A Novel Video-Based Methodology for Automated Classification of Dystonia and Choreoathetosis in Dyskinetic Cerebral Palsy During a Lower Extremity Task.

BACKGROUND: Movement disorders in children and adolescents with dyskinetic cerebral palsy (CP) are commonly assessed from video recordings, however scoring is time-consuming and expert knowledge is required for an appropriate assessment. OBJECTIVE: To explore a machine learning approach for automated classification of amplitude and duration of distal leg dystonia and choreoathetosis within short video sequences. METHODS: Available videos of a heel-toe tapping task were preprocessed to optimize key point extraction using markerless motion analysis. Postprocessed key point data were passed to a time series classification ensemble algorithm to classify dystonia and choreoathetosis duration and amplitude classes (scores 0, 1, 2, 3, and 4), respectively. As ground truth clinical scoring of dystonia and choreoathetosis by the Dyskinesia Impairment Scale was used. Multiclass performance metrics as well as metrics for summarized scores: absence (score 0) and presence (score 1-4) were determined. RESULTS: Thirty-three participants were included: 29 with dyskinetic CP and 4 typically developing, age 14 years:6 months ± 5 years:15 months. The multiclass accuracy results for dystonia were 77% for duration and 68% for amplitude; for choreoathetosis 30% for duration and 38% for amplitude. The metrics for score 0 versus score 1 to 4 revealed an accuracy of 81% for dystonia duration, 77% for dystonia amplitude, 53% for choreoathetosis duration and amplitude. CONCLUSIONS: This methodology study yielded encouraging results in distinguishing between presence and absence of dystonia, but not for choreoathetosis. A larger dataset is required for models to accurately represent distinct classes/scores. This study presents a novel methodology of automated assessment of movement disorders solely from video data.

Eat-Radar: Continuous Fine-Grained Intake Gesture Detection Using FMCW Radar and 3D Temporal Convolutional Network With Attention.

Unhealthy dietary habits are considered as the primary cause of various chronic diseases, including obesity and diabetes. The automatic food intake monitoring system has the potential to improve the quality of life (QoL) of people with diet-related diseases through dietary assessment. In this work, we propose a novel contactless radar-based approach for food intake monitoring. Specifically, a Frequency Modulated Continuous Wave (FMCW) radar sensor is employed to recognize fine-grained eating and drinking gestures. The fine-grained eating/drinking gesture contains a series of movements from raising the hand to the mouth until putting away the hand from the mouth. A 3D temporal convolutional network with self-attention (3D-TCN-Att) is developed to detect and segment eating and drinking gestures in meal sessions by processing the Range-Doppler Cube (RD Cube). Unlike previous radar-based research, this work collects data in continuous meal sessions (more realistic scenarios). We create a public dataset comprising 70 meal sessions (4,132 eating gestures and 893 drinking gestures) from 70 participants with a total duration of 1,155 minutes. Four eating styles (fork & knife, chopsticks, spoon, hand) are included in this dataset. To validate the performance of the proposed approach, seven-fold cross-validation method is applied. The 3D-TCN-Att model achieves a segmental F1-score of 0.896 and 0.868 for eating and drinking gestures, respectively. The results of the proposed approach indicate the feasibility of using radar for fine-grained eating and drinking gesture detection and segmentation in meal sessions.

Effectiveness of wheeled mobility skill interventions in children and young people with cerebral palsy: A systematic review.

