Gait analysis is an indispensable tool for scientific assessment and treatment of individuals whose ability to walk is impaired. The high cost of installation and operation are a major limitation for wide-spread use in clinical routine. Advances in Artificial Intelligence (AI) could significantly reduce the required instrumentation. A mobile phone could be all equipment necessary for 3D gait analysis. MediaPipe Pose provided by Google Research is such a Machine Learning approach for human body tracking from monocular RGB video frames that is detecting 3D-landmarks of the human body. Aim of this study was to analyze the accuracy of gait phase detection based on the joint landmarks identified by the AI system. Motion data from 10 healthy volunteers walking on a treadmill with a fixed speed of 4.5km/h (Callis, Sprintex, Germany) was sampled with a mobile phone (iPhone SE 2nd Generation, Apple). The video was processed with Mediapipe Pose (Version 0.9.1.0) using custom python software. Gait phases (Initial Contact - IC and Toe Off - TO) were detected from the angular velocities of the lower legs. For the determination of ground truth, the movement was simultaneously recorded with the AS-200 System (LaiTronic GmbH, Innsbruck, Austria). The number of detected strides, the error in IC detection and stance phase duration was calculated. In total, 1692 strides were detected from the reference system during the trials from which the AI-system identified 679 strides. The absolute mean error (AME) in IC detection was 39.3 ± 36.6 ms while the AME for stance duration was 187.6 ± 140 ms. Landmark detection is a challenging task for the AI-system as can clearly be seen be the rate of only 40% detected strides. As mentioned by Fadillioglu et al., error in TO-detection is higher than in IC-detection

Patellofemoral osteoarthritis (PFOA) affects 32% men and 36% women over the age of 60years and is associated with anterior knee pain, stiffness, and poor mobility. Patellofemoral arthroplasty (PFA) is a bone-sparing treatment for isolated PFOA. This study set out to investigate the relationship between patient-related outcome measures (PROMs) and measurements obtained from gait analysis before and after PFA. There are currently no studies relating to gait analysis and PFA available in the literature. A prospective cohort study was conducted of ten patients known to have isolated PFOA who had undergone PFA compared to a gender and age matched control group. The patients were also asked to complete questionnaires (Oxford knee score (OKS), EQ-5D-5L) before surgery and one year after surgery. Gait analysis was done on an instrumented treadmill comparing Ground reaction force parameters between the control and pre and post-operative PFA patients. The average age 60 (49–69) years with a female to male ratio of 9:1. Patient and healthy subjects were matched for age and gender, with no significant difference in BMI. Post-op PFA improvement in gait seen in ground reaction force at 6.5km/h. Base support difference was statistically significant both on the flat P=0.0001 and uphill P=0.429 (5% inclination) and P=0.0062 (10% inclination). PROMS response rate was 70%(7/10) pre-operative and 60%(6/10) post-operative. EQ-5D-5L scores reflected patient health state was better post-operatively. This study found that gait analysis provides an objective measure of functional gait and reflected by significant quality-of-life improvement of patients post PFA. Literature lacks studies relating to gait-analysis and PFA. Valuable information provided by this study highlights that PFA has a beneficial outcome reflected by PROMs and improvement in vertical ground reaction force and gait. Further research is needed to assess how care-providers may use gait-analysis as part of patient care plans for PFOA patients

This study aimed to quantify self-reported outcomes and walking gait biomechanics in patients following primary and revision THA. The specific goals of this study were to investigate: (i) if primary and revision THA patients have comparable preoperative outcomes; and (2) if revision THA patients have worse postoperative outcomes than primary THA patients. Forty-three patients undergoing primary THA for osteoarthritis and 23 patients undergoing revision THA were recruited and followed longitudinally for their first 12 postoperative months. Reasons for revision were loosening (73%), dislocation (9%), and infection (18%). Patients completed the Hip dysfunction and Osteoarthritis Outcome Score (HOOS), and underwent gait analysis preoperatively, and at 3 and 12 months postoperatively. A 10 camera motion analysis system (V5 Vantage, Vicon, UK) recorded marker trajectories (100 Hz) during walking at self- selected speeds. A generic lower-body musculoskeletal model (Gait2392) was scaled using principal component analysis [1] and the inverse kinematics tool in Opensim 3.3 was used to compute joint angles for the lower limbs in the sagittal plane. Independent samples t-test were used to compare patient reported outcomes between the primary and revision groups at each timepoint. Statistical parametric mapping was used to compare gait patterns between the two groups at each timepoint. Preoperatively, patients undergoing primary THA reported significantly worse pain (p<0.001), symptoms (p<0.001), function (p<0.001), and quality of life (p=0.004). No differences were observed at 3 and 12 months postoperatively between patients who had received a primary or revision THA. The only observed difference in gait pattern was that patients with a revision THA had reduced hip extension at 3 months, but no differences were observed preoperatively and 12 months. Despite the suggestions in the literature that revision THA is bound to have worse outcomes compared to primary THA, we found no differences in in patient-reported outcomes and gait patterns at 12 months postoperatively. This suggests that it may be possible, in some circumstances, for patients following revision THA to achieve similar outcomes to their peers undergoing primary THA

