Telemetric knee implants have provided invaluable insight into the forces occurring in the knee during various activities. However, due to the high amount of cost involved only a few of them have been developed. Mathematical modeling of the knee provides an alternative that can be easily applied to study high number of patients. However, in order to ensure accuracy these models need to be validated with in vivo force data. Previously, mathematical models have been developed and validated to study only specific activities. Therefore, the objective of this study was compare the knee force predictions from the same model with that obtained using telemetry for multiple activities. Kinematics of a telemetric patient was collected using fluoroscopy and 2D to 3D image registration for gait, deep knee bend (DKB), chair rise, step up and step down activities. Along with telemetric forces obtained from the implant, synchronized ground reaction forces (GRF) were also collected from a force plate. The relevant kinematics and the GRF were input into an inverse dynamic model of the human leg starting from the foot and ending at the pelvis (Figure 1). All major ligaments and muscles affecting the knee joint were included in the model. The pelvis and the foot were incorporated into the system so as to provide realistic boundary conditions at the hip and the ankle and also to provide reference geometry for the attachment sites of relevant muscles. The muscle redundancy problem was solved using the pseudo-inverse technique which has been shown to automatically optimize muscle forces based on the Crowninshield-Brand cost function. The same model, without any additional changes, was applied for all activities and the predicted knee force results were compared with the data obtained from telemetry. Comparison of the model predictions for the tibiofemoral contact forces with the telemetric implant data revealed a high degree of correlation both in the nature of variation of forces and the magnitudes of the forces obtained. Interestingly, the model predicted forces with a high level of accuracy for activities in which the flexion of the knee do not vary monotonically (increases and decreases or vice-versa) with the activity cycle (gait, step up and step down). During these activities, the difference between the model predictions with the telemetric data was less than 5% (Figure 2). For activities where flexion varies monotonically (either increases or decreases) with activity (DKB and chair rise) the difference between the forces was less than 10% (Figure 3). The results from this study show that inverse dynamic computational models of the knee can be robust enough to predict forces occurring at the knee with a high amount of accuracy for multiple activities. While this study was conducted only on one patient with a telemetric implant, the required inputs to the model are generic enough so that it is applicable for any TKA patient with the mobility to conduct the desired activity. This allows kinetic data to be provided for the improvement of implant design and surgical techniques accessibly and relatively inexpensively

Objectives. The monitoring of fracture healing is a complex process. Typically, successive radiographs are performed and an emerging calcification of the fracture area is evaluated. The aim of this study was to investigate whether different bone healing patterns can be distinguished using a telemetric instrumented femoral internal plate fixator. Materials and Methods. An electronic telemetric system was developed to assess bone healing mechanically. The system consists of a telemetry module which is applied to an internal locking plate fixator, an external reader device, a sensor for measuring externally applied load and a laptop computer with processing software. By correlation between externally applied load and load measured in the implant, the elasticity of the osteosynthesis is calculated. The elasticity decreases with ongoing consolidation of a fracture or nonunion and is an appropriate parameter for the course of bone healing. At our centre, clinical application has been performed in 56 patients suffering nonunion or fracture of the femur. Results. A total of 39 cases of clinical application were reviewed for this study. In total, four different types of healing curves were observed: fast healing; slow healing; plateau followed by healing; and non-healing. Conclusion. The electronically instrumented internal fixator proved to be valuable for the assessment of bone healing in difficult healing situations. Cost-effective manufacturing is possible because the used electronic components are derived from large-scale production. The incorporation of microelectronics into orthopaedic implants will be an important innovation in future clinical care. Cite this article: B. Kienast, B. Kowald, K. Seide, M. Aljudaibi, M. Faschingbauer, C. Juergens, J. Gille. An electronically instrumented internal fixator for the assessment of bone healing. Bone Joint Res 2016;5:191–197. DOI: 10.1302/2046-3758.55.2000611

Introduction: Rabbits are a well-established animal model for orthopaedic research. and the tibia is commonly used for investigations of fracture repair with different implant materials. Occurring forces in the animal model are of fundamental interest for the development of degradable bone implants to prevent implant failure. Therefore, a new method for the direct measurement of forces in the rabbit tibia was developed. The aim of this study was to determine maximal forces during weight bearing in the rabbit for future implementation into FEM-simulation. Animals and Methods: An external ring fixation was attached to the left tibiae of 5 rabbits and an ostectomy followed. Force sensors were included into the collateral rods to incur the emerging forces completely. On each side, a measurement amplifier was applied to transfer the collected data telemetrically. During the study, the animals were weighted and x-rays were taken regularly. Measurements started 8 days postoperatively and were repeated 8 times until day 50 post-op. The rabbits were placed in a run and animated to move while the forces were registered. Force peaks were filtered from the collected data of each measurement as absolute values and relative to the animals’ weight (force-weight ratio/FWR). Results: All included animals tolerated the external fixa-tion well and no clinical intolerances occurred. Beginning of callus formation was detected radiographically about 3 weeks post-op and all fixations could be removed 12–14 weeks after application without any permanent detriments. The maximal force amounted to 6950 g and 172 % FWR in animal 4 during the first recording. Means of the 5 maximal values for each measurement were located between 55 % FWR and 152 % FWR for the first measurement, converged to approx. 80 % FWR during the second recording 3 days later and descended to 20–40 % FWR until the end of the experiment. Discussion: Aim of this study was to determine maximal forces during weight bearing in a rabbit model. Our model for in-vivo monitoring of these forces was practicable and provided profound data. The highest values occurred during the first or second recording. That coincides with the radiographic detection of callus after 3 weeks. Therefore, reliable measurements have to be carried out during the first 2 weeks postoperatively. Detected values show that the rabbit tibia is strained with up to 170 % of the body weight, which is the compressive force an implant in a weight bearing bone has to be able to bear. Future research will focus on the in-vivo monitoring of bending and torsion forces and the implementation of these data into FEM-simulation