AIM: To systematically review the effectiveness of wheeled mobility interventions in children and young people with cerebral palsy (CP). METHOD: A systematic literature search was performed in MEDLINE, Embase, Cochrane Central Register of Controlled Trials, EBSCO, PEDro, and Web of Science using database-specific concepts such as 'child' and 'wheelchair'. Studies focusing on wheeled mobility skill interventions with participants aged 6 to 21 years with CP were included. RESULTS: Twenty studies with 203 participants were included. The impact of wheeled mobility skill interventions was assessed on mobility skills (n = 18), activity and participation (n = 10), and quality of life (n = 3). No studies reported effects on stress, fatigue, and motivational aspects. Interventions included power wheelchair skill training (n = 12), computer-based training (n = 5), smart wheelchair training (n = 2), and manual wheelchair training (n = 1), showing positive wheeled mobility intervention effects. Study quality based on the Methodological Index for Non-Randomized Studies scale was 9 out of 16 and 14 out of 24 for non-comparative and comparative studies respectively. Risk of bias was serious-to-critical on the Risk of Bias in Non-Randomized Studies of Interventions. INTERPRETATION: Wheeled mobility interventions showed promising beneficial effects on wheeled mobility, activity and participation, and quality of life for children and young people with CP. Future studies with structured and standardized training programmes and assessment tools are warranted to further accelerate the wheeled mobility skill acquisition process in this population. WHAT THIS PAPER ADDS: Wheeled mobility interventions improve wheeled mobility skills in individuals with cerebral palsy. The mobility skill acquisition process benefits from structured and standardized training. Knowledge of the intervention effects on participation and quality of life is limited. Most studies had moderate quality of evidence because of methodological limitations.

Drinking Gesture Detection Using Wrist-Worn IMU Sensors with Multi-Stage Temporal Convolutional Network in Free-Living Environments.

Maintaining adequate hydration is important for health. Inadequate liquid intake can cause dehydration problems. Despite the increasing development of liquid intake monitoring, there are still open challenges in drinking detection under free-living conditions. This paper proposes an automatic liquid intake monitoring system comprised of wrist-worn Inertial Measurement Units (IMU s) to recognize drinking gesture in free-living environments. We build an end-to-end approach for drinking gesture detection by employing a novel multi-stage temporal convolutional network (MS-TCN). Two datasets are collected in this research, one contains 8.9 hours data from 13 participants in semi-controlled environments, the other one contains 45.2 hours data from 7 participants in free-living environments. The Leave-One-Subject-Out (LOSO) evaluation shows that this method achieves a segmental F1-score of 0.943 and 0.900 in the semi-controlled and free-living datasets, respectively. The results also indicate that our approach outperforms the convolutional neural network and long-short-term-memory network combined model (CNN-LSTM) on our datasets. The dataset used in this paper is available at https://github.com/Pituohai/drinking-gesture-dataset/. Clinical Relevance- This automatic liquid intake monitoring system can detect drinking gesture in daily life. It has the potential to be used to record the frequency of drinking water for at-risk elderly or patients in the hospital.

Eye movements and stress during eye-tracking gaming performance in children with dyskinetic cerebral palsy.

AIM: This study aimed to explore eye movements and stress during eye-tracking gaming performance in children with dyskinetic cerebral palsy (CP) compared with typically developing children, and associations between eye-tracking performance, eye movements, stress, and participants' characteristics. METHOD: This cohort study included 12 children with dyskinetic CP aged 5 to 12 years (mean age 8 years 7 months, standard deviation [SD] 2 years 3 months) and 23 typically developing children aged 5 to 13 years (mean age 9 years 0 months, SD 2 years 7 months). Participants played 10 eye-tracking games. Tobii X3-120 and Tobii Pro Lab were used to record and analyse eye movements. Stress was assessed through heart rate variability (HRV), recorded during rest, and eye-tracking performance using the Bittium Faros360° ECG Holter device. Eye-tracking performance was measured using gaming completion time. Fixation and saccade variables were used to quantify eye movements, and time- and frequency-domain variables to quantify HRV. Non-parametric statistics were used. RESULTS: Gaming completion time was significantly different (p < 0.001) between groups, and it was negatively correlated with experience (rs  = -0.63, p = 0.029). No significant differences were found between groups in fixation and saccade variables. HRV significantly changed from rest to eye-tracking performance only in typically developing children and not in children with dyskinetic CP. INTERPRETATION: Children with dyskinetic CP took longer to perform the 10 games, especially the inexperienced users, indicating the importance of the early provision of eye-tracking training opportunities. It seems that eye-tracking tasks are not a source of increased stress and effort in children with dyskinetic CP. WHAT THIS PAPER ADDS: Participants with dyskinetic cerebral palsy (CP) took twice as long to perform 10 eye-tracking games than typically developing peers. Participants with dyskinetic CP with previous eye-tracking experience performed the games faster. Fixation and saccade variables were not significantly different between children with and without dyskinetic CP. Heart rate variability showed no differences between rest and performance in participants with dyskinetic CP. Gross Motor Function Classification System, Manual Ability Classification System, and Viking Speech Scale levels were not correlated to the eye movements or stress variables.