The risk of falls in patients undergoing orthopedic procedures is particularly significant in terms of health and socioeconomic effects. The literature analyzed closely this risk following procedures performed on the lower limb, but the implications following procedures on the upper limb remain to be investigated. Interestingly, it is not clear whether the increased risk of falling in patients undergoing shoulder surgery is due to preexisting risk factors at surgery or postoperative risk factors, such as anesthesiologic effects, opioid medications used for pain control, or brace use. Only one prospective study examined gait and fall risk in patients using a shoulder abduction brace (SAB) after shoulder surgery, revealing that the brace adversely affected gait kinematics with an increase in the risk of falls. The main purpose of the study was to investigate the influence of SAB on gait parameters in patients undergoing shoulder surgery. Patients undergoing elective shoulder surgery (arthroscopic rotator cuff repair, reverse total shoulder arthroplasty, and Latarjet procedure), who used a 15° SAB in the postoperative period, were included. Conversely, patients age > 65 years old, with impaired lower extremity function (e.g., fracture sequelae, dysmorphism, severe osteo-articular pathology), central and peripheral nervous system pathologies, and cardiac/respiratory/vascular insufficiency were excluded. Participants underwent kinematic analysis at four different assessment times: preoperative (T0), 24 hours after surgery (T1), 1 week after surgery (T2), and 1 week after SAB removal (T3). The tests used for kinematic assessment were the Timed Up and Go (TUG) and the 10-meter test (10MWT), both of which examine functional mobility. Agility and balance were assessed by a TUG test (transitions from sitting to standing and vice versa, walking phase, turn-around), while gait (test time, cadence, speed, and pelvic symmetry) was evaluated by the 10MWT. Gait and functional mobility parameters during 10MWT and TUG tests were assessed using the BTS G-Walk sensor (G-Sensor 2). One-way ANOVA for repeated measures was conducted to detect the effects of SAB on gait parameters and functional mobility over time. Statistical analysis was performed with IBM®SPSS statistics software version 23.0 (SPSS Inc., Chicago, IL, USA), with the significant level set at p<0.05. 83% of the participants had surgery on the right upper limb. A main effect of time for the time of execution (duration) (p=0.01, η2=0.148), speed (p<0.01, η2=0.136), cadence (p<0.01, η2=0.129) and propulsion-right (R) (p<0.05, η2=0.105) and left (L) (p<0.01, η2=0.155) in the 10MWT was found. In the 10MWT, the running time at T1 (9.6±1.6s) was found to be significantly longer than at T2 (9.1±1.3s, p<0.05) and at T3 (9.0±1.3s, p=0.02). Cadence at T1 (109.7±10.9steps/min) was significantly lower than at T2 (114.3 ±9.3steps/min, p<0.01) and T3 (114.3±9.3steps/min, p=0.02). Velocity at T1 (1.1±0.31m/s) was significantly lower than at T2 (1.2± 0.21m/s, p<0.05). No difference was found in the pelvis symmetry index. No significant differences were found during the TUG test except for the final rotation phase with T2 value significantly greater than T3 (1.6±0.4s vs 1.4±0.3s, p<0.05). No statistically significant differences were found between T0 and T2 and between T0 and T3 in any of the parameters analyzed. Propulsion-R was significantly higher at T3 than T1 (p<0.01), whereas propulsion-L was significantly lower at T1 than T0 (p<0.05) and significantly higher at T2 and T3 than T1 (p<0.01). Specifically, the final turning phase was significantly higher at T2 than T3 (p<0.01); no significant differences were found for the duration, sit to stand, mid-turning and stand to sit phases. The results demonstrated that the use of the abduction brace affects functional mobility 24 hours after shoulder surgery but no effects were reported at longer term observations

The study compared thigh-shank and shank-foot coordination during gait before and after total knee arthroplasty (TKA) with controls (CTRL). Twenty-seven patients (male=15/female=12; age=63.2±6.9 years) were evaluated one month prior to and twelve months after surgery, and compared to 27 controls (male=14/female=13; age=62.2±4.3). The participants were outfitted with a full-body marker set. Gait speed (normalized by leg length) was calculated. The time series of the thigh, shank, and foot orientation in relation to the laboratory coordinate system were extracted. The coordination between the thigh-shank and shank-foot in the sagittal plane were calculated using a vector coding technique. The coupling angles were categorized into four coordination patterns. The stance phase was divided into thirds: early, mid, and late stance. The frequency of each pattern and gait speed were compared using a one-way ANOVA with a post-hoc Bonferroni correction. Walking speed and shank-foot coordination showed no differences between the groups. The thigh-shank showed differences. The pre-TKA group showed a more in-phase pattern compared to the CTRL group during early-stance. During mid-stance, the pre- and post-TKA presented a more in-phase pattern compared to the CTRL group. Regarding shank-foot coordination, the groups presented an in-phase and shank pattern, with more shank phase during mid-stance and more in-phase during late-stance. The pre-TKA group showed greater differences than the post-TKA compared to the controls. The more in-phase pattern in the pre- and post-TKA groups could relate to a reduced capacity for the thigh that leads the movement. During mid-stance in normal gait, the knee is extending, where the thigh and shank movements are in opposite directions. The in-phase results in the TKA groups indicate knee stiffness during the stance phase, which may relate to a muscular deficit or a gait strategy to reduce joint stress