In an interdisciplinary project involving electronic engineers and clinicians, a telemetric system was developed to measure the bending load in a titanium internal femoral fixator. As this was a new device, the main question posed was: what clinically relevant information could be drawn from its application? As a first clinical investigation, 27 patients (24 men, three women) with a mean age of 38.4 years (19 to 66) with femoral nonunions were treated using the system. The mean duration of the nonunion was 15.4 months (5 to 69). The elasticity of the plate-callus system was measured telemetrically until union. Conventional radiographs and a CT scan at 12 weeks were performed routinely, and healing was staged according to the CT scans. All nonunions healed at a mean of 21.5 weeks (13 to 37). Well before any radiological signs of healing could be detected, a substantial decrease in elasticity was recorded. The relative elasticity decreased to 50% at a mean of 7.8 weeks (3.5 to 13) and to 10% at a mean of 19.3 weeks (4.5 to 37). At 12 weeks the mean relative elasticity was 28.1% (0% to 56%). The relative elasticity was significantly different between the different healing stages as determined by the CT scans. Incorporating load measuring electronics into implants is a promising option for the assessment of bone healing. Future application might lead to a reduction in the need for exposure to ionising radiation to monitor fracture healing

Introduction. Current methodologies for designing and validating existing THA systems can be expensive and time-consuming. A validated mathematical model provides an alternative solution with immediate predictions of contact mechanics and an understanding of potential adverse effects. The objective of this study is to demonstrate the value of a validated forward solution mathematical model of the hip that can offer kinematic results similar to fluoroscopy and forces similar to telemetric implants. Methods. This model is a forward solution dynamic model of the hip that incorporates the muscles at the hip, the hip capsule, and the ability to modify implant position, orientation, and surgical technique. Muscle forces are simulated to drive the motion, and a unique contact detection algorithm allows for virtual implantation of components in any orientation. Patient-specific data was input into the model for a telemetric subject and for a fluoroscopic subject. Results. For both stance and swing phase, the model predicted similar patterns and magnitudes compared to telemetry (forces) and fluoroscopy (kinematics). During stance phase, the model predicts 2.5 xBW of maximum hip force while telemetry predicts 2.3 xBW, yielding 8.7% error (Figure 1a). During swing phase, the model predicts 1.1 xBW maximum hip force, similar to telemetry (Figure 1b). During stance phase, the model predicts 1.3mm of hip separation (sliding) compared to 1.6mm for fluoroscopy, yielding 18.8% error (Figure 1c). During swing phase, the model predicts 1.9mm of separation compared to 1.7mm for fluoroscopy, yielding 11.8% error (Figure 1d). The model was also used to assess component placement, version, and optimal positioning compared to live surgery, producing very promising results. Conclusion. The model has proven accurate in predicting kinematics and forces. Therefore, forward solution mathematical modeling can be used to efficiently evaluate new component designs, positioning and technique differences, patient-specific scenarios, and any specific contribution towards THA outcomes that cannot be controlled in vivo. For any figures or tables, please contact the authors directly

Introduction. While fluoroscopic techniques have been widely utilized to study in vivo kinematic behavior of total knee arthroplasties, determination of the contact forces of large population sizes has proven a challenge to the biomedical engineering community. This investigation utilizes computational modeling to predict these forces and validates these with independent telemetric data for multiple patients, implants, and activities. Methods. Two patients with telemetric implants, the first of which was studied twice with the reexamination occurring 8 years after the first, were studied. Three-dimensional models of the patients' bones were segmented from CT and aligned with the design models of the telemetric implants. Fluoroscopy was collected for gait, deep knee bend, chair rise, and stair activities while being synchronized to the ground reaction force (GRF) plate, telemetric forces, knee flexion angles, electromyography (EMG), and vibration sensors. Registration of the implants and bones to the 2-D fluoroscopy provided the 6 degree of freedom kinematic data for each object. Orientation and position of the components, the GRFs, ligament properties, and muscle attachment locations were the only inputs to the Kane's dynamics inverse solution. Dynamic contact mapping and pseudo-inverse solution method were incorporated to output the predicted muscle forces of the vastus lateralis, rectus femoris, vastus medialis, biceps femoris long head, and gastrocnemius and contact forces at the patellofemoral and medial and lateral tibiofemoral. While every major muscle of the lower limb was incorporated into the model, these five were used in the validation process. EMG signals were processed to determine the neural excitation, muscle activation, and using the dynamic muscle length from the kinematics, the tension generated by these muscles. Results. Comparison of the model predictions for the tibiofemoral contact forces with the telemetric implant data resulted in an error <10% for all patients and activities. Predicted muscle forces were <15% error from the EMG calculated forces. Discussion. An inverse computational model of the knee robust enough to encompass multiple patients and activities was successfully created and validated. The accuracy of the muscle forces demonstrates that the model correctly simulates anatomical motion and not just transferal of GRFs. While this study was conducted on patients with telemetric implants, the required inputs to the model can be obtained from any TKA patient with the mobility to conduct the desired activity. This allows not only kinematic data, but also kinetics, to be provided for the improvement of implant design and surgical techniques accessibly and relatively inexpensively