Exercise load and physical activity intensity in relation to dystonia and choreoathetosis during powered wheelchair mobility in children and youth with dyskinetic cerebral palsy.

PURPOSE: To explore the relation between exercise load, physical activity intensity, and movement disorders during powered wheelchair (PW) mobility in people with severe dyskinetic cerebral palsy (DCP). METHODS: Ten participants with DCP, 6-21 years old, users of a head/foot steering system were included. Dystonia and choreoathetosis were assessed using the Dyskinesia Impairment Mobility Scale (DIMS), heart rate (HR) was used to assess the exercise load of the tasks on the participants, and the accelerometry-based activity index (AI) to measure the physical activity intensity and energy expenditure during mobility task performance. RESULTS: Neck- and distal arm dystonia showed significant correlations with HR (0.64 < rs < 0.77; 0.009 < p < 0.048), whereas neck- and proximal arm choreoathetosis with AI (0.64 < rs < 0.76, 0.011 < p < 0.044). Total-body AI was strongly correlated to the AI of the arms (0.66 < rs < 0.90, < 0.001 < p < 0.038), but not to the AI of the head. CONCLUSIONS: During PW mobility tasks, dystonia is associated to exercise load and choreoathetosis to physical activity intensity and energy expenditure. Findings highlight the difficulties in measuring exercise load and activity intensity in PW users with DCP due to the involuntary hypertonic and/or hyperkinetic hallmark of the movement disorders. Nevertheless, a relaxed surrounding with minimal distractions during PW training may increase learning efficiency. Future studies with a bigger sample size are highly recommended to fully establish the relationship between the variables and to allow generalizability of results.Implications for rehabilitationDystonia is positively related to heart rate during powered mobility, which may be explained by the hypertonic hallmark of dystonia causing an increase in exercise load.Choreoathetosis is positively related to the physical activity index during powered mobility where the hyperkinetic hallmark of choreoathetosis may lead to an increase in physical activity intensity and energy expenditure.Arm overflow movements are the component which contribute the most to total-body activity index, thus, minimizing these movements may lower the overall energy expenditure during powered mobility.Mobility training in a relaxed surrounding with minimal distractions and minimized arm overflow movements may lead to a less-demanding powered wheelchair mobility experience and increased learning efficiency.

Gestational weight gain prediction using privacy preserving federated learning.

Gestational weight gain prediction in expecting women is associated with multiple risks. Manageable interventions can be devised if the weight gain can be predicted as early as possible. However, training the model to predict such weight gain requires access to centrally stored privacy sensitive weight data. Federated learning can help mitigate this problem by sending local copies of trained models instead of raw data and aggregate them at the central server. In this paper, we present a privacy preserving federated learning approach where the participating users collaboratively learn and update the global model. Furthermore, we show that this model updation can be done incrementally without having the need to store the local updates eternally. Our proposed model achieves a mean absolute error of 4.455 kgs whilst preserving privacy against 2.572 kgs achieved in a centralised approach utilising individual training data until day 140.Clinical relevance- Privacy preserving training of machine learning algorithm for early gestational weight gain prediction with minor tradeoff to performance.

In-vitro validation of inertial-sensor-to-bone alignment.

