Strike Off Research Articles

A Novel Gait Event Detection Algorithm Using a Thigh-Worn Inertial Measurement Unit and Joint Angle Information.

This paper describes the development and evaluation of a novel, threshold-based gait event detection algorithm utilizing only one thigh inertial measurement unit (IMU) and unilateral, sagittal plane hip and knee joint angles. The algorithm was designed to detect heel strike (HS) and toe off (TO) gait events, with the eventual goal of detection in a real-time exoskeletal control system. The data used in the development and evaluation of the algorithm were obtained from two gait databases, each containing synchronized IMU and ground reaction force (GRF) data. All database subjects were healthy individuals walking in either a level-ground, urban environment or a treadmill lab environment. Inertial measurements used were three-dimensional thigh accelerations and three-dimensional thigh angular velocities. Parameters for the TO algorithm were identified on a per-subject basis. The GRF data were utilized to validate the algorithm's timing accuracy and quantify the fidelity of the algorithm, measured by the F1-Score. Across all participants, the algorithm reported a mean timing error of -41±20 ms with an F1-Score of 0.988 for HS. For TO, the algorithm reported a mean timing error of -1.4±21 ms with an F1-Score of 0.991. The results of this evaluation suggest that this algorithm is a promising solution to inertial based gait event detection; however, further refinement and real-time evaluation are required for use in exoskeletal control.

An adaptive gait event detection method based on stance point for walking assistive devices

This paper presents an adaptive and fuzzy logic-based gait event detection method for wearable assistive devices. A conventional and straightforward way to detect gait events is to utilize gyroscope measurements in the sagittal plane for time-series pattern recognition (positive peaks and negative peaks) based on a predefined threshold. This approach works well in the biomechanics analysis while it may have difficulties adapting to the changes in human walking speed for wearable robot applications. To tackle the above issue, first, we keep updating the detection threshold according to the last stride information. Second, we detect the stance point (zero-velocity point) as an indicator to distinguish between the heel strike and toe off events by combining the information about the foot angular velocity and acceleration. A method to construct a fuzzy membership function is also proposed via a series of moving intervals from foot acceleration data. Validation of the proposed gait event detection method using force plates showed that the method obtained high detection accuracy (F1-score = 0.99) for healthy subjects with and without the robotic support limb (RSL).

Feature Selection using Random Forest Classifier for Foot Strike Event Detection in Toe Walkers

Automated Gait event identification of Foot Strike (FS) and Foot Off (FO) in pathological gait data, can be time saving in comparison to conventional manual annotations done currently. Identification of FS and FO allows breaking walking trials into gait cycles and hence aids in comparison of gait parameters like joint angles, forces and moments across gait cycles. Automated Gait Event Detection is also useful in development of wearable sensor devices and robotic systems that assist gait. Researchers have proposed several automatic gait event detection algorithms based on kinematic parameters and systematic study of the literature suggests specific parameters to have higher contribution in identification of FS event in all common pathological gait patterns. We used Random Forest Classifier Feature selection technique to identify high contributing features in FS event in toe walking pediatric pathological gait dataset and the results suggest high similarity in selected features by the machine learning technique with those suggested by popular event detection algorithms based on kinematic parameters for pathological gait. Hence we conclude that RFC feature selection is suitable for feature selection in toe walkers gait dataset for event detection purpose. Keyword : Feature selection, foot off, foot strike, pathological gait.

Impact of Gait Events Identification through Wearable Inertial Sensors on Clinical Gait Analysis of Children with Idiopathic Toe Walking

Idiopathic toe walking (ITW) is a gait deviation characterized by forefoot contact with the ground and excessive ankle plantarflexion over the entire gait cycle observed in otherwise-typical developing children. The clinical evaluation of ITW is usually performed using optoelectronic systems analyzing the sagittal component of ankle kinematics and kinetics. However, in standardized laboratory contexts, these children can adopt a typical walking pattern instead of a toe walk, thus hindering the laboratory-based clinical evaluation. With these premises, measuring gait in a more ecological environment may be crucial in this population. As a first step towards adopting wearable clinical protocols embedding magneto-inertial sensors and pressure insoles, this study analyzed the performance of three algorithms for gait events identification based on shank and/or foot sensors. Foot strike and foot off were estimated from gait measurements taken from children with ITW walking barefoot and while wearing a foot orthosis. Although no single algorithm stands out as best from all perspectives, preferable algorithms were devised for event identification, temporal parameters estimate and heel and forefoot rocker identification, depending on the barefoot/shoed condition. Errors more often led to an erroneous characterization of the heel rocker, especially in shoed condition. The ITW gait specificity may cause errors in the identification of the foot strike which, in turn, influences the characterization of the heel rocker and, therefore, of the pathologic ITW behavior.