Nonunions occur in situations with interrupted fracture healing process and indicate conditions where the fracture has no potential to heal without further intervention. Per definition, no healing is detected nine months post operation and there is no visible progress of healing over the last three months. The classification of nonunions as hypertrophic, oligotrophic, atrophic and pseudoarthosis, as well as aseptic or septic, identifies mechanical and biological requirements for fracture healing that have not been met. The overall treatment strategy comprises identification and elimination of the problems. However, current clinical methods to determine the state of healing are based on highly subjective radiographic evaluation or clinical examination. A data collection telemetric system for objective continuous measurement of the load carried by a bridging smart implant was developed to assess the mechanical stability and monitor bone healing in complicated fracture situations. The first results from a clinical trial show that the system is capable to offer early warning of nonunions or poor fracture healing. Nonunions are often multifactorial in nature and not just related to a biomechanical problem. Their successful treatment requires consideration of both biological and mechanical aspects. Disturbed vascularity and stability are the most important factors. Infection could be another complicating factor resulting in unpredictable long-time treatment. New technologies for monitoring of fracture healing in addition to radiographic evaluation and clinical examination seem to be promising for early detection of nonunions

Introduction:. There is substantial range in kinematics and joint loading in the total knee arthroplasty (TKA) patient population. Prospective TKA designs should be evaluated across the spectrum of loading conditions observed in vivo. Recent research has implanted telemetric tibial trays into TKA patients and measured loads at the tibiofemoral (TF) joint [1]. However, the number of patients for which telemetric data is available is limited and restricts the variability in loading conditions to a small subset of those which may be encountered in vivo. However, there is a substantial amount of fluoroscopic data available from numerous TKA patients and component designs [2]. The purpose of this study was to develop computational simulations which incorporate population-based variability in loading conditions derived from in vivo fluoroscopy, for eventual use in computational as well as experimental activity models. Methods:. Fluoroscopic kinematic data was obtained during squat for several patients with fixed bearing and rotating platform (RP) components. Anterior-posterior (A-P) and internal-external (I-E) motions of the TF joint were extracted from full extension to maximum flexion. Joint compressive loading was estimated using an inverse-dynamics approach. Previously-developed computational models of the knee, lower limb, and Kansas knee simulator were virtually implanted with the same design as the fluoroscopy patients. A control system was integrated with the computational models such that external loading at the hip and ankle were determined in order to reproduce the measured in vivo motions and compressive load (Fig. 1). Accuracy of the model in matching the in vivo motions was assessed, in addition to the resulting joint A-P and I-E loading. The external loading determined for a broader range of patients can subsequently be utilized in a force-controlled simulation to assess the robustness of implant concepts to patient loading variability. The applicability of this work as a comparative tool was illustrated by assessing the kinematics of two PS RP designs under three patient-specific loading conditions. Results:. External hip and ankle loading conditions were determined for each computational model that reproduced in vivo A-P, I-E and flexion-extension joint motions and estimated compressive load. For example, RMS accuracy of 0.4 mm, 0.2° and 0.7° were achieved for A-P, I-E and flexion, respectively (Fig. 1, 2). There was good agreement in both trend and magnitude of joint loads predicted from the externally-loaded models compared to telemetric measurements. Comparative analysis of two designs under multiple loading conditions illustrated variability in joint mechanics as a result of design factors and variation between subjects for the same design (Fig. 3). Discussion:. Pre-clinical evaluation of new devices under physiological joint loading conditions is crucial to robust functionality across the TKA population. The loads applied to a TKA system will affect fixation, wear, and functional performance. Harnessing in vivo kinematic data to develop population-based loading profiles will facilitate development of a platform for comprehensive design-phase evaluation of prospective designs. In addition, loading conditions for experimental simulators can be developed in order to test new devices under the range of variability likely to be encountered in vivo

PROBLEM. Since the COVID-19 pandemic of 2020, there has been a marked rise in the use of telemedicine to evaluate patients following total knee arthroplasty (TKA). Telemedicine is helpful to maintain patient contact, but it cannot provide objective functional TKA data. External monitoring devices can be used, but in the past have had mixed results due to patient compliance and data continuity, particularly for monitoring over numerous years. This novel stem is a translational product with an embedded sensor that can remotely monitor patient activity following TKA. SOLUTION. The Canturio™ TE∗ System (Canary Medical) functions structurally as a tibial extension for the Persona® cemented tibial plate (Zimmer Biomet). The stem is instrumented with internal motion sensors (3-D accelerometer and gyroscope) and telemetry that collects and transmits kinematic data. Raw data is converted by analytics into clinically relevant gait metrics using a proprietary algorithm. The Canturio™ TE∗ will monitor the patient's gait daily for the first year and then with lower frequency thereafter to conserve battery power enabling the potential for 20 years of longitudinal data collection and analysis. A base station in the OR activates the device and links the stem and data to the patient. A base station in the patient's home collects and uploads data to the Cloud Based Canary Data Management Platform (Canary Medical). The Canary Cloud is structured as an FDA regulated and HIPPA-compliant database with cybersecurity protocols integrated into the architecture. A third base station is an accessory used in the health care professional's office to perform an on-demand gait analysis of a patient. A dashboard allows the health care professional and patient to monitor objective data of the patient's activity and progress post treatment. MARKET. The early target market for this device includes total joint surgeons who are early adopters of technology and currently utilize technology in their practice. The kinematic data provided by the Canturio™ TE∗ System will enable clinicians to augment patient care by reviewing their objective gait metrics. In the future, this data has the potential to be integrated with other Zimmer Biomet technologies, such as the Rosa™ Knee robotic platform, mymobility™, and sensored devices like iAssist™, to provide the surgeon with a complete pre-surgical functional assessment, intraoperative data, and post-operative functional data. PRODUCT. Persona IQ will be the combination of the proven Persona personalized total knee system with the Canary Medical Canturio™ TE∗. TIMING AND FUNDING. The Canturio™ TE is currently under De Novo FDA review for market clearance; it is not yet available for commercial distribution. The plan is to launch the product in 2021 pending regulatory De Novo grant. This effort is a partnership between Zimmer Biomet and Canary Medical. ∗ The Canturio™ - TE is currently under De Novo FDA review for market clearance; it is not yet available for commercial distribution

