Osteoarthritis and the pain associated with it result in gait pattern alteration, in particularly gait asymmetry when the disease is unilateral [1–2]. The quantification of such asymmetry could assist with the diagnosis and follow up. Various asymmetry indices have been proposed to compare the spatiotemporal, kinematic and kinetic parameters of lower limbs during the gait cycle. One, the Continuous Relative Phase [3] compares the joints angle and its derivatives to assess the gait asymmetry during the gait cycle. However, the indices rely on marker based gait measurement systems that are costly and generally require manual examination, calibration procedures and the precise placement of sensors/markers on the body of the patient. Create an automatic method to assess gait asymmetry with low cost depth camera system like Kinect.Background
Aim
Osteoarthritis and the pain associated with it result in gait pattern alteration, in particularly gait asymmetry when the disease is unilateral [1–2]. The quantification of such asymmetry could assist with the diagnosis and follow up. Various asymmetry indices have been proposed to compare the spatiotemporal, kinematic and kinetic parameters of lower limbs during the gait cycle. One, the Continuous Relative Phase [3] compares the joints angle and its derivatives to assess the gait asymmetry during the gait cycle. However, the indices rely on marker based gait measurement systems that are costly and generally require manual examination, calibration procedures and the precise placement of sensors/markers on the body of the patient. To overcome these issues, a new asymmetry index was proposed in [4]. It uses an inexpensive, easy-to-use and markerless depth camera (Microsoft Kinect™) output. Without requiring joint localization, it directly uses depth images provided by the Kinect™. It is based on the longitudinal spatial difference between lower-limb movements averaged during several gait cycles. To evaluate the relevance of this index ILong, its sensitivity versus the position of the sensor and the sensitivity versus the number of gait cycle, fifteen healthy subjects were tested on a treadmill walking normally and with an artificially induced gait asymmetry created by placing a thick sole under one shoe. The gait movement was simultaneously recorded using two Kinects™, one placed in front of and another behind the subject, and a motion capture system. The Continuous Relative Phase computed with the Kinect™ skeleton failed to assess gait asymmetry. With the Kinect™ placed in front of and behind the patient the proposed longitudinal index distinguished the asymmetrical gait (p<0.001). Moreover, the correlation coefficient between the index measured by Kinect™ and the ground truth of this index measured by motion capture is more than .85 when using one stride and reaches .90 when using at least five strides. This gait asymmetry index measured with a Kinect™ is low cost, easy to use and is a promising development for clinical gait analysis for Osteoarthritis disease diagnostic and follow up.
Femoral component design is a key part of hip arthroplasty performance. We have previously reported that a hip resurfacing offered functional improved performance over a long stem. However resurfacing is not popular for many reasons, so there is a growing trend towards shorter femoral stems, which have the added benefit of ease of introduction through less invasive incisions. Concern is also developing about the impact of longer stems on lifetime risk of periprosthetic fracture, which should be reduced by the use of a shorter stem. For these reasons, we wanted to know whether a shorter stem offered any functional improvement over a conventional long stem. We surmised that longer stems in hip implants might stiffen the femoral shaft, altering the mechanical properties. From our database of over 800 patients who have been tested in the lab, we identified 95 patients with a hip replacement performed on only one side, with no other lower limb co-morbidities, and a control group: 19 with long stem implant, age 66 ± 14 (LONG) 40 with short stem implant, age 69 ± 9 (SHORT) 26 with resurfacing, age 60 ± 8 (RESURF) 43 healthy control with no history of arthroplasty, age 59 ± 10 (CONTROL) All groups were matched for BMI and gender. Participants were asked to walk on an instrumented treadmill. Initially a 5 minute warm up at 4 km/h, then tests at increasing speed in 0.5 km/h increments. Maximum walking speed was determined by the patients themselves, or when subjects moved from walking to running. Ground reaction forces (GRF) were measured in 20 second intervals at each speed. Features were calculated based on the mean GRF for each trial, and on symmetry measures such as first peak force (heel strike), second peak force (toe-off), the rate at which the foot was loaded and unloaded, and step length.Introduction
Materials and Methods
Normal human locomotion entails a rather narrow base of support (BoS), of around 12cm at normal walking speeds. This relatively narrow gait requires good balance, and is beneficial, as it minimises the adduction moment at the knee. Normal knees have a slightly oblique joint line, and slight varus, which allow the normal human to walk rapidly with a narrow BoS. Patients with increased varus and secondary osteoarthritis have a broader BoS, which exacerbates the excessive load, making walking painful and ungainly. We wondered if there would be a difference between the base of support of patients whose knee kinematics had been preserved, by retaining the native jointline obliquity and the acl, in comparison with those whose alignment had been altered to a mechanically correct ‘neutral’ alignment. Of 201 patients measured following knee arthroplasty, 31 unicondylar patients and 35 total knee patients, with a single primary arthroplasty, and no co-morbidities, over 1 year post-operatively were identified. Two control groups of controls, a younger cohort of 112 people and 17 in an age matched older cohort. All operations were performed by the same surgeon. The total knees were cruciate retaining devices, inserted in mechanical alignment, and the unicondylar knees were inserted retaining the native alignment