A major shortcoming in kinematic estimation using skin-attached inertial sensors is the alignment of sensor-embedded and segment-embedded coordinate systems. Only a correct alignment results in clinically relevant kinematics. Model-based inertial-sensor-to-bone alignment methods relate inertial sensor measurements with a model of the joint. Therefore, they do not rely on properly executed calibration movements or a correct sensor placement. However, it is unknown how accurate such model-based methods align the sensor axes and the underlying segment-embedded axes, as defined by clinical definitions. Also, validation of the alignment models is challenging, since an optical motion capture ground truth can be prone to disturbances from soft tissue movement, orientation estimation and manual palpation errors. We present an anatomical tibiofemoral ground truth on an unloaded cadaveric measurement set-up that intrinsically overcomes these disturbances. Additionally, we validate existing model-based alignment strategies. Modeling the degrees of freedom leads to the identification of rotation axes. However, there is no reason why these axes would align with the segment-embedded axes. Relative inertial-sensor orientation information and rich arbitrary movements showed to aid in identifying the underlying joint axes. The first dominant sagittal rotation axis aligned sufficiently well with the underlying segment-embedded reference. The estimated axes that relate to secondary kinematics tend to deviate from the underlying segment-embedded axes as much as their expected range of motion around the axes. In order to interpret the secondary kinematics, the alignment model should more closely match the biomechanics of the joint.

Reference in-vitro dataset for inertial-sensor-to-bone alignment applied to the tibiofemoral joint.

Skin-attached inertial sensors are increasingly used for kinematic analysis. However, their ability to measure outside-lab can only be exploited after correctly aligning the sensor axes with the underlying anatomical axes. Emerging model-based inertial-sensor-to-bone alignment methods relate inertial measurements with a model of the joint to overcome calibration movements and sensor placement assumptions. It is unclear how good such alignment methods can identify the anatomical axes. Any misalignment results in kinematic cross-talk errors, which makes model validation and the interpretation of the resulting kinematics measurements challenging. This study provides an anatomically correct ground-truth reference dataset from dynamic motions on a cadaver. In contrast with existing references, this enables a true model evaluation that overcomes influences from soft-tissue artifacts, orientation and manual palpation errors. This dataset comprises extensive dynamic movements that are recorded with multimodal measurements including trajectories of optical and virtual (via computed tomography) anatomical markers, reference kinematics, inertial measurements, transformation matrices and visualization tools. The dataset can be used either as a ground-truth reference or to advance research in inertial-sensor-to-bone-alignment.

Optimizing the Bluetooth Low-Energy Service Discovery Process.

Bluetooth Low Energy (BLE), a short-range and low-power communication protocol, has gained a lot of popularity in recent years. A part of BLE is the Generic Attribute Profile (GATT) which defines the data communication between two devices. During the initial connection between two BLE devices a discovery of services, characteristics and descriptors is required for the GATT to operate. During this discovery phase, the device is unusable as it builds the foundation for further data transactions. When unoptimized, this discovery step can take up to a few seconds, leading to frustrations for the end user or delays in some applications. In this paper, we aim to find guidelines on how to optimize this discovery process. A simulation framework was developed, able to simulate and analyze the packet exchange of the service discovery, while taking link layer parameters into account. The results show that minimizing the connection interval and maximizing the data length leads to the lowest discovery times. Practical experiments in real environment, however, show that the theoretically calculated times are not reachable due to processing overhead and retransmissions. Theoretical results also show that the current BLE discovery process, even after optimizations, has a lot of overhead. To fix the problems with the current protocol, this paper proposes a new Rapid Service Discovery Protocol, which enables a fast and efficient service discovery.

Bluetooth Low Energy Interference Awareness Scheme and Improved Channel Selection Algorithm for Connection Robustness.

Bluetooth Low Energy (BLE) is a popular wireless communication protocol heavily used in Internet of Things applications. Nowadays, robustness is considered a key requirement in wireless communication. However, radio interference from various sources may affect the performance of BLE devices, leading to channel congestion. Therefore, there is a broadly recognized need of methodologies capable of sensing and avoiding interference. In this paper, two improvements at the data link layer for interference detection and channel selection are proposed to enhance the BLE connection robustness. This paper also presents a wide range of experimental evaluations aiming at validating the improvements and providing insights on both these improvements. Particularly, the communication performance of the BLE link layer is assessed in terms of channel usage distribution, supervision timeout ratio (STR) and packet loss rate (PLR) under different interference environments. Results from these experiments (reliability over 97% and 99% under two different harsh environments) highlight the effects of both improvements on the BLE robustness. Meanwhile, the authority of scheduling the whole mechanism is given to the link layer and even the higher application layer. This paper provides a set of solutions for BLE confronting interference in link layer.