Purpose of the study: It has been demonstrated that navigation systems improve the quality of implantation of total knee arthroplasty (TKA). The definitions of the reference alignment for the femur are not however consensual. We wanted to define the different alignments of the femur on the lateral view, including the femoral head and comparing the alignments with those defined by the measured axes during navigated implantation. Material and methods: We analysed 30 navigated TKA or unicompartmental prosthesis implantations. The following lines were drawn on the pre and postoperative lateral telemetric views: anatomic axis aligned on the anterior cortical of the femur, mechanical alignment n°1 (centre of the femoral head to the most distal point of the Blumensaat line), mechanical alignment n°2 (centre of the femoral head to the junction between the anterior two-thirds and the posterior third of the femoral condyles). The anatomic diaphyseal alignment was taken as the reference and the angles between this reference line and the other lines was measure. In addition, the sagittal orientation of the femoral component measured during the operation by the navigation system in relation to the n°2 mechanical alignment was noted; this orientation was also measured on the postoperative lateral telemetric views in relation to this same mechanical alignment. Results: The mean difference between the anatomic cortical alignment and the reference was 0.3 (−1 to +). The mean difference between the n°1 mechanical alignment and the reference was −1.1 (−5 to +3). The mean difference between the mechanical alignment n°2 and the reference was 0.8 (−4 to 4). The mean intraoperative sagittal orientation of the femoral component was 0.0 (−2 to 2). The mean postoperative sagittal orientation of the femoral component was 1.1 (−4 to 6). Discussion: The differences between the orientations of the different sagittal alignments of the femur were minimal. The cortical axis has a smaller variance and could be considered as the most reliable reference, but this alignment does not include the femoral anteversion. The difference between the sagittal orientation of the femoral component as measured by the navigation system and as measured on the postoperative x-rays was also minimal, and probably of no significance clinically. Conclusion: The choice of the sagittal alignment of the femur is of little importance. The intraoperative navigated measurement of the sagittal orientation of the femoral component is reliable

Introduction. Previous research defines the existence of a “safe zone” (SZ) pertaining to acetabular cup implantation during total hip arthroplasty (THA). It is believed that if the cup is implanted at 40°±10° inclination and 15°±10° anteversion, risk of dislocation is reduced. However, recent studies have documented that even when the acetabular cup is placed within the SZ, high incidence dislocation and instability remains due to the combination of patient-specific configuration, cup diameter, head size, and surgical approach. The SZ only investigates the angular orientation of the cup, ignoring translational location. Translational location of the cup can cause a mismatch between anatomical hip center and implanted cup center, which has not been widely explored. Objective. The objective of this study is to define a zone within which the implanted joint center can be altered with respect to the anatomical joint center but will not increase the likelihood of post-operative hip separation or dislocation. Methods. A theoretical forward solution hip model, previously validated by telemetric devices and fluoroscopy data of existing implants, was used for analysis. The model allows for modifications of implant geometries/placement and soft tissue resection to simulate various surgical conditions. For the baseline simulation, the cup center was matched to the anatomical hip joint center, calculated as the center of the best fit sphere mapping the acetabulum, and the orientation of the cup was 40°/15° (inclination/anteversion). Keeping cup orientation the same, the location of the cup was moved in 1 mm increments in all directions to identify the region where a mismatch between the two centers did not lead to separation or instability in the joint. Results. During both swing and stance phase, when the acetabular cup was placed within the optimal conic with a slant height of 5±1 mm, no hip instability or dislocation risk occurred. As the acetabular cup was translated to the boundary of the optimal conic, hip instability increased. When the acetabular cup was placed at the boundary of the optimal conic, up to 2 mm of hip separation in the lateral direction occurred during swing phase, resulting in a decrease in contact area and an increase in contact stress. As the cup was placed outside the optimal conic, severe edge loading and hip separation up to 3.5 mm occurred during swing phase. In general, this resulted in large increases in cup stress, resulting in increased risk of wear leading to early complications. Discussion. This study introduces the concept of an optimal conic in the hip joint space to reduce the incidence of dislocation and hip instability after THA. Placing the cup center within the optimal conic reduces hip instability. Moving the cup further from the anatomical hip center increases the occurrence of hip instability. Cup placement within the optimal conic and angular SZ can lead to better postoperative outcomes. For any figures or tables, please contact authors directly