Simultaneous validation of wearable motion capture system for lower body applications: over single plane range of motion (ROM) and gait activities.

Extracting data from {Zhu, 2019 #5} daily life activities is important in biomechanical applications to define exact boundary conditions for the intended use-based applications. Although optoelectronic camera-marker based systems are used as gold standard tools for medical applications, due to line-of-sight problem, there is a need for wearable, affordable motion capture (MOCAP) systems. We investigate the potential use of a wearable inertial measurement unit (IMU) based-wearable MOCAP system for biomechanical applications. The in vitro proof of concept is provided for the full lower body consisting of hip, knee, and ankle joints via controlled single-plane anatomical range of motion (ROM) simulations using an electrical motor, while collecting data simultaneously via opto-electronic markers and IMU sensors. On 15 healthy volunteers the flexion-extension, abduction-adduction, internal-external rotation (ROM) values of hip and, the flexion- extension ROM values of the knee and ankle joints are calculated for both systems. The Bland-Altman graphs showed promising agreement both for in vitro and in vivo experiments. The maximum Root Mean Square Errors (RMSE) between the systems in vitro was 3.4° for hip and 5.9° for knee flexion motion in vivo, respectively. The gait data of the volunteers were assessed between the heel strike and toe off events to investigate the limits of agreement, calculating the population averages and standard deviation for both systems over the gait cycle. The maximum difference was for the ankle joint <6°. The results show that proposed system could be an option as an affordable-democratic solution.

Deep Learning Enables Exoboot Control to Augment Variable-Speed Walking

Ankle exoskeletons have the potential to improve mobility, but common controllers are often inflexible to variations in tasks, such as changes in walking speed. To enable effective variable-speed exoboot control, we developed and validated a two-headed convolutional neural network trained to (1) classify stance versus swing and (2) predict the phase during stance, which was then mapped to a desired exoboot torque. This Machine Learning Estimator (MLE) was trained from nine participants walking at three speeds and four exoboot assistance levels. A Time-Based Estimator (TBE) that predicted gait phase from the two previous stride durations was used to apply realistic torques during MLE training and served as a within&#x2013;participant control condition. The MLE was validated online with three new participants walking at a range of speeds and torques, both interpolating within and extrapolating outside the training set. Online validation accuracy (RMSE) across tested speeds and torque levels was 3.9&#x0025;. On a simple walking task in which treadmill speed was varied sinusoidally between 1.1 and 1.6 m&#x002F;s with a 30 s period, the three participants exhibited a mean 5.2&#x0025; decrease in metabolic expenditure with the MLE compared to no-exo (boots only), but exhibited a 5.4&#x0025; increase when walking with the TBE. The MLE more accurately predicted heel strike and toe off events (heel strike Mean Absolute Error: 9.6 ms; toe off MAE: 13.2 ms) than the TBE (heel strike MAE: 19.1 ms; toe off MAE: 34 ms). These positive results validated the potential of using a deep learning model for gait state estimation to effectively control an ankle exoskeleton across variable walking speeds.

Can increased load carriage affect lower limbs kinematics during military gait?

The aim of this study was to investigate if increased load carriage, in male military personnel, can affect the lower limbs kinematics. Twelve male military volunteers from the Portuguese Army were recruited and evaluated in an unloaded and loaded gait condition. Linear kinematics and lower limbs joint angle at heel strike, midstance and toe off were calculated. The stance, swing and double support times were found to be different between load conditions (p < 0.05). There was an interaction between load and limb (p < 0.05) for joint angles, during midstance, with limbs performing different movements in the frontal plane during loaded gait. Load increase had a different effect on the right knee, with a reduction in the abduction (valgus). This study may be beneficial in offering suggestion to improve the performance of gait with load and in an attempt to help prevent possible injuries. Practitioner summary: Increased load can affect lower limbs of male soldiers at the pelvic, hip and knee angles on the frontal plane, which can alter the joint force distribution. While these alterations may indicate protective mechanics, load management procedures should be implemented along with gait monitoring to avoid negative effects in performance.