Dystonia and choreoathetosis presence and severity in relation to powered wheelchair mobility performance in children and youth with dyskinetic cerebral palsy.

INTRODUCTION: Power wheelchairs (PW) with head/foot steering systems are used as an alternative to joysticks in children with severe dyskinetic cerebral palsy (DCP). Mobility training programs are unstandardized to date, and insight on dystonia, choreoathetosis, and mobility performance may lead to greater independent mobility. OBJECTIVE: To map the presence and severity of dystonia and choreoathetosis during PW mobility in DCP and their relation with mobility performance. METHODS: Ten participants with DCP performed four PW mobility tasks using a head/foot steering system. Dystonia and choreoathetosis in the neck and arm regions were evaluated using the Dyskinesia Impairment Mobility Scale (DIMS). PW mobility performance was assessed using time-on-task and the number of errors during performance. The Wilcoxon-signed rank test and the Spearman's correlation coefficients were used to explore differences and correlations. RESULTS: Median levels of dystonia (83.6%) were significantly higher (p < 0.01) than median levels of choreoathetosis (34.4%). Positive significant correlations were found between the Arm Proximal DIMS and the PW mobility experience (rs=-0.92, p < 0.001), and between the Arm Distal DIMS and the number of errors (rs = 0.66, p = 0.039) during mobility performance. CONCLUSIONS: Dystonia is more present and severe during PW mobility than choreoathetosis. The hypertonic hallmark of dystonia may mask the hyperkinetic hallmark of choreoathetosis, resulting in lower median levels. Results may suggest that with an increase in driving experience, children with DCP adopt deliberate strategies to minimize the negative impact of arm overflow movements on mobility performance, however, future research with bigger sample size and additional outcome measures is strongly encouraged.

Eye Gaze Gaming Intervention in Children with Dyskinetic Cerebral Palsy: A Pilot Study of Task Performance and Its Relation with Dystonia and Choreoathetosis.

OBJECTIVES: To investigate the operational competences screen navigation and dwell function underlying eye gaze performance, and the relation of dystonia and choreoathetosis with eye gaze performance in children with dyskinetic cerebral palsy (DCP). METHODS: During a 5-week intervention, ten participants with DCP played eye gaze video games daily for 30 minutes. Six games were used to assess task performance, fixation count, and eye movement accuracy during four measurements. Dystonia and choreoathetosis were evaluated using the Dyskinesia Impairment Scale. RESULTS: Eye gaze performance improved over time (p = .013). Moderate to strong within-subject correlations were found between eye movement accuracy and task performance, and between eye movement accuracy and fixation count. No significant correlations were found with the movement disorders. CONCLUSIONS: Eye gaze technology shows great potential to be a successful computer interface for children with severe DCP, thereby potentially improving their communication skills, participation levels, and quality of life.

High Levels of Kinesiophobia at Discharge from the Hospital May Negatively Affect the Short-Term Functional Outcome of Patients Who Have Undergone Knee Replacement Surgery.

BACKGROUND: Kinesiophobia is a psycho-cognitive factor that hampers recovery after orthopedic surgery. No evidence exists on the influence of kinesiophobia on the short-term recovery of function in patients with knee replacement (KR). Therefore, the aim of the present study is to investigate the impact of kinesiophobia on short-term patient-reported outcomes (PROMs) and performance-based measures (PBMs). METHODS: Forty-three KR patients filled in the Tampa scale for kinesiophobia (TSK) at time of discharge. Patients with TSK ≥ 37 were allocated to the kinesiophobia group (n = 24), others to the no-kinesiophobia group (n = 19). Patients were asked to complete PROMs and to execute PBMs at discharge and at 6-weeks follow-up. An independent samples t-test was used to compare group differences for PROMs and PBMs at both measurement sessions. Multiple linear regression analysis models were used to model PBM outcomes from age, pain and TSK scores. RESULTS: Significant differences were observed between groups for PROMs and PBMs. Kinesiophobia significantly contributed to the reduced functional outcomes. CONCLUSION: At discharge from the hospital, 55.8% of KR patients demonstrated high levels of kinesiophobia (TSK ≥ 37). This may negatively influence short-term recovery of these patients, by putting them at higher risk for falling and reduced functionality.