Introduction. Aseptic loosening is one of the highest causes for revision in total knee arthroplasty (TKA). With growing interest in anatomically aligned (AA) TKA, it is important to understand if this surgical technique affects cemented tibial fixation any differently than mechanical alignment (MA). Previous studies have shown that lipid/marrow infiltration (LMI) during implantation may significantly reduce fixation of tibial implants to bone analogs [1]. This study aims to investigate the effect of surgical alignment on fixation failure load after physiological loading. Methods. Alignment specific physiological loading was determined using telemetric tibial implant data from Orthoload [2] and applying it to a validated finite element lower limb model developed by the University of Denver [3]. Two high demand activities were selected for the loading section of this study: step down (SD) and deep knee bend (DKB). Using the lower limb model, hip and ankle external boundary conditions were applied to the ATTUNE. ®. knee system for both MA and AA techniques. The 6 degree of freedom kinetics and kinematics for each activity were then extracted from the model for each alignment type. Mechanical alignment (MA) was considered to be neutral alignment (0° Hip Knee Ankle Angle (HKA), 0° Joint Line (JL)) and AA was chosen to be 3° varus HKA, 5° JL. It is important not to exceed the limits of safety when using AA as such it is noted that DePuy Synthes recommends staying within 3º varus HKA and 3º JL. The use of 5º JL was used in this study to account for surgical variation [Depuy-Synthes surgical technique DSUS/JRC/0617/2179]. Following a similar method described by Maag et al [1] ATTUNE tibial implants were cemented into a bone analog with 2 mL of bone marrow in the distal cavity and an additional reservoir of lipid adjacent to the posterior edge of the implant. Tibial implant constructs were then subjected to intra-operative ROM/stability evaluation, followed by a hyperextension activity until 15 minutes of cement curing time, and finally 3 additional ROM/stability evaluations were performed using an AMTI VIVO simulator. The alignment specific loading parameters were then applied to the tibial implants using an AMTI VIVO simulator. Each sample was subjected to 50,000 DKB cycles and 120,000 SD cycles at 0.8 Hz in series; approximating 2 years of physiological activity. After physiological loading the samples were tested for fixation failure load by axial pull off. Results. Following alignment specific physiological loading the average fixation pull-off load for MA was 3289 ± 400 N and for AA was 3378 ± 133 N (Figure 1). There was no statistically significant difference fixation failure load by axial pull-off between the two alignment types (p=0.740). Conclusion. This study indicated that anatomic alignment, as defined with the alignment limits of this study, does not adversely affect the fixation failure load of ATTUNE tibial implants. For any figures or tables, please contact the authors directly

Introduction. Infections affect 1–3% of Total Knee Arthroplasty (TKA) patients with severe ramifications to mobility. Unfortunately, reinfection rates are high (∼15%) suggesting improved diagnostics are required. A common strategy to treat TKA infection in North America is the two-stage revision procedure involving the installation of a temporary spacer in the joint while the infection is treated for 6–12 weeks before permanent revision. Subdermal temperature increases during infection by 1–4°C providing a potential indicator for when the infection has been cleared. We propose an implantable temperature sensor integrated into a tibial spacer for telemetric use. We hypothesized that suitable sensing performance for infection monitoring regarding precision and relative accuracy can be attained using a low power, compact, analog sensor with <0.1ºC resolution. Materials & Methods. An experimental sensor was selected for our implanted application due to its extremely low (9 μA) current draw and compact chip package. Based upon dynamic range it was determined that the analog/digital converter must be a minimum of 11 bits to deliver suitable (<0.1ºC) resolution. A 12-bit ADC equipped microcontroller was selected. The MCP9808 (Microchip Technology, Chandler, AZ, USA) delivers manufacturer characterized thermal data in decimal strings through serial communication to the same microcontroller. The rated accuracy of the MCP9808 sensors in the required temperature range is max/typ +/− 0.5/0.25ºC with a precision of +/− 0.05ºC delivered at a resolution of 0.0625ºC. Within a thermally insulated chamber with a resistive heating element, the following experiment was conducted: Using empirical plant modelling tools, simulation and implementation an effective PI control scheme was implemented to create a highly precise temperature chamber. With MCP9808 as reference, the temperature in the thermal chamber was driven to 20 different temperatures between 35 and 40ºC for 10 minutes each and sampled at 5 Hz. This trial was repeated three times over three days. Transient data was discarded so as only to evaluate the steady state characteristics, wavelet denoising was applied, and a regression between the reference MCP9808 temperature response vs the experimental sensor intended for implantation was tabulated in Matlab. Results. Compared to reference values, the experimental temperature sensor displayed relative accuracy of +/− 0.275ºC (with 95% confidence) and precision of +/−0.135ºC over a 35–40ºC range as determined over 190,212 relevant samples. Note that in practice, the precision is independent of reference, but the absolute accuracy is relative to the gold standard's accuracy. Conclusion. Infection frequently results in permanent mobility issues in the context of total knee arthroplasty. This has led to an ongoing call for better treatments. Analysis suggests that the proposed experimental sensor offers high precision and reasonable relative accuracy in temperature sensing, substantially tighter than the expected stimulus from infection, while also offering desirable characteristics for implantation. This sensing platform will be integrated into an instrumented tibial spacer in future work. For any figures or tables, please contact authors directly