Vacuum orthoses are being applied in the care of patients with foot and lower leg conditions, as ankle fractures or sprains. The lower leg is protected and immobilized, which increases mobility. Due to the design, the orthoses lead to a difference in leg length, i.e. the side with the orthosis becomes longer, which changes the gait kinematics. To prevent or mitigate the unfavourable effects of altered gait kinematics, leg length-evening devices (shoe lifts) are offered that are worn under the shoe on the healthy side. Our aim was to evaluate the effect of such a device on the normality of gait kinematics. Gait analysis was conducted with 63 adult, healthy volunteers having signed an informed consent form that were asked to walk on a treadmill at a speed of 4.5km/h in three different conditions:. barefoot - as reference for establishing the normality score baseline. with a vacuum orthosis (VACOPed, OPED GmbH, Germany) and a sport shoe. with a vacuum orthosis and a shoe lift (EVENup, OPED GmbH, Germany). Data was sampled using the gait analysis system MCU 200 (LaiTronic GmbH, Austria). The positions of the joint markers were exported from the software and evaluated for the joint angles during the gait cycle using custom software (implemented in DIAdem 2017, National Instruments). A normality score using a modification of the Gait Profile Score (GPS) was calculated in every 1%-interval of the gait cycle and evaluated with a Wilcoxon signed rank test. The GPS value was reduced by 0.33° (0.66°) (median and IQR) while wearing the shoe lift. The effect was statistically significant, and very large (W = 1535.00, p < .001; r (rank biserial) = 0.52, 95% CI [0.29, 0.70]). The significant reduction of the GPS value indicates a more normal gait kinematics while using the leg length-evening device on the contralateral shoe. This rather simple and inexpensive device thus might improve patient comfort and balance while using the vacuum orthoses

Introduction. A recent study to identify clinically meaningful benchmarks for gait improvement after total hip replacement (THA) has shown that the minimum clinically important improvement (MCII) in gait speed after THA is 0.32 m/sec. Currently, it remains to be investigated what preoperative factors link to suboptimal recovery of gait function after THA. This study aimed to identify preoperative lower-limb muscle predictors for gait speed improvement after THA for hip osteoarthritis. Method. This study enrolled 58 patients who underwent unilateral primary THA. Gait speed improvement was evaluated as the subtraction of preoperative speed from postoperative speed at 6 months after THA. Preoperative muscle composition of the glutei medius and minimus (Gmed+min) and the gluteus maximus (Gmax) was evaluated on a single axial computed tomography slice at the bottom end of the sacroiliac joint. Cross-sectional area ratio of individual composition to the total muscle was calculated. Result. The females (n=45) showed smaller total cross-sectional areas of the gluteal muscles than the males (n=13). Gmax in the females showed lower lean muscle mass area (LMM) and higher ratios of the intramuscular fat area and the intramuscular adipose tissue area to the total muscle area (TM) than that in the males. Regression analysis revealed that LMM/TM of Gmed+min may correlate negatively with postoperative improvement in gait speed. Receiver operating characteristic curve analysis for prediction of MCII in gait speed at ≥ 0.32 m/sec resulted in the highest area under the curve for Gmax TM with negative correlation. The explanatory variables of hip abductor muscle composition predicted gait speed improvement after THA more precisely in the females compared with the total group of both sexes. Conclusion. Preoperative Gmax TM could predict gait speed MCII after THA. Preoperative muscle composition should be evaluated separately based on sexes for achievement of clinically important improvement in gait speed after THA