and joint-line obliquity. The gait of all subjects was analysed on an instrumented, calibrated treadmill with underlying force plates. Patients start by walking at a comfortable speed for them for 5 minutes, before the speed of the treadmill is increased at 1/2 km/h increments until maximum walking speed obtained, spending 30 seconds at each. After the flat test, it was then repeated on a downhill slope of 6°. Base of Support is interpreted as the distance between the centre point of heel strike and toe off from one foot to that of the other. The top walking speed in the unicondylar group was significantly greater than that of the total knee group, as we reported in 2013. TKA patients have an average BoS of 14cm, while UKA patients and controls have a 12cm BoS. The BoS did not reduce with speed. This 2cm, or 17% increase in BoS is significant. Shapiro-Wilk tests demonstrate a normal distribution to the results, and ANOVA testing reveals a significant difference (p<0.05) within the groups between the speeds of 4.5 to 9. Post-Hoc Bonferroni testing reveal a significant difference between the TKA group and each of the other three groups. On the downhill test (figure 1), the mean BoS in the TKA group increased to 16cm. This increase is highly significant, with a p value of <0.001, while the increase in the UKA group at higher speeds failed to reach significance, and the controls both stayed at 12cm. 6 Bi-uni knees tested acted just like the UKAs. A narrow base of support minimises excessive loads across the joint line. Maintenance of jointline obliquity and an ACL enables this feature to be returned to normal following uni, or bi-uni, while a well aligned TKA seems to prevent it.Materials and Methods
Discussion
Any arthroplasty that offers superior function needs to be assessed using metrics that are capable of detecting those functions. The Oxford Hip Score (OHS), the Harris Hip Score (HHS) and WOMAC are patient reported outcome measures (PROMs) with well documented ceiling effects: following hip arthroplasty, many patients are clustered close to full marks following surgery. Two recent well conducted randomised clinical trials made exactly this error, by using OHS and WOMAC to detect a differences in outcome between hip resurfacing and hip arthroplasty despite published data already showing in single arm studies that these two procedures score close to full marks using either of these PROMS. We have already reported that patients with hip resurfacing arthroplasty (HRA) were able to walk faster and with more normal stride length than patients with well performing hip replacements. In an attempt to relate this functional superiority to an outcome measure that does not rely upon the use of expensive machinery, we developed a patient centred outcome measure (PCOM) based upon a method developed by Philip Noble's group, and the University of Arizona's Metabolic Equivalent of Task Index (MET). This PCOM allows patients to select the functions that matter to them personally against which the success of their own operation will be measured, with greater sensitivity to intensity than is achieved by the UCLA. Our null hypothesis was that this PCOM would be no more successful than the PROMs in routine use in discriminating between types of hip arthroplasty, and that there would be no difference in gait between patients following these procedures. From our database of over 800 patients whose gait has been assessed in the lab, we identified 22 patients with a well performing conventional THAs, and matched them for age, sex, BMI, height, preop diagnosis with 22 patients with a well performing conventional THA. Both were compared with healthy controls using the novel PCOM and in a gait lab. PROMs for the two groups were almost identical, while HRA scored higher in the PCOM. The 9% difference was significant (p<0.05). At top walking speed, HRA were 10% faster, with a 9% longer stride length, both of these metrics also reached significance. Function following hip replacement is very good, with high satisfaction rates, but the use of a PCOM, and objective measures of function reveal substantial inferiority of THA over THR in two well matched groups. This 9% difference is well over the 5% difference that is considered ‘clinically relevant’. When coupled with the very strong data regarding life expectancy and infection, this functional data makes a compelling case for the use of resurfacing in active adults.Results
Discussion
The Oxford Hip Score (OHS), the Harris Hip Score (HHS) and WOMAC are examples of patient reported outcome measures (PROMs) have well documented ceiling effects, with many patients clustered close to full marks following arthroplasty. Any arthroplasty that offers superior function would therefore fail to be detectable using these metrics. Two recent well conducted randomised clinical trials made exactly this error, by using OHS and WOMAC to detect a differences in outcome between hip resurfacing and hip arthroplasty despite published data already showing in single arm studies that these two procedures score close to full marks using both PROMS. We had observed that patients with hip resurfacing arthroplasty (HRA) were able to walk faster and with more normal stride length than patients with well performing hip replacements, but that these objective differences in gait were not captured by PROMs. In an attempt to capture these differences, we developed a patient centred outcome measure (PCOM) using a method developed by Philip Noble's group. This allows patients to select the functions that matter to them personally against which the success of their own operation will be measured. Our null hypothesis was that this PCOM would be no more successful than the OHS in discriminating between types of hip arthroplasty. 