Summary. The mathematical model has proven to be highly accurate in measuring leg length before and after surgery to determine how leg length effects hip joint mechanics. Introduction. Leg length discrepancy (LLD) has been proven to be one of the most concerning problems associated with total hip arthroplasty (THA). Long-term follow-up studies have documented the presence of LLD having direct correlation with patient dissatisfaction, dislocation, back pain, and early complications. Several researchers sought to minimize limb length discrepancy based on pre-operative radiological templating or intra-operative measurements. While often being a common occurrence in clinical practice to compensate for LLD intra-operatively, the center of rotation of the hip joint has often changes unintentionally due to excessive reaming. Therefore, the clinical importance of LLD is still difficult to solve and remains a concern for clinicians. Objective. The objective of this study is two-fold: (1) use a validated forward-solution hip model to theoretically analyze the effects of LLD, gaining better understanding of mechanisms leading to early complication of THA and poor patient satisfaction and (2) to investigate the effect of the altered center of rotation of the hip joint regardless LLD compensation. Methods. The theoretical mathematical model used in this study has been previously validated using fluoroscopic results from existing implant designs and telemetric devices. The model can be used to theoretically investigate various surgical alignments, approaches, and procedures. In this study, we analyzed LLD and the effects of the altered center of rotation regardless of LLD compensation surgeons made. The simulations were conducted in both swing and stance phase of gait. Results. During swing phase, leg shortening lead to loosening of the hip capsular ligaments and subsequently, variable kinematic patterns. The momentum of the lower leg increased to levels where the ligaments could not properly constrain the hip leading to the femoral head sliding from within the acetabular cup (Figure 1). This piston motion led to decreased contact area and increased contact stress within the cup. Leg lengthening did not yield femoral head sliding but increased joint tension and contact stress. A tight hip may be an influential factor leading to back pain and poor patient satisfaction. During stance phase, leg shortening caused femoral head sliding leading to decreased contact area and an increase in contact stress. Leg lengthening caused an increase in capsular ligaments tension leading to higher stress in the hip joint (Figure 2). Interestingly, when the acetabular cup was superiorized and the surgeon compensated for LLD, thus matching the pre-operative leg length by increasing the neck length of the femoral implant, the contact forces and stresses were marginally increased at heel strike (Figure 3). Conclusion and Discussion. Altering the leg length during surgery can lead to higher contact forces and contact stresses due to tightening the hip joint or increasing likelihood of hip joint separation. Leg shortening often lead to higher stress within the joint. Further assessment must be conducted to develop tools that surgeons can use to ensure post-operative leg length is similar to the pre-operative condition. For any figures or tables, please contact authors directly

Currently, hip implant designs are evaluated experimentally using mechanical simulators or cadavers, and total hip arthroplasty (THA) postoperative outcomes are evaluated clinically using long-term follow-up. However, these evaluation techniques can be both costly and time-consuming. Neither can provide an assessment of post-operative results at the onset of implant development. More recently, a forward-solution mathematical model was developed that functions as theoretical joint simulator, providing instant feedback to designers and surgeons alike. This model has been validated by comparing the model predictions with kinematic results from fluoroscopy for both implanted and non-implanted hips and kinetics from a telemetric hip. The model allows surgical technique modifications and implant component placement under in vivo conditions. The objective of this study was to further expand the capabilities of the model to function as an intraoperative virtual surgical tool (Figure 1). This new module allows the surgeon to simulate surgery, then predict, compare, and optimize postoperative THA outcomes based on component placement, sizing choices, reaming and cutting locations, and surgical methods. This virtual surgery tool simulates the quadriceps, hamstring, gluteus, iliopsoas, tensor fasciae latae, and an adductor muscle groups, as well as the hip capsular ligament groups. The model can simulate resecting, weakening, loosening, or tightening of soft tissues based on surgical techniques. Additionally, the model can analyze a variety of activities, including gait and deep flexion activities. Initially, the virtual surgery module offers theoretical surgery tools that allow surgeons to alter surgical alignments, component designs, offsets, as well as reaming and cutting simulations. The virtual model incorporates a built-in CT scan bone database which will assist in determining muscle and ligament attachment sites as well as bony landmarks. The virtual model can be used to assist in the placement of both the femoral component and the acetabular cup (Figure 2). Moreover, once the surgeon has decided on the placements of the components, they can use the simulation capabilities to run virtual human body maneuvers based on the chosen parameters. The simulations will reveal force, contact stress, and motion predictions of the hip joint (Figure 3). The surgeon can then choose to modify the positions accordingly or proceed with the surgery. This new virtual surgical tool will allow surgeons to gain a better understanding of possible post-operative outcomes under pre-operative conditions or intra-operatively. Simulations using the virtual surgery model has revealed that improper component placement may lead to non-ideal post-operative function, which has been simulated using the model. Further evaluation is ongoing so that this new module can reveal more information pre-operatively, allowing a surgeon to gain ample information before surgery, especially with difficult and revision cases

Introduction: Understanding the forces across the human lower extremity joint is of considerable interest to the clinician. In the past, telemetric hip implants have been used to determine the forces across the hip joint, but the forces at the knee joint remain unvalidated. Recently, video fluoroscopy has been utilized to accurately determine the in vivo kinematics of human joints during various activities. The objective of this study was to predict muscle and joint forces from a mathematical model utilizing fluoroscopy as the input motion data. Methods: Initially, two subjects (one with a total knee and a second with a total hip arthroplasty) were asked to perform normal gait and a deep knee bend while under fluoroscopic surveillance. A fully automated computer model-fitting algorithm was employed to convert the two dimensional (2D) fluoroscopic videos to 3D, and the in vivo motion of the implanted joint was determined. The kinematic data then served as input to a mathematical model in which the relative motions of the segments and the interaction forces between the foot and the ground were also treated as input data. The predicted forces for the implanted joint, quadriceps muscles and patellar ligament were plotted with respect to time, percent gait cycle and knee flexion angle. Results: The resultant force at the implanted knee joint ranged from 2.0 to 3.5 times body weight (BS) during gait, depending on walking speed and walking motion. A forward leaning pattern resulted in significantly higher knee joint forces. During a deep knee bend, the knee joint forces could rise as high as 3.5 BW. The resultant forces at the implanted hip joint ranged from 2.0 to 4.0 BW, depending on the activity (greater during deep knee bend), walking speed, walking motion and the incidence of hip separation. The patellofemoral forces were minimal during walking (< 0.5 BW), but increased significantly with greater knee flexion to a maximum of 3.5 BW. The quadriceps muscle and patellar ligament forces were similar during gait (1.0 BW), but the quadriceps force was 40% greater in deep knee flexion. Discussion: The present study has determined that the predicted hip joint forces are similar to telemetrically derived joint forces at the hip joint. Both knee, hip and muscle forces were greater in deep flexion compared to gait. A sensitivity analysis determined that the model is extremely sensitive to patellar ligament and patella motion. Altering the kinematics of the patella and patellar ligament could increase the knee joint forces by 1.0 BW

