of a human walking simulator Medical and Biological Engineering and Computing, Special Issue of World Congress on Medical Physics and Biomedical Engineering. .. sequence on the contralateral side for both That is, TA was activated first, followed by GN TA was activated at a latency of 65 ms; however, our TA latency was 116 ms This may have been due to differences in deceleration time; i.e., the 614 Biomedical Engineering treadmill could realize deceleration within 60 ms, whereas the deceleration time of the splitbelt walking machine was 100 ms 2.2 Simulation models... Central nerve Neural system input torque CPG model Musculoskeletal model sensory signal Sensory feedback module Normal Walker interaction Walking Fig 1 the composition of Normal Walker Environment 616 Biomedical Engineering Fig 2 The neuron-neuron and neuron-link connections Normal Walker with Reflex: Fig.3 shows the composition of this simulation model In order to realize the reflexive responses in the... Fuchs, H E & George, T M (2003) Comparison of Revision Rates Following Endoscopically Versus Nonendoscopically Placed Ventricular Shunt Catheters, Surgical Neurology, vol 59, no 5, pp 375-379 610 Biomedical Engineering A Simulation Study on Balance Maintenance Strategies during Walking 611 34 X A Simulation Study on Balance Maintenance Strategies during Walking Yu Ikemoto, Wenwei Yu and Jun Inoue Chiba... flexor reflex afferents could induce a clear resetting of the locomotion rhythm (Schomburg et al, 1998) However, it is almost impossible to test this hypothesis using the same methods in humans 612 Biomedical Engineering Thus, the spatio-temporal relation among neuro-control mechanisms, muscle activities and physical motions remains unknown Moreover, there is no widely accepted theory on the underlying... order to optimise the usefulness of such a valve, its schedule should be selected in way that delivers a personalised treatment for each specific patient Achieving such a goal is not an easy task 602 Biomedical Engineering due to the dynamic behaviour of intracranial pressure that not only varies among patients but also within individual patient with time There are two extremes for schedule alternatives... abnormality in ICP or not In the case of any abnormality, it will respond by either modifying the valve schedule to accommodate the symptom or alerting the physician in case of faults possibilities 604 Biomedical Engineering The availability of such option in the proposed shunting system, spares patient from unnecessary pain, suffering and risks accompanied with the current diagnosis method And on the contrary... the profiles should reflect the fundamental elements of human balance-recovery, also in order to make comparison under the similar condition, the same muscle activation profiles was applied 618 Biomedical Engineering 2.3 Evaluation Only the recovered/fell evaluation was unable to reflect the difference between the same “fell” or “recovered” cases With regard to quantitative evaluation, we used two... activation period 0.05s (c) Muscular reflexive activation period 0.09s Table 2 Balance recovery by CPG phase modulation and muscular reflexive patterns when slip perturbation duration changes 620 Biomedical Engineering (a) (b) Fig 5 Stick graphs of the Normal Walker and the Normal Walker with Reflex (arrows denote the slip period): (a) the Normal Walker fell down when a slip perturbation occurs; and . closer than ever. This chapter is concerned with the spreading of awareness, particularly among the biomedical engineering community e.g. organisations, companies, physicians and patients,. simultaneously optimizing repre- sentation and transformation. In: MICCAI 2007. (2007) 809–817 Biomedical Engineering5 94 Belongie, S., Malik, J., Puzicha, J.: Shape matching and object recognition. Biomedical Engineering5 92 (a) The center of one patch in S A,2 (b) Initialization of its correspondence assignment