A Novel Method to Estimate the Full Knee Joint Kinematics Using Low Cost IMU Sensors for Easy to Implement Low Cost Diagnostics.

Traditional motion capture systems are the current standard in the assessment of knee joint kinematics. These systems are, however, very costly, complex to handle, and, in some conditions, fail to estimate the varus/valgus and internal/external rotation accurately due to the camera setup. This paper presents a novel and comprehensive method to infer the full relative motion of the knee joint, including the flexion/extension, varus/valgus, and internal/external rotation, using only low cost inertial measurement units (IMU) connected to the upper and lower leg. Furthermore, sensors can be placed arbitrarily and only require a short calibration, making it an easy-to-use and portable clinical analysis tool. The presented method yields both adequate results and displays the uncertainty band on those results to the user. The proposed method is based on an fixed interval smoother relying on a simple dynamic model of the legs and judicially chosen constraints to estimate the rigid body motion of the leg segments in a world reference frame. In this pilot study, benchmarking of the method on a calibrated robotic manipulator, serving as leg analogue, and comparison with camera-based techniques confirm the method's accurateness as an easy-to-implement, low-cost clinical tool.

Inertial Sensor-Based Lower Limb Joint Kinematics: A Methodological Systematic Review.

The use of inertial measurement units (IMUs) has gained popularity for the estimation of lower limb kinematics. However, implementations in clinical practice are still lacking. The aim of this review is twofold-to evaluate the methodological requirements for IMU-based joint kinematic estimation to be applicable in a clinical setting, and to suggest future research directions. Studies within the PubMed, Web Of Science and EMBASE databases were screened for eligibility, based on the following inclusion criteria: (1) studies must include a methodological description of how kinematic variables were obtained for the lower limb, (2) kinematic data must have been acquired by means of IMUs, (3) studies must have validated the implemented method against a golden standard reference system. Information on study characteristics, signal processing characteristics and study results was assessed and discussed. This review shows that methods for lower limb joint kinematics are inherently application dependent. Sensor restrictions are generally compensated with biomechanically inspired assumptions and prior information. Awareness of the possible adaptations in the IMU-based kinematic estimates by incorporating such prior information and assumptions is necessary, before drawing clinical decisions. Future research should focus on alternative validation methods, subject-specific IMU-based biomechanical joint models and disturbed movement patterns in real-world settings.

Measuring and Localizing Individual Bites Using a Sensor Augmented Plate During Unrestricted Eating for the Aging Population.

Food intake monitoring can play an important role in the prevention of malnutrition in the aging population, but traditional tools may not be adequate for use in this target group. These tools typically involve the use of questionnaires or food diaries that require manual data entry. Due to their time-consuming nature, they are often incomplete, contain mistakes, or not used at all. An alternative to self-reporting tools, in the form of a plate system that automatically measures the consumed food during the meal, is presented in this paper. Furthermore, the system can estimate the location where each bite was taken on the plate. The system is compatible with an off-the-shelf plate that is mounted on top of a base station. Weight sensors are integrated in the base, allowing for easy removal and cleaning of the plate. Localization of bites is done by looking at the movement of the center of mass during eating. When used with a compartmentalized plate, the amount of consumed food per compartment can be measured. With prior knowledge of the type of food in each compartment, this can give an indication of calories and nutritional intake. We present a bite detection algorithm using a random forest decision tree classifier. Data from 24 aging adults (ages 52-95) eating a single meal with chopsticks was used to train and evaluate the model. Out of a total of 836 true annotated bites, the algorithm detected 602 with a precision and recall of 0.78 and 0.76, respectively. By summing the weights of detected bites from each compartment, the algorithm was able to estimate the amount of food taken per compartment with an average error of (8 ±8)% of the portion size.