During the preoperative examination, surgeons determine whether a patient, with a degenerative hip, is a candidate for total hip arthroplasty (THA). Although research studies have been conducted to investigate in vivo kinematics of degenerative hips using fluoroscopy, surgeons do not have assessment tools they can use in their practice to further understand patient assessment. Ideally, if a surgeon could have a theoretical tool that efficiently allows for predictive post-operative assessment after virtual surgery and implantation, they would have a better understanding of joint conditions before surgery. The objectives of this study were (1) to use a validated forward solution hip model to theoretically predict the in vivo kinematics of degenerative hip joints, gaining a better understanding joint conditions leading to THA and (2) compare the predicted kinematic patterns with those derived using fluoroscopy for each subject. A theoretical model, previously evaluated using THA kinematics and telemetry, was used for this study, incorporating numerous muscles and ligaments, including the quadriceps, hamstring, gluteus, iliopsoas, tensor fasciae latae, an adductor muscle groups, and hip capsular ligaments. Ten subjects having a pre-operative degenerative hip were asked to perform gait while under surveillance using a mobile fluoroscopy unit. The hip joint kinematics for ten subjects were initially assessed using in vivo fluoroscopy, and then compared to the predicted kinematics determined using the model. Further evaluations were then conducted varying implanted component position to assess variability. The fluoroscopic evaluation revealed that 33% of the degenerative hips experienced abnormal hip kinematics known as “hip separation” where the femoral head slides within the acetabulum, resulting in a decrease in contact area. Interestingly, the mathematical model produced similar kinematic profiles, where the femoral head was sliding within the acetabulum (Figure 1). During swing phase, it was determined that this femoral head sliding (FHS) is caused by hip capsular laxity resulting in reducing joint tension. At the point of maximum velocity of the foot, the momentum of the lower leg becomes too great for capsule to properly constrain the hip, leading to the femoral component pistoning outwards. During stance phase, kinematics of degenerative hips were similar to kinematics of a THA subject with mal-positioning of the acetabular cup. Further evaluation revealed that if the cup was placed at a position other than its native, anatomical center, abnormal forces and torques acting within the joint lead to the femoral component sliding within the acetabular cup. It was hypothesized that in degenerative hips, similar to THA, the altered center of rotation is a leading influence of FHS (Figure 2). The theoretical model has now been validated for subjects having a THA and degenerative subjects. The model has successfully derived kinematic patterns similar to subjects evaluated using fluoroscopy. The results in this study revealed that altering the native joint center is the most influential factor leading to FHS, or more commonly known as hip separation. A new module for the mathematical model is being implemented to simulate virtual surgery so that the surgery can pre- operatively plan and then simulate post-operative results

Introduction. Aseptic loosening of total knee replacements is a leading cause for revision. It is known that micromotion has an influence on the loosening of cemented implants though it is not yet well understood what the effect of repeated physiological loading has on the micromotion between implants and cement mantle. This study aims to investigate effect of physiological loading on the stability of tibial implants previously subjected to simulated intra-operative lipid/marrow infiltration. Methods. Three commercially available fixed bearing tibial implant designs were investigated in this study: ATTUNE. ®. , PFC SIGMA. ®. CoCr, ATTUNE. ®. S+. The implant designs were first prepared using a LMI implantation process. Following the method described by Maag et al tibial implants were cemented in a bone analog with 2 mL of bone marrow in the distal cavity and an additional reservoir of lipid adjacent to the posterior edge of the implant. The samples were subjected to intra- operative range of motion (ROM)/stability evaluation using an AMTI VIVO simulator, then a hyperextension activity until 15 minutes of cement cure time, and finally 3 additional ROM/stability evaluations were performed. Implant specific physiological loading was determined using telemetric tibial implant data from Orthoload and applying it to a validated FE lower limb model developed by the University of Denver. Two high demand activities were selected for the loading section of this study: step down (SD) and deep knee bend (DKB). Using the above model, 6 degree of freedom kinetics and kinematics for each activity was determined for each posterior stabilized implant design. Prior to loading, the 3-D motion between tibial implant and bone analog (micromotion) was measured using an ARAMIS Digital Image Correlation (DIC) system. Measurement was taken during the simulated DKB at 0.25Hz using an AMTI VIVO simulator while the DIC system captured images at a frame rate of 10Hz. The GOM software calculated the distance between reference point markers applied to the posterior implant and foam bone. A Matlab program calculated maximum micromotion within each DKB cycle and averaged that value across five cycles. The implant specific loading parameters were then applied to the three tibial implant designs. Using an AMTI VIVO simulator each sample was subjected to 50,000 DKB and 120,000 SD cycles at 0.8Hz in series; equating to approximately 2 years of physiological activity. Following loading, micromotion was measured using the same method as above. Results. Initial micomotion measurements during DKB activity for ATTUNE. ®. , PFC SIGMA. ®. CoCr, ATTUNE. ®. S+ were 155µm, 246µm, and 104µm, respectively, and following physiological loading were 159µm, 264µm, and 112µm, respectively. While there was statistical significance between the micromotion of implant designs (p<0.05), there was no significance between before and after loading. Conclusion. This study shows there is no significant change in micromotion after approximately 2 years of physiological loading. However, there is a significant difference in micromotion between implant designs