In Silico of Different Gait Cycle in Customised Leg Orthosis: A Finite Element Approach

Leg orthosis is one of medical device for fracture bone treatment. Several complications have been reported when patients are wearing the conventional Plaster of Paris or fibreglass leg orthosis. Its including numbness due to tight application, swelling, venous congestion and skin irritation. Therefore, the aim of this study is to develop and biomechanical analyse a customized leg cast that could tackle those complications. First, the leg was scanned using a 3D scanner. The leg cast was constructed from a 3D scanned leg model and designed using 3-Matic software which later simulated in finite element analysis using Marc software. The study focuses on three gait cycles; midstance, heel strike and toe off where stress and deformation were predicted. From the results, the cast only supported the ankle in midstance phase with only 7.297MPa stress and not capable to support the ankle in heel strike and toe off phases with maximum stress of 106.99 MPa and 213.12 MPa, respectively, which are beyond its yield strength of ABS, 23MPa. The average of overall displacement occurred for both skin and cast were less than 1.5mm. In short, the cast could only support the ankle in midstance phase and cannot be used for heel strike.

Influence of Carrying Unstable Load on Thoracic Kinematics While Walking on a Curved Path

This study investigated the effect of carrying unstable load on thoracic kinematics while walking on a curved path. Three-dimensional spinal kinematics were defined as the rotations between thoracic and the Virtual laboratory coordinate system (Tho/Virtual lab) which consisted of lateral bending (LB), flexion/extension (FE) and axial rotation (AR) in the frontal plane, sagittal plane and transverse plane, respectively. Eight healthy young adults (4 males and 4 females) performed loads carrying and walking on one meter radius curved path. Spinal kinematics was determined at the left leg heel strike and just before the right toe off during the curved path walking. As a result, a significant main effect of load intensity was found only on FE of (Tho/Virtual lab) at both left leg heel strike and right leg toe off. The study concluded that an increase in the load intensity of unstable load from 10% of body weight likely to generate more thorax extension.

A Wearable Sensor-based System For Gait Analysis That Is Robust To Gait Variations

Gait analysis is widely used to assess deficits following sports injuries or monitor recovery during rehabilitation [1]. While traditional technologies such as motion capture systems and instrumented force plates can be used to measure kinematics during relevant phases of gait, they are confined to lab environments. Advances in inertial measurement unit (IMU) technology provide alternative prospects for portable assessment of both gait events and kinematics. PURPOSE: Evaluate IMU-based system (wearable sensors and autonomous detection algorithms) for detecting gait events and monitoring range of motion (ROM) under controlled gait variations similar to those observed following an injury [1-3]. METHODS: 10 healthy participants (5 M, 5 F, 26.5 ± 2 y.o.) were instrumented with 6 IMUs (Delsys Inc., USA) placed on the sacrum and sternum and bilaterally on the lower/upper legs. Force sensitive resisters (FSR; placed under each foot) and motion capture (Vicon, UK) outcomes were used as gold standard for validating gait events and kinematic measures, respectively. Subjects walked on a treadmill with normal gait followed by gait alterations including: 1) reduced sagittal knee ROM by >30%, 2) reduced sagittal hip ROM by >20%, and 3) increased trunk obliquity by >10%. These gait variations were chosen for their relevance to sport-related injuries such as ACL tear or abdominal strain [1-3]. Our detection algorithms used lower leg IMU data to identify heel strike and toe off, with cycle duration as the time between heel strikes; and IMU data from upper/lower leg, upper leg/sacrum, and sternum to compute knee, hip, and trunk ROM respectively. RESULTS: Cycle duration was detected with <0.5% error with respect to FSRs, and heel strike and toe off were detected within <5% of gait duration across trials, subjects, and gait variations. Knee, hip and trunk ROM were within 5 degrees of those obtained using motion capture for both normal and altered gait. CONCLUSION: Our wearable IMU-based system can accurately detect gait events and calculate gait kinematics during a range of controlled gait variations similar to those resulting from sports injuries. 1] Gokeler et al. Int J Sports Phys Ther, 2013. 2] Young et al. Am J Sports Med, 2014. 3] Hewett et al. Exerc Sport Sci Rev, 2011. Acknowledgments: Work supported in part by NINDS R43HD100209.