For clinical movement analysis, optical marker-based motion capture is the gold standard. With the advancement of AI-driven computer vision, markerless motion capture (MMC) has emerged. Validity against the marker-based standard has only been examined for lightly-dressed subjects as required for marker placement. This pilot study investigates how different clothing affects the measurement of typical gait metrics. Gait tests at self-selected speed (4 km/h) were performed on a treadmill (Motek Grail), captured by 9 cameras (Qualisys Miqus, 720p, f=100Hz) and analyzed by a leading MMC application (Theia, Canada). A healthy subject (female, h=164cm, m=54kg) donned clothes between trials starting from lightly dressed (LD: bicycle tight, short-sleeved shirt), adding a short skirt (SS: hip occlusion) or a midi-skirt (MS: partial knee occlusion) or street wear (SW: jeans covering ankle, long-sleeved blouse), the lattern combined with a short jacket (SWJ) or a long coat (SWC). Gait parameters (mean±SD, t=10s) calculated (left leg, mid-stance) were ankle pronation (AP-M), knee flexion (KF-M), pelvic obliquity (PO-M) and trunk lateral lean (TL-M) representing clinically common metrics, different joints and anatomic planes. Four repetitions of the base style (LD) were compared to states of increased garment coverage using the t-test (Bonferroni correction). For most gait metrics, differences between the light dress (LD) and various clothing styles were absent (p>0.0175), small (< 2SD) or below the minimal clinically important differences (MCID). For instance, KF-M was for LD=10.5°±1.7 versus MD=12.0°±0.5 (p=0.07) despite partial knee cover. AP-M measured for LD=5.2°±0.6 versus SW=4.1°±0.7 (p<0.01) despite ankle cover-up. The difference for KF-M between LD=10.5°±1.7 versus SWL=6.0°±0.9, SW and SWJ (7.6°±1.5, p<0.01) indicates more intra-subject gait variability than clothing effect. This study suggests that typical clothings styles only have a small clinically possibly negligible effect on common gait parameters measured with MMC. Thus, patients may not need to change clothes or be instructed to wear specific garments. In addition to avoiding marker placement, this further increases speed, ease and economy of clinical gait analysis with MMC facilitating high volume or routine application

Abstract. Objectives. Little is known about the impact of cartilage defects on knee joint biomechanics. This investigation aimed to determine the gait characteristics of patients with symptomatic articular cartilage lesions of the knee. Methods. Gait analyses were performed at the Regional North-West Joint Preservation Centre. Anthropometric measurements were obtained, then 16 retroreflective markers representing the Plug-in-Gait biomechanical model were placed on pre-defined anatomical landmarks. Participants walked for two minutes at a self-selected speed on a treadmill on a level surface, then for 2 minutes downhill. A 15-camera motion-capture system recorded the data. Knee kinematics were exported into Matlab to calculate the average kinematics and spatiotemporal parameters per patient across 20 gait cycles. Depending on the normality of the data, paired t-tests or Wilcoxon ranked tests were performed to compare both knees (α = 0.05). Results. 20 patients participated; one of whom has bilateral cartilage defects. All 20 data sets were analysed for level walking; 18 were analysed for downhill walking. On a level surface, patients walked at an average speed of 3.1±0.8km/h with a cadence of 65.5±15.3 steps/minute. Patients also exhibited equal step lengths (0.470±0.072m vs 0.471±0.070m: p=0.806). Downhill, the average walking speed was 2.85±0.5km/h with a cadence of 78.8±23.1 steps/minute and step lengths were comparable (0.416±0.09m vs 0.420±0.079m: p=0.498). During level walking, maximum flexion achieved during swing did not differ between knees (54.3±8.6° vs 55.5±11.0°:p=0.549). Neither did maximal extension achieved at heel strike (3.1±5.7° vs 5.4±4.7°:p=0.135). On average, both knees remained in adduction throughout the gait cycle, with the degree of adduction greater in flexion in the operative knee. However, differences in maximal adduction were not significant (22.4±12.4° vs 18.7±11.0°:p=0.307). Maximal internal-external rotation patterns were comparable in stance (0.9±7.7° vs 3.5±9.8°: p=0.322) and swing (7.7±10.9° vs 9.8±8.3°:p=0.384). During downhill walking, maximum flexion also did not differ between operative and contralateral knees (55.38±10.6° vs 55.12±11.5°:p=0.862), nor did maximum extension at heel strike (1.32±6.5° vs 2.73±4.5°:p=0.292). No significant difference was found between maximum adduction of both knees (15.87±11.0° vs 16.78±12.0°:p=0.767). In stance, differences in maximum internal-external rotation between knees were not significant (5.39±10.7° vs 6.10±11.8°:p=0.836), nor were they significant in swing (7.69±13.3° vs 7.54±8.81°:p=0.963). Conclusions. Knee kinematics during level and downhill walking were symmetrical in patients with a cartilage defect of the knee, but an increased adduction during flexion in the operative knee may lead to pathological loading across the medial compartment of the knee during high flexion activities. Future work will investigate this further and compare the data to a healthy young population. We will also objectively assess the functional outcome of this joint preservation surgery to monitor its success. Declaration of Interest. (b) declare that there is no conflict of interest that could be perceived as prejudicing the impartiality of the research reported:I declare that there is no conflict of interest that could be perceived as prejudicing the impartiality of the research project