Background. In vivo fluoroscopic studies have proven that femoral head sliding and separation from within the acetabular cup during gait frequently occur for subjects implanted with a total hip arthroplasty. It is hypothesized that these atypical kinematic patterns are due to component malalignments that yield uncharacteristically higher forces on the hip joint that are not present in the native hip. This in vivo joint instability can lead to edge loading, increased stresses, and premature wear on the acetabular component. Objective. The objective of this study was to use forward solution mathematical modeling to theoretically analyze the causes and effects of hip joint instability and edge loading during both swing and stance phase of gait. Methods. The model used for this study simulates the quadriceps muscles, hamstring muscles, gluteus muscles, iliopsoas group, tensor fasciae latae, and an adductor muscle group. Other soft tissues include the patellar ligament and the ischiofemoral, iliofemoral, and pubofemoral hip capsular ligaments. The model was previously validated using telemetric implants and fluoroscopic results from existing implant designs. The model was used to simulate theoretical surgeries where various surgical alignments were implemented and to determine the hip joint stability. Parameters of interest in this study are joint instability and femoral head sliding within the acetabular cup, along with contact area, contact forces, contact stresses, and ligament tension. Results. During swing phase, it was determined that femoral head pistoning is caused by hip capsule laxity resulting from improperly positioned components and reduced joint tension. At the point of maximum velocity of the foot (approximately halfway through), the momentum of the lower leg becomes too great for a lax capsule to properly constrain the hip, leading to the femoral component pistoning outwards. This pistoning motion, leading to separation, is coupled with a decrease in contact area and an impulse-like spike in contact stress (Figure 1). During stance phase, it was determined that femoral head sliding within the acetabular cup is caused by the proprioceptive notion that the human hip wants to rotate about its native, anatomical center. Thus, component shifting yields abnormal forces and torques on the joint, leading to the femoral component sliding within the cup. This phenomenon of sliding yields acetabular edge-loading on the supero-lateral aspect of the cup (Figure 2). It is also clear that joint sliding yields a decreased contact area, in this case over half of the stable contact area, corresponding to a predicted increase in contact stress, in this case over double (Figure 2). Discussion. From our current analysis, the causes and effects of hip joint instability are clearly demonstrated. The increased stress that accompanies the pistoning/impulse loading scenarios during swing phase and the supero-lateral edge-loading scenarios during stance phase provide clear explanations for premature component wear on the cup, and thus the importance of proper alignment of the THA components is essential for a maximum THA lifetime. For any figures or tables, please contact authors directly

Background. Extensive research has previously been conducted analyzing the biomechanical effects of rotational changes (i.e. version and inclination) of the acetabular cup. Many sources, citing diverse dislocation statistics, encourage surgeons to strive for various “safe zones” during the THA operation. However, minimal research has been conducted, especially under in vivo conditions, to assess the consequences of cup translational shifting (i.e. offsets, medial and superior reaming, etc.). While it is often the practice to medialize the acetabular cup intraoperatively, there is still a lack of information regarding the biomechanical consequences of such cup medializations and medial/superior malpositionings. Objective. Therefore, the objective of this study is to use a validated forward solution mathematical model to vary cup positioning in both the medial and superior directions to assess simulated in vivo kinematics. Methods. The model used for this study has been validated with telemetric data and incorporates numerous muscles and ligaments. The model is parametrically derived and allows the user to simulate a theoretical THA surgery and to assess the outcomes of proper positioning as well as malpositioning of the cup. Parameters of interest in this study are component positions, joint instability and sliding, and contact area. Results. An intraoperative representation of the pelvis and cup was assessed (Figure 1), with a green star showing the native anatomical center, the red circle showing the acetabular cup center, and the arrow representing the reaming direction. During swing phase, it was determined that unaccounted for acetabular cup shifting of 5–10 mm leads to capsular ligament laxity coupled with an increase in hip joint instability. Two swing phase scenarios were assessed, one simulating adequate capsular tension and therefore a uniform contact patch and the other simulating inadequate capsule tension and therefore femoral component pistoning with a smaller contact patch (Figure 2). During stance phase, it was determined that acetabular cup shifting of 5–10 mm in the medial and/or superior directions yields an increase in hip joint instability. Two stance phase scenarios were simulated, one yielding no hip separation and therefore a uniform, centralized contact patch, and the other yielding ∼1.5 mm of hip separation and therefore a non-uniform, supero-lateral edge loading patch (Figure 3). Cup orientation does not appear to directly cause hip instability, but it will either lessen or exacerbate the instability, depending on the specific scenario. The results in this study did reveal that overly-inclined cups will yield less stability in the lateral direction, and overly-anteverted cups will yield less stability in the anterior direction. Discussion. In general, instability during stance phase comes in the form of femoral head sliding and edge loading, and instability during swing phase comes in the form of femoral head pistoning. This study's analyses did reveal that proper alignment of the acetabular cup is required for ideal clinical results. The results from this study dictate that proper translational alignment of the cup as well as rotational alignment is necessary for patient stability and proper hip mechanics. For any figures or tables, please contact authors directly