Development of a Crutch Substitute for Mimicking Human Natural Walking Gait

In order to resolve some of the disadvantages of conventional crutch designs, as well as some of the existing crutch-substitute devices, available on the market, a novel Exo-Limb crutch design is presented. The Exo-limb is a hands-free crutch meant to enhance and replace standard underarm crutches and other competitive products during injury rehabilitation. The focus of this research has been on creating a cost-effective passive device that mimics humans natural walking gait using purely mechanical components. Prior to the design, human natural treadmill walking was monitored by a 3D Motion Capture System and a reference end¢‚¬€œfoot trajectory with a ¢‚¬Ëœteardrop shape¢‚¬„¢ was acquired. Considering the design objectives, natural human walking and comfort, and other factors such as load capacity and weight of the device, the final design was determined. In order to satisfy the design objectives a kinematic synthesis, previously developed by one of the co-authors, is applied to test if the end¢‚¬€œfoot trajectory of the designed crutch substitute smoothly follows the desired reference, ¢‚¬Ëœteardrop shape¢‚¬„¢ in the vicinity of two specified task points, heel strike and toe off. A prototype of the final design was fabricated and its performance was tested by 2 mph treadmill walking. The research and developments made in this project with regard to mimicking the natural walking gait are important contributions that find applications in different areas, such as military, robotic locomotion, injury recovery and physical therapy.

Evaluating the Accuracy of Virtual Reality Trackers for Computing Spatiotemporal Gait Parameters.

Ageing, disease, and injuries result in movement defects that affect daily life. Gait analysis is a vital tool for understanding and evaluating these movement dysfunctions. In recent years, the use of virtual reality (VR) to observe motion and offer augmented clinical care has increased. Although VR-based methodologies have shown benefits in improving gait functions, their validity against more traditional methods (e.g., cameras or instrumented walkways) is yet to be established. In this work, we propose a procedure aimed at testing the accuracy and viability of a VIVE Virtual Reality system for gait analysis. Seven young healthy subjects were asked to walk along an instrumented walkway while wearing VR trackers. Heel strike (HS) and toe off (TO) events were assessed using the VIVE system and the instrumented walkway, along with stride length (SL), stride time (ST), stride width (SW), stride velocity (SV), and stance/swing percentage (STC, SWC%). Results from the VR were compared with the instrumented walkway in terms of detection offset for time events and root mean square error (RMSE) for gait features. An absolute offset between VR- and walkway-based data of (15.3 ± 12.8) ms for HS, (17.6 ± 14.8) ms for TOs and an RMSE of 2.6 cm for SW, 2.0 cm for SL, 17.4 ms for ST, 2.2 m/s for SV, and 2.1% for stance and swing percentage were obtained. Our findings show VR-based systems can accurately monitor gait while also offering new perspectives for VR augmented analysis.

Evaluation of Cement Paste Cylinder Preparation Methods for Mechanical Property Measurements

Abstract Testing cement paste (CP) cylinders for thermal, mechanical, or both properties has gained some recent traction, with thermal methods (e.g., the recently completed ASTM C1753) being more developed than mechanical property assessments. CP contains water, cementitious materials, and sometimes admixtures; no sand or aggregates. Currently there is no standard production method for CP cylinders. As such, the objectives of this article are to assess the variability of CP mechanical properties from multiple methods and then recommend a CP cylinder preparation method considering overall properties and variability. The recommended method prepares specimen tops in a similar manner to one common method for concrete cylinders (i.e., strike off the specimen top). The rationale for selecting this approach was this method produced essentially the same average compressive strength as existing approaches but with slightly less variability and no extra effort. The proposed method had compressive strength coefficients of variations of 17 % or less when specimens were tested within 0.5 hours of removal from moist curing. The proposed method is able to produce specimens with density and moisture content coefficients of variation of less than 1 %.

Wearable Sensor-Based Real-Time Gait Detection: A Systematic Review.