Development of a Data Logger for Capturing Human-Machine Interaction in Wheelchair Head-Foot Steering Sensor System in Dyskinetic Cerebral Palsy.

The use of data logging systems for capturing wheelchair and user behavior has increased rapidly over the past few years. Wheelchairs ensure more independent mobility and better quality of life for people with motor disabilities. Especially, for people with complex movement disorders, such as dyskinetic cerebral palsy (DCP) who lack the ability to walk or to handle objects, wheelchairs offer a means of integration into daily life. The mobility of DCP patients is based on a head-foot wheelchair steering system. In this work, a data logging system is proposed to capture data from human-wheelchair interaction for the head-foot steering system. Additionally, the data logger provides an interface to multiple Inertial Measurement Units (IMUs) placed on the body of the wheelchair user. The system provides accurate and real-time information from head-foot navigation system pressure sensors on the wheelchair during driving. This system was used as a tool to obtain further insights into wheelchair control and steering behavior of people diagnosed with DCP in comparison with a healthy subject.

Lower extremity gait kinematics outcomes after knee replacement demonstrate arthroplasty-specific differences between unicondylar and total knee arthroplasty: A pilot study.

BACKGROUND: The aim of the present study is to compare sagittal gait kinematics of ankle, knee and hip joints between subjects with unicondylar and total knee arthroplasty and age matched healthy controls. Since unicondylar knee replacement is a less invasive procedure, which more closely preserves knee joint anatomy, we hypothesized that one year post unicondylar knee arthroplasty patients would demonstrate more normal gait patterns than patients with total knee arthroplasty. RESEARCH QUESTION: Do unicondylar and total knee arthroplasty patients display similar gait kinematics one year after surgery? METHODS: Fourteen subjects (8 posterior stabilized and 6 medial unicondylar knee replacements) that were one year post surgery, and 6 healthy control subjects underwent a 3D gait analysis and a physical examination (range of motion, muscle strength). Statistical parametric mapping was used to compare gait kinematics of the lower limbs between groups. Additionally, differences in peak angles and clinical outcomes were assessed using a one-way ANOVA between subjects analysis. RESULTS: Both knee replacement groups showed reduced knee flexion range of motion and reduced muscle strength at the operated leg compared to the control group. Subjects with TKA demonstrated reduced knee flexion at loading response and midstance of the gait cycle. Both UKA and TKA demonstrated significantly less knee flexion during swing. SIGNIFICANCE: The results of this study demonstrate arthroplasty-specific differences in muscle strength, range of motion and gait kinematics of the lower limb one year after knee surgery. Future planning of post-surgery follow-up should addresses these arthroplasty-specific weaknesses and gait deviations.

Hip and knee kinematics of the forward lunge one year after unicondylar and total knee arthroplasty.

Patients with unicondylar knee arthroplasty (UKA) report higher functionality compared to those with total knee arthroplasty (TKA). However, these patients should also be assessed during more demanding tasks in order to appreciate their true functionality. The forward lunge (FL) is a motor task commonly used in clinics to evaluate functional recovery after knee replacement surgery. Unfortunately, clear evidence comparing FL kinematics between patients with UKA and TKA is still missing. The purpose of this study was to compare hip and knee joint kinematics during the FL between patients with UKA, TKA and controls. Twenty subjects (8 TKA, 6 UKA, 6 controls) underwent 3D motion analysis during a FL. Differences in hip and knee kinematics between groups were identified using statistical parametric mapping. We concluded that patients with TKA demonstrated reduced knee and hip flexion angles during the loaded phase of the FL, which could have been an attempt to unload the knee joint. This is in contrast to patients with UKA, who showed similar knee and hip joint kinematics compared to controls throughout the entire FL. It seems that retaining the cruciate ligaments is beneficial for the execution of a complex motor task such as the FL.