22 patients with a well performing Hip Resurfacing Arthroplasty were identified. These were closely matched by age, sex, BMI, height, preop diagnosis with 22 patients with a well performing conventional THA. Both were compared with healthy controls using the novel PCOM and in a gait lab. PROMs for the two groups were similar, while HRA scored higher in the PCOM. The 9% difference was significant (p<0.05). At top walking speed, HRA were 10% faster, with a 9% longer stride length. Outcome measures should be able to detect differences that are clinically relevant to patients and their surgeons. The currently used hip scores are not capable of delivering this distinction, and assume that most hip replacements are effectively perfect. While the function of hip replacements is indeed very good, with satisfaction rates high, objective measures of function are essential for innovators who are trying to deliver improved functional outcome. The 9% difference in PCOM found in this small study reflects the higher activity levels reported by many, and of similar magnitude to the 10% difference in top walking speed, despite no detectable difference in conventional PROMS. PCOMs may offer further insight into differences in function. For investigators who wish to develop improvements to hip arthroplasty, PCOMs and objective measures of gait may describe differences that matter more to patients than conventional hip scores.Results
Discussion
Our primary hypothesis was simple: does gait on a downhill gradient distinguish between types of knee arthroplasty? Our secondary hypotheses were these: are stride length and other kinematic variables affected by cruciate ligament integrity following knee arthroplasty? Ethical approval was sought and gained prior to commencement of the study. 52 subjects were tested on the instrumented treadmill, 3 groups (UKA, TKA, and young healthy control) of 19, 14, and 19 respectively. The two high performing arthroplasty groups were recruited from a database of patient related outcome measures (PROMs) and were chosen based on high Oxford knee scores (OKS) with a minimum 12 months post hip arthroplasty.Introduction
Participants
Outcome measures are an essential element of our industry: comparing a novel procedure against an established one requires a reliable set of metrics that are comprehensible to both the technologist and the layman. We surmised that a detailed assessment of function before and after knee arthroplasty, combined with a detailed set of personal goals would enable us to test the hypothesis that less invasive joint and ligament preserving operations could be demonstrated to be more successful, and cost effective. We asked the simple question: how well can people walk following arthroplasty, and can we measure this? Using a treadmill, instrumented with force plates, we developed a regime of walking at increasing speeds and on varying inclines, both up and down hill. The data from the force plates was then extracted directly, without using the proprietary software that filtered it. Code was written in matlab script to ensure that missed steps were not mistakenly attributed to the wrong leg, automatically downloading of all the gait data at all speeds and inclines. The pattern of gait of both legs could then be compared over a range of activities. Wide variation is seen in gait both before and after arthroplasty. The variables that are easiest to explain are these:
width of gait – this appears to be a pre-morbid variable, not easily correctible with surgery. (figure 1) top walking speed – total knee replacement is associated with 11% lower top speeds than uni knees or normals (p < 0.05) change in stride length with increasing speed: normal people increase their walking speed by increasing both their cadence and their stride length incrementally until a top stride length is reached. Patients with a total knee replacement do not increase their stride length at a normal rate, having to rely on increasing cadence to deliver speed increase. Patients with uni or bi-compartmental knee replacements increase speed like normal people. Downhill gait: as many as 40% of fit patients with ‘well functioning’ total knee replacements choose not to walk downhill at all, while all fit patients with ‘well functioning’ partial replacements are able to do this. Those who can manage, can only manage 90% of the normal speed, unlike unis which are indistinguishable from normal (p < 0.05)Materials and methods
Results
A recent PRCT failed to demonstrate superiority of HRA over THA at low speeds. Having seen HRA walk much faster, we wondered if faster walking speed might reveal larger differences. We therefore asked two simple questions: Does fast or uphill walking have an effect on the observed difference in gait between limbs implanted with one HRA and one THA? If there is a difference in gait between HRA and THA implanted legs, which is more normal?
There were 3 females and 6 males in the study group, who had a mean age of 67 (55–76) vs the control group 64 (53–82, p = 0.52). The BMIs of the two groups did not differ significantly (28 v 25, p = 0.11). The mean average oxford score of included patients was 44 (36–48). Radiographs of all subjects were examined to ensure that implanted components were well fixed. The mean time from THA operation to gait assessment was 4 years (1–17 yrs) and that for HRA was 6 years (0.7–10 yrs, p = 0.31). Subjects in this study had a mean TWS of 6.8 km/hr (5–9.5), and a mean TWI of 19 degrees (10–25 degrees).INTRODUCTION
METHODS
The combination of patient-specific “just-in-time” implant manufacture and robotic technology has not yet been reported. The robot enables accurate placement of anatomically-matched implants. It should be cost-effective, simplify the procedure, and reduce instrumentation. The aims of this study were to determine whether the procedure was safe, radiographically accurate, and comparable in time and cost to conventional arthroplasty. All patients over 3 months post-op were included. Component position, orientation and size were determined from CT scans by the surgeon prior to manufacture. The implants were inserted using the Sculptor robot, which is supplied free of cost (Savile Row, Stanmore Implants, UK). Following registration, bone was milled away using a high-speed burr under haptic control of the robot. The implants were cemented and a mobile bearing inserted. Patients were followed up clinically and radiographically. Oxford and EQ-5D scores were obtained. Costs of the implant, instruments, and consumables were calculated and compared to published data for conventional UKA and TKA.Background
Methods