Gait analysis has traditionally been carried out in a laboratory environment using expensive equipment, but, recently, reliable, affordable, and wearable sensors have enabled integration into clinical applications as well as use during activities of daily living. Real-time gait analysis is key to the development of gait rehabilitation techniques and assistive devices such as neuroprostheses. This article presents a systematic review of wearable sensors and techniques used in real-time gait analysis, and their application to pathological gait. From four major scientific databases, we identified 1262 articles of which 113 were analyzed in full-text. We found that heel strike and toe off are the most sought-after gait events. Inertial measurement units (IMU) are the most widely used wearable sensors and the shank and foot are the preferred placements. Insole pressure sensors are the most common sensors for ground-truth validation for IMU-based gait detection. Rule-based techniques relying on threshold or peak detection are the most widely used gait detection method. The heterogeneity of evaluation criteria prevented quantitative performance comparison of all methods. Although most studies predicted that the proposed methods would work on pathological gait, less than one third were validated on such data. Clinical applications of gait detection algorithms were considered, and we recommend a combination of IMU and rule-based methods as an optimal solution.

Loading during midstance of gait is associated with tibiofemoral articular cartilage composition following anterior cruciate ligament reconstruction

Loading during midstance of gait is associated with tibiofemoral articular cartilage composition following anterior cruciate ligament reconstruction

The use of pedobarographic analysis to evaluate movement patterns in unstable total knee arthroplasty: A proof of concept study

BackgroundDefinition and clinical diagnosis of instability in TKA is challenging. Sensitive and objective biomechanical tools to aid diagnosis are currently lacking. This proof-of-concept study evaluates the use of pressure mat analyses to identify abnormal biomechanical loading patterns associated with TKA instability within an outpatient clinical setting. MethodsTwenty participants were examined: 10 patients with suspected unilateral TKA instability and 10 healthy controls. Participants underwent bilateral stance and gait tests measuring time and limb loading pressure parameters. Gait was divided into three phases: heel strike, mid-foot and toe off. Pressure recordings are expressed relative to bodyweight. Between-limb loading discrepancies were calculated in TKA patients and controls, and these differences were then compared between groups. Statistical significance was accepted at p < 0.05. ResultsTKA patients consistentlyoffloadedpressure away from the operated limb, whereas healthy controls exhibited more even limb loading throughout bilateral stance (p < 0.05). TKA patients exhibited greater discrepancy in overall step contact time between limbs (−0.09 s ± 0.16 s; p = 0.016) compared to controls (0.06 s ± 0.08 s; p = 0.04). Post-hoc tests showed significant between-group differences during midfoot (−0.04 s ± 0.07 s; p = 0.03) and toe-off (0.05 s ± 0.14 s; p = 0.013). Between-group differences in limb loading discrepancy were evident at heel strike (−9.24% ± 2.11%; p = 0.0166) and toe-off (−10.34% ± 5.51%; p = 0.0496). DiscussionPedobarographic measurements demonstrated differences in mechanical loading patterns in patients with TKA instability compared to healthy controls during functional tasks and warrants further investigation. This may prove to be a useful clinical diagnostic tool in identifying patients that would benefit from revision surgery or physical therapy.

Dysfunctional muscle activities and co-contraction in the lower-limb of lumbar disc herniation patients during walking

This study aimed to investigate lower-limb muscle activities in gait phases and co-contraction of one gait cycle in patients with lumbar disc herniation (LDH). This study enrolled 17 LDH patients and 17 sex- and age-matched healthy individuals. Bilateral muscle activities of the rectus femoris (RF), biceps femoris long head (BL), tibialis anterior (TA), and lateral gastrocnemius (LG) during walking were recorded. The gait cycle was divided into four phases by the heel strike and top off according to the kinematics tracks. Root mean square (RMS), mean frequency (MF), and co-contraction of surface electromyography signals were calculated. The LDH patients showed enhanced BL RMS during the single support phase (SS), second double support phase, and swing phase (SW) as well as decreased MF of RF during SS and of TA and LG during SW (p < 0.05). The co-contraction of the TA-LG was increased in LDH patients than in the control group (p < 0.05). Positive correlations were observed between TA-LG co-contraction (affected side, r = 0.557, p = 0.020; contralateral side, r = 0.627, p = 0.007) and the Oswestry disability index scores in LDH patients. LDH patients have increased BL firing rate and insufficient motor unit recruitment in specific phases in the lower limbs during walking. Dysfunction in LDH patients was associated with immoderate intermuscular co-contraction of the TA-LG during walking.