Introduction. Knee osteoarthritis often causes malalignment and altering bone load. This malalignment is corrected during total knee arthroplasty surgery, balancing the ligaments. Nonetheless, preoperative gait patterns may influence postoperative prosthesis load and bone support. Thus, the purpose is to investigate the impact of preoperative gait patterns on postoperative femoral and tibial component migration in total knee arthroplasty. Method. In a prospective cohort study, 66 patients with primary knee osteoarthritis undergoing cemented Persona total knee arthroplasty were assessed. Preoperative knee kinematics was analyzed through dynamic radiostereometry and motion capture, categorizing patients into four homogeneous gait patterns. The four subgroups were labeled as the flexion group (n=20), the abduction (valgus) group (n=17), the anterior drawer group (n=10), and the tibial external rotation group (n=19). The femoral and tibial component migration was measured using static radiostereometry taken supine on the postoperative day (baseline) and 3-, 12-, and 24- months after surgery. Migration was evaluated as maximum total point motion. Result. Of the preoperatively defined four subgroups, the abduction group with a valgus-characterized gait pattern exhibited the highest migration for both the femoral (1.64 mm (CI95% 1.25; 2.03)) and tibial (1.21 mm (CI95% 0.89; 1.53)) components at 24-month follow-up. For the femoral components, the abduction group migrated 0.6 mm (CI95% 0.08; 1.12) more than the external rotation group at 24 months. For the tibial components, the abduction group migrated 0.43 mm (CI95% 0.16; 0.70) more than the external rotation group at 3 months. Furthermore, at 12- and 24-months follow-up the abduction group migrated 0.39 mm (95%CI 0.04; 0.73) and 0.45 mm (95%CI 0.01; 0.89) more than the flexion group, respectively. Conclusion. A preoperative valgus-characterized gait pattern seems to increase femoral and tibial component migration until 2 years of follow-up. This suggests that the implant fixation depends on load distributions originating from specific preoperative gait patterns

Introduction and Objective. Gait variability is the amplitude of the fluctuations in the time series with respect to the mean of kinematic (e.g., joint angles) or kinetic (e.g., joint moments) measurements. Although gait variability increases with normal ageing or pathological mechanisms, such as knee osteoarthritis (OA). The purpose was to determine if a patient who underwent a total knee arthroplasty (TKA) can reduce gait variability. Materials and Methods. Twenty-five patients awaiting TKA were randomly assigned to receive either medial pivot (MP, m=7/f=6, age=62.4±6.2 years) or posterior stabilized (PS, m=7/f=5, age=63.7±8.9 years) implants, and were compared to 13 controls (CTRL, m=7/f=6, age=63.9±4.3 years). All patients completed a gait analysis within one month prior and 12 months following surgery, CTRLs completed the protocol once. A waveform F-Test Method (WFM) was used to compare the variance in knee biomechanics variables at each interval of the gait cycle. Results. Preoperatively, the PS group had greater sagittal knee angle variability compared to the MP (32–58% gait cycle) and CTRL (21–53% gait cycle) groups. Postoperatively, no difference in sagittal knee angle variability existed between any of the groups. Preoperatively, sagittal knee moment variability was greater in the MP (2–39% gait cycle) and PS (5–19% and 42–57% gait cycle) groups compared to the CTRL. Postoperatively, sagittal knee moment was lower in the MP (49–55% gait cycle) and greater in the PS (23–36% gait cycle) compared to the CTRL. Knee power variability was greater preoperatively in the MP (52–61% gait cycle) and PS (52–62% gait cycle) compared to the CTRL. Postoperatively, knee power variability was lower in the MP (17–22% and 45–50% gait cycle) and PS (6–23%, 34–41% and 45–49% gait cycle) compared to the CTRL group. Conclusions. Preoperatively, knee OA patients have greater variability in knee moments than CTRLs during the transition from double-limb support to single-limb support on the affected limb. This indicates knee instability as patients are adopting a gait strategy that refers to knee muscle contraction avoidance. The MP group showed greater knee stability postoperatively as they had lower knee moment and power variability compared to the CTRL. The significance of having less variability than CTRLs is not well understood at this time. Future research on muscle activity is needed to determine if neuromuscular adaptations are causing these reductions in variability after TKA

Abstract. Objectives. 1. To investigate the effect of revision total knee replacement (TKR) on gait kinematics in patients with a primary TKR and instability.2. To compare gait kinematics between patients with a well-functioning TKR and those with a primary TKR and symptoms of instability. Methods. This single-centre observational study is following patients who have had a revision TKR due to knee instability. Data was collected pre- and post-operatively at 8–12 week follow-up. The data was compared to a control group of 18 well-functioning TKR patients. Kinematic gait data was collected during routine clinics using a treadmill-based infrared 3D system (Vicon, Oxford, UK) and a published lower limb marker-set. Patients performed 15 strides at three different speeds: 0.6mph, self-selected, and a ‘slow walk’ normalised to leg length (Froude number 0.09). PROMs questionnaires were collected. NHS ethical approval was obtained. Results. Data was collected for 18 well-functioning TKR patients and 8 revision TKR patients pre- and post-operatively, but only 5 could walk at the normalised speed. When walking at a normalised speed (Froude 0.09), patients with a TKR with instability had reduced range of knee flexion (52° (sd 14)) compared to those with a well-functioning TKR (59° (sd 11)). Short term follow-up after a revision TKR operation demonstrated a stiffer knee (45° (sd 12)). However, those with revision TKR had a more flexed knee during stance phase. Conclusions. At short-term follow-up, this cohort of revision TKR patients appear to have reduced flexion range, while remaining more flexed during stance. This may represent a less efficient gait pattern, which may also adversely affect the implant[1]. Longer term follow-up may demonstrate whether this normalises with post-operative rehabilitation. Declaration of Interest. (b) declare that there is no conflict of interest that could be perceived as prejudicing the impartiality of the research reported:I declare that there is no conflict of interest that could be perceived as prejudicing the impartiality of the research project