Effects of Hallux Valgus Orthoses on Ground Reaction Force Using 3D Motion Analysis in Individuals With Hallux Valgus Deformity

Background: Hallux valgus (HV) is a foot deformity developed by mediolateral deviation of the first metatarsophalangeal joint. Although various foot-toe orthoses were used to correct the HV angle, verification of the effects of kinetics variables such as ground reaction force (GRF) through three-dimensional (3D) gait analysis according to the various type of orthoses for HV is insufficient. Objects: This study aimed to investigate the effect of soft and hard types of foot and toe orthoses to correct HV deformity on the GRF in individuals with HV using 3D motion analysis system during walking. Methods: Twenty-six subjects participated in the experiment. Participants had HV angle of more than 15° in both feet. Two force platforms were used to obtain 3D GRF data for both feet and a 3D motion capture system with six infrared cameras was used to measure exact stance phase point such as heel strike or toe off period. Total walk trials of each participant were 8 to 10, the walkway length was 6 m. Two-way repeated measures ANOVA was used to determine the effects of each orthosis condition on the various GRF values. Results: The late anteroposterior maximal force and a first vertical peak force of the GRF showed that the hard type orthosis condition significantly increased GRF compared to the other orthosis conditions (p < 0.05). Conclusion: There were significant effects in GRF values when wearing the hard type foot orthosis. However, the hard type foot orthosis was uncomfortable to wear during walking. Therefore, it is necessary to develop a new foot-toe orthosis that can compensate for these disadvantages.

Relationship Between Body Composition and Balance Performance in Older Adults with Hyperkyphosis

Older adults with hyperkyphosis might have a high risk of falls since their whole body center of mass may shift to the boundary of the base of support. Body composition changes, such as low bone mineral content (BMC), decreased muscle mass, high body mass index (BMI), and increased fat mass are common in older adults with hyperkyphosis. This study aimed to investigate the relationship between body composition and balance performance using a biomechanical analysis in older adults with hyperkyphosis. Thirty older adults with hyperkyphosis were recruited. BMC, muscle mass, BMI, and fat mass were measured for body composition. Balance performances were determined with walking, quiet standing, and forward reach. Gait speed, step length, center of mass–center of pressure inclination angle of heel strike (Inc-HS) and toe off (Inc-TO) during walking, center of mass–center of pressure inclination angle during quiet standing (Inc-QS), and reaching distance were calculated. BMC had a moderately positive correlation with gait speed (r = 0.48, p < 0.01) and a moderately positive correlation with step length (r = 0.43, p = 0.01). Muscle mass had a moderately positive correlation with step length (r = 0.41, p = 0.02), moderately positive correlation with Inc-HS (r = 0.36, p = 0.04), and moderately positive correlation with reaching distance (r = 0.43, p = 0.01). No significant correlations were found among BMI, fat mass and balance performance. BMC and muscle mass should be considered as factors that might affect walking and forward reach in older adults with hyperkyphosis.

Analysis of foot plantar pressure behavior of children with obstetric brachial plexus paralysis

Definition and clinical diagnosis of instability in TKA is challenging. Sensitive and objective biomechanical tools to aid diagnosis are currently lacking. This proof-of-concept study evaluates the use of pressure mat analyses to identify abnormal biomechanical loading patterns associated with TKA instability within an outpatient clinical setting.Twenty participants were examined: 10 patients with suspected unilateral TKA instability and 10 healthy controls. Participants underwent bilateral stance and gait tests measuring time and limb loading pressure parameters. Gait was divided into three phases: heel strike, mid-foot and toe off. Pressure recordings are expressed relative to bodyweight. Between-limb loading discrepancies were calculated in TKA patients and controls, and these differences were then compared between groups. Statistical significance was accepted at p < 0.05.TKA patients consistently offloaded pressure away from the operated limb, whereas healthy controls exhibited more even limb loading throughout bilateral stance (p < 0.05). TKA patients exhibited greater discrepancy in overall step contact time between limbs (−0.09 s ± 0.16 s; p = 0.016) compared to controls (0.06 s ± 0.08 s; p = 0.04). Post-hoc tests showed significant between-group differences during midfoot (−0.04 s ± 0.07 s; p = 0.03) and toe-off (0.05 s ± 0.14 s; p = 0.013). Between-group differences in limb loading discrepancy were evident at heel strike (−9.24% ± 2.11%; p = 0.0166) and toe-off (−10.34% ± 5.51%; p = 0.0496).Pedobarographic measurements demonstrated differences in mechanical loading patterns in patients with TKA instability compared to healthy controls during functional tasks and warrants further investigation. This may prove to be a useful clinical diagnostic tool in identifying patients that would benefit from revision surgery or physical therapy.