Abstract. Objectives. Although hip replacement and resurfacing procedures both aim to restore mobility, improve joint function, and relieve pain, it is unclear how each differ in terms of gait mechanics and if they are affected by varying walking speeds. We compared limb symmetry and ground reaction force (GRF) profiles between bilateral total hip arthroplasty patients (THA), bilateral hip resurfacing arthroplasty patients (HRA), and healthy control participants (CON) during level-treadmill walking at different speeds. Methods. Bilateral THA and bilateral HRA patients (nTHA = 15; nHRA = 15; postoperative 12–18 months), and age-, mass-, and height-matched CON participants (nCON = 20) underwent gait analysis on an instrumented treadmill. Walking trials started at 4 km/h and increased in 0.5 km/h increments until top walking speed (TWS) was achieved. Gait symmetry index (SI = 0% for symmetry) was assessed between limbs during weight-acceptance, mid-stance and push-off phases of gait; and vertical GRFs were captured for the normalised stance phase using statistical parametric mapping (SPM; CI = 95%). Results. THA had a significantly lower TWS (6.51 ± 0.06 km/h) compared to HRA (7.09 ± 0.07 km/h, p = 0.01) and CON (7.15 km/h ± 0.06, p = 0.02). There were no SI differences between groups nor between walking speeds (SI < 5%). There were no GRF differences between groups at slower walking speeds (4.0–5.0 km/h). However, at 5.5 and 6 km/h, THA had lower GRF at the push-off phase (0.88 ± 0.09 N/BW), compared to HRA (1.06 ± 0.08 N/BW, p = 0.01) and CON (1.04 ± 0.02 N/BW, p = 0.01). Conclusions. The main finding was that HRA patients demonstrated restored gait function and similar walking profiles to CON participants at any speed. With a diverging gait profile, walking speeds over 5.5 km/h provided a functional challenge for THA patients

Introduction and Objective. In recent studies, robotic-assisted surgical techniques for unicompartmental knee arthroplasty (UKA) have demonstrated superior implant positioning and limb alignment compared to a conventional technique. However, the impact of the robotic-assisted technique on clinical and functional outcomes is less clear. The aim of this study was to compare the gait parameters of UKA performed with conventional and image-free robotic-assisted techniques. Materials and Methods. This prospective, single center study included 66 medial UKA, randomized to a robotic-assisted (n=33) or conventional technique (n=33). Gait analysis was performed on a treadmill at 6 months to identify changes in gait characteristics (walking speed, each degree-of-freedom: flexion–extension, abduction–adduction, internal-external rotation and anterior-posterior displacement). Clinical results were assessed at 6 months using the IKS score and the Forgotten Joint Score. Implants position was assessed on post-operative radiographs. Results. Post-operatively, the whole gait cycle was not significantly different between groups. In both groups there was a significant improvement in varus deformity between the pre- and post-operative gait cycle. There was no significant difference between the two groups in clinical scores, implant position, revision and complication rates. Conclusions. No difference of gait parameters could be identified between medial UKA performed with image-free robotic-assisted technique or with conventional technique

Objectives. Whilst gait speed is variable between healthy and injured adults, the extent to which speed alone alters the 3D in vivo knee kinematics has not been fully described. The purpose of this prospective study was to understand better the spatiotemporal and 3D knee kinematic changes induced by slow compared with normal self-selected walking speeds within young healthy adults. Methods. A total of 26 men and 25 women (18 to 35 years old) participated in this study. Participants walked on a treadmill with the KneeKG system at a slow imposed speed (2 km/hr) for three trials, then at a self-selected comfortable walking speed for another three trials. Paired t-tests, Wilcoxon signed-rank tests, Mann-Whitney U tests and Spearman’s rank correlation coefficients were conducted using Stata/IC 14 to compare kinematics of slow versus self-selected walking speed. Results. Both cadence and step length were reduced during slow gait compared with normal gait. Slow walking reduced flexion during standing (10.6° compared with 13.7°; p < 0.0001), and flexion range of movement (ROM) (53.1° compared with 57.3°; p < 0.0001). Slow walking also induced less adduction ROM (8.3° compared with 10.0°; p < 0.0001), rotation ROM (11.4. °. compared with 13.6. °. ; p < 0.0001), and anteroposterior translation ROM (8.5 mm compared with 10.1 mm; p < 0.0001). Conclusion. The reduced spatiotemporal measures, reduced flexion during stance, and knee ROM in all planes induced by slow walking demonstrate a stiff knee gait, similar to that previously demonstrated in osteoarthritis. Further research is required to determine if these characteristics induced in healthy knees by slow walking provide a valid model of osteoarthritic gait. Cite this article: N. Mannering, T. Young, T. Spelman, P. F. Choong. Three-dimensional knee kinematic analysis during treadmill gait: Slow imposed speed versus normal self-selected speed. Bone Joint Res 2017;6:514–521. DOI: 10.1302/2046-3758.68.BJR-2016-0296.R1

Introduction and Objective. Slipped Capital Femoral Epiphysis (SCFE) is one of the most common hip disorders in children and is characterized by a proximal femoral deformity, resulting in early osteoarthritis. Several studies have suggested that SCFE patients after in situ fixation show an altered gait pattern. Early identification of gait alterations might lead to earlier intervention programs to prevent osteoarthritis. The aim of this study is to analyse gait alterations in SCFE patients after in situ fixation compared to typically developed children, using the Computer Assisted Rehabilitation Environment (CAREN) system. Materials and Methods. This is a cross-sectional, multi-center case-control study in the Netherlands. Eight SCFE patients and eight age- and sex-matched typically developed were included from two hospitals. Primary outcomes were kinematic parameters (absolute joint angles), studied with gait analysis using statistical parametric mapping (SPM). Secondary outcomes were spatiotemporal parameters, the Notzli alpha angle, muscle activation patterns (EMG), and clinical questionnaires (VAS, Borg CR10, SF-36, and HOOS), analyzed using non-parametric statistical methods. Results. Patients (mean BMI=28±9 kg/m. 2. ) showed altered gait patterns, with significantly increased external hip rotation and decreased downward pelvic obliquity during the pre-swing phase of the gait cycle compared to typically developed (mean BMI=22±3 kg/m. 2. ). Walking speed, cadence, % stance time, and step length were reduced in SCFE patients. Coefficient of variances of cadence, stance time, and step length were increased. Patients had a mean alpha angle of 64, SD=7.9. Clinical questionnaires showed that general health (SF-36) was 80±25, energy/fatigue (SF-36) was 67±15, pain (VAS) was 0±1.5, and total HOOS score was 85±18. Conclusions. SCFE patients after in situ fixation appear to have developed a compensation mechanism, showing slight alterations in gait parameters, good general health, little functional limitations of the hip, and no self-reported pain. Cam deformities, altered joint loading, and this compensation mechanism might influence long-term early osteoarthritis. BMI reduction should be implemented in care plans, as obesity might also play a role in unfavorable long-term outcomes

Introduction. Adolescent Idiopathic Scoliosis (AIS) is a three-dimensional deformity of the spine with unclear etiology. Due to the asymmetry of lateral curves, there are differences in the muscle activation between the convex and concave sides. This study utilized a comprehensive thoracic spine and ribcage musculoskeletal model to improve the biomechanical understanding of the development of AIS deformity and approach an explanation of the condition. Methods. In this study, we implemented a motion capture model using a generic rigid-body thoracic spine and ribcage model, which is kinematically determinate and controlled by spine posture obtained, for instance, from radiographs. This model is publicly accessible via a GitHub repository. We simulated gait and standing models of two AIS (averaging 15 years old, both with left lumbar curve and right thoracic curve averaging 25 degrees) and one control subject. The marker set included extra markers on the sternum and the thoracic and lumbar spine. The study was approved by the regional Research Ethics Committee (Journal number: H17034237). Results. We investigated the difference between the muscle activation on the right and left sides including erector spinae (ES), psoas major (PS), and multifidus (MF). Results of the AIS simulations indicated that, on average throughout the gait cycle, the right ES, left PS and left MF had 46%, 44%, and 23% higher activities compared to the other side, respectively. In standing, the ratios were 28%, 40%, and 19%, respectively. However, for the control subject, the differences were under 7%, except ES throughout the gait, which was 17%. Conclusion. The musculoskeletal model revealed distinct differences in force patterns of the right and left sides of the spine, indicating an instability phenomenon, where larger curves lead to higher muscle activations for stabilization. Acknowledgement. The project is funded by the European Union's Horizon 2020 program through Marie Skłodowska-Curie grant No. [764644]

Abstract. Objectives. Exploring the relationship of gait function pre and post total knee replacement (TKR) in two groups of patients. Methods. Three-dimensional gait analysis was performed at Cardiff University, UK, and Karolinska University Hospital, Sweden, on 29 and 25 non-pathological (NP) volunteers, and 39 and 28 patients with end-stage knee osteoarthritis (OA), respectively. Patients were assessed pre and one-year post-TKR. Data reduction was performed via Principal Component (PC) analysis on twenty-four kinematic and kinetic waveforms in both NP and pre/post-TKR. Cardiff's and Karolinska's cohorts were analysed separately. The Cardiff Classifier, a classification system based on the Dempster-Shafer theory, was trained with the first 3 PCs of each variable for each cohort. The Classifier classifies each participant by assigning them a belief in NP, belief in OA (BOA) and belief in uncertainty, based on their biomechanical features. The correlation between patient's BOA values (range: 0–1, 0 indicates null BOA and 1 high BOA) pre and post-TKR was tested through Spearman's correlation coefficient in each cohort. The related-samples Wilcoxon signed-rank test (α=0.05) determined the significant changes in BOA in each cohort of patients. The Mann-Whitney U test (α=0.05) was run to explore differences between the patients’ cohorts. Results. There were no significant differences between patients’ cohorts in median age (p=0.096), height (p=0.673), weight (p=0.064) or KOOS sub-scores pre or post-TKR (p-value ranged 0.069 to 0.955) but Cardiff's patients had a significantly higher BMI (p=0.047). There was a significant, median decrease of 0.12 and 0.19 in the BOA pre to post TKR (p<0.001) in Cardiff's and Karolinska's patients, respectively. There was a statistically significant, strong positive correlation between the BOA pre and post-TKR (Cardiff:r. s. =0.706, p<0.001; Karolinska:r. s. =0.669, p<0.001). Conclusions. In two distinct cohorts of patients, having a more compromised gait function in end-stage knee OA was correlated with poorer gait function post-TKR

In an attempt to alleviate symptoms of the disease, patients with knee osteoarthrosis (KOA) frequently alter their gait patterns. Understanding the underlying pathomechanics and identifying KOA phenotypes is essential for improving treatments. We aimed to investigate altered kinematics in patients with KOA to identify subgroups. Sixty-six patients with symptomatic KOA scheduled for total knee arthroplasty and 12 age-matched healthy volunteers with asymptomatic knees were included. We used k-means to separate the patients based on dynamic radiostereometric assessed knee kinematics. Ligament lesions, KOA score, and clinical outcome were assessed by magnetic resonance imaging, radiographs, and patient reported outcome measures, respectively. We identified four clusters that were supported by clinical characteristics. Compared with the healthy group; The flexion group (n=20): revealed increased flexion, greater adduction, and joint narrowing and consisted primarily of patients with medial KOA. The abduction group (n=17): revealed greater abduction, joint narrowing and included primarily patients with lateral KOA. The anterior draw group (n=10): revealed greater anterior draw, external tibial rotation, lateral tibial shift, adduction, and joint narrowing. This group was composed of patients with medial KOA, some degree of anterior cruciate ligament lesion and the greatest KOA score. The external rotation group (n=19): revealed greater external tibial rotation, lateral tibial shift, adduction, and joint narrowing while no anterior draw was observed. This group included primarily patients with medial collateral and posterior cruciate ligament lesions. Patients with KOA can, based on their gait patterns, be classified into four subgroups, which relate to their clinical characteristics. The findings add to our understanding of associations between disease pathology characteristics in the knee and the pathomechanics in patients with KOA. A next step is to investigate if patients in the pathomechanic clusters have different outcomes following total knee arthroplasty

Gait measurements can vary due to various intrinsic and extrinsic factors, and this variability becomes more pronounced using inertial sensors in a free-living environment. Therefore, identifying and quantifying the sources of variability is essential to ensure measurement reliability and maintain data quality. This study aimed to determine the variability of daily accelerations recorded by an inertial sensor in a group of healthy individuals. Ten participants, four males and six females, with a mean age of 50 years (range: 29–61) and BMI of 26.9 kg/m. 2. (range: 21.4–36.8), were included. A single accelerometer continuously recorded lower limb accelerations over two weeks. We extracted and analyzed the accelerations of three consecutive strides within walking bouts if the time difference between the bouts was more than two hours. Multivariate mixed-effects modeling was performed on both the discretized acceleration waveforms at 101 points (0–100) and the harmonics of the signals in the frequency domain to determine the variance components for different subjects, days, bouts, and steps as the random effect variables. Intraclass correlation coefficients (ICCs) were calculated for between-day, between-bout, and between-step comparisons. The results showed that the ICCs for the between-day, between-bout, and between-step comparisons were 0.73, 0.82, 0.99 for the vertical axis; 0.64, 0.75, 0.99 for the anteroposterior axis; and 0.55, 0.96, 0.97 for the mediolateral axis. For the signal harmonics, the respective ICCs were 0.98, 0.98, 0.99 for the vertical axis; 0.54, 0.93, 0.98 for the anteroposterior axis; and 0.69, 0.78, 0.95 for the mediolateral axis. Overall, this study demonstrated that accelerations recorded continuously for multiple days in a free-living environment exhibit high variability, mainly between days, and some variability arising from differences between walking bouts during different times within days. However, reliable and repeatable gait measurements can be obtained by identifying and quantifying the sources of variability