Assessment of changes in gait parameters and vertical ground reaction forces after total hip arthroplasty

Stepping Beyond Counts in Recovery of Total Hip Arthroplasty: A Prospective Study on Passively Collected Gait Metrics

Gait quality parameters have been used to measure recovery from total hip arthroplasty (THA) but are time-intensive and previously could only be performed in a lab. Smartphone sensor data and algorithmic advances presently allow for the passive collection of qualitative gait metrics. The purpose of this prospective study was to observe the recovery of physical function following THA by assessing passively collected pre- and post-operative gait quality metrics. This was a multicenter, prospective cohort study. From six weeks pre-operative through to a minimum 24 weeks post-operative, 612 patients used a digital care management application that collected gait metrics. Average weekly walking speed, step length, timing asymmetry, and double limb support percentage pre- and post-operative values were compared with a paired-sample t-test. Recovery was defined as the post-operative week when the respective gait metric was no longer statistically inferior to the pre-operative value. To control for multiple comparison error, significance was set at p < 0.002. Walking speeds and step length were lowest, and timing asymmetry and double support percentage were greatest at week two post-post-operative (p < 0.001). Walking speed (1.00 ± 0.14 m/s, p = 0.04), step length (0.58 ± 0.06 m/s, p = 0.02), asymmetry (14.5 ± 19.4%, p = 0.046), and double support percentage (31.6 ± 1.5%, p = 0.0089) recovered at 9, 8, 7, and 10 weeks post-operative, respectively. Walking speed, step length, asymmetry, and double support all recovered beyond pre-operative values at 13, 17, 10, and 18 weeks, respectively (p < 0.002). Functional recovery following THA can be measured via passively collected gait quality metrics using a digital care management platform. The data suggest that metrics of gait quality are most negatively affected two weeks post-operative; recovery to pre-operative levels occurs at approximately 10 weeks following primary THA, and follows a slower trajectory compared to previously reported step count recovery trajectories.

Stepping beyond Counts in Recovery of Total Knee Arthroplasty: A Prospective Study on Passively Collected Gait Metrics

Advances in algorithms developed from sensor-based technology data allow for the passive collection of qualitative gait metrics beyond step counts. The purpose of this study was to evaluate pre- and post-operative gait quality data to assess recovery following primary total knee arthroplasty. This was a multicenter, prospective cohort study. From 6 weeks pre-operative through to 24 weeks post-operative, 686 patients used a digital care management application to collect gait metrics. Average weekly walking speed, step length, timing asymmetry, and double limb support percentage pre- and post-operative values were compared with a paired-samples t-test. Recovery was operationally defined as when the respective weekly average gait metric was no longer statistically different than pre-operative. Walking speed and step length were lowest, and timing asymmetry and double support percentage were greatest at week two post-operative (p < 0.0001). Walking speed recovered at 21 weeks (1.00 m/s, p = 0.063) and double support percentage recovered at week 24 (32%, p = 0.089). Asymmetry percentage was recovered at 13 weeks (14.0%, p = 0.23) and was consistently superior to pre-operative values at week 19 (11.1% vs. 12.5%, p < 0.001). Step length did not recover during the 24-week period (0.60 m vs. 0.59 m, p = 0.004); however, this difference is not likely clinically relevant. The data suggests that gait quality metrics are most negatively affected two weeks post-operatively, recover within the first 24-weeks following TKA, and follow a slower trajectory compared to previously reported step count recoveries. The ability to capture new objective measures of recovery is evident. As more gait quality data is accrued, physicians may be able to use passively collected gait quality data to help direct post-operative recovery using sensor-based care pathways.

Optimal locations and computational frameworks of FSR and IMU sensors for measuring gait abnormalities

Neuromuscular diseases cause abnormal joint movements and drastically alter gait patterns in patients. The analysis of abnormal gait patterns can provide clinicians with an in-depth insight into implementing appropriate rehabilitation therapies. Wearable sensors are used to measure the gait patterns of neuromuscular patients due to their non-invasive and cost-efficient characteristics. FSR and IMU sensors are the most popular and efficient options. When assessing abnormal gait patterns, it is important to determine the optimal locations of FSRs and IMUs on the human body, along with their computational framework. The gait abnormalities of different types and the gait analysis systems based on IMUs and FSRs have therefore been investigated. After studying a variety of research articles, the optimal locations of the FSR and IMU sensors were determined by analysing the main pressure points under the feet and prime anatomical locations on the human body. A total of seven locations (the big toe, heel, first, third, and fifth metatarsals, as well as two close to the medial arch) can be used to measure gate cycles for normal and flat feet. It has been found that IMU sensors can be placed in four standard anatomical locations (the feet, shank, thigh, and pelvis). A section on computational analysis is included to illustrate how data from the FSR and IMU sensors are processed. Sensor data is typically sampled at 100 Hz, and wireless systems use a range of microcontrollers to capture and transmit the signals. The findings reported in this article are expected to help develop efficient and cost-effective gait analysis systems by using an optimal number of FSRs and IMUs.

Validation of inertial measurement units with optical tracking system in patients operated with Total hip arthroplasty

Background

Patient reported outcome measurement (PROMs) will not capture in detail the functional joint motion before and after total hip arthroplasty (THA). Therefore, methods more specifically aimed to analyse joint movements may be of interest. An analysis method that addresses these issues should be readily accessible and easy to use especially if applied to large groups of patients, who you want to study both before and after a surgical intervention such as THA. Our aim was to evaluate the accuracy of inertial measurement units (IMU) by comparison with an optical tracking system (OTS) to record pelvic tilt, hip and knee flexion in patients who had undergone THA.

Methods

49 subjects, 25 males 24 females, mean age of 73 years (range 51–80) with THA participated. All patients were measured with a portable IMU system, with sensors attached lateral to the pelvis, the thigh and the lower leg. For validation, a 12-camera motion capture system was used to determine the positions of 15 skin markers (Oqus 4, Qualisys AB, Sweden). Comparison of sagittal pelvic rotations, and hip and knee flexion-extension motions measured with the two systems was performed. The mean values of the IMU’s on the left and right sides were compared with OTS data.

Results

The comparison between the two gait analysis methods showed no significant difference for mean pelvic tilt range (4.9–5.4 degrees) or mean knee flexion range (54.4–55.1 degrees) on either side (p > 0.7). The IMU system did however record slightly less hip flexion on both sides (36.7–37.7 degrees for the OTS compared to 34.0–34.4 degrees for the IMU, p < 0.001).

Conclusions

We found that inertial measurement units can produce valid kinematic data of pelvis- and knee flexion-extension range. Slightly less hip flexion was however recorded with the inertial measurement units which may be due to the difference in the modelling of the pelvis, soft tissue artefacts, and malalignment between the two methods or misplacement of the inertial measurement units.

Trial registration

The study has ethical approval from the ethical committee “Regionala etikprövningsnämnden i Göteborg” (Dnr: 611–15, 2015-08-27) and all study participants have submitted written approval for participation in the study.

Biomechanical changes and recovery of gait function after total hip arthroplasty for osteoarthritis: a systematic review and meta-analysis

OBJECTIVE

To determine the change in walking gait biomechanics after total hip arthroplasty (THA) for osteoarthritis (OA) compared to the pre-operative gait status, and to compare the recovery of gait following THA with healthy individuals.

METHODS

Systematic review with meta-analysis of studies investigating changes in gait biomechanics after THA compared to (1) preoperative levels and (2) healthy individuals. Data were pooled at commonly reported time points and standardised mean differences (SMDs) were calculated in meta-analyses for spatiotemporal, kinematic and kinetic parameters.

RESULTS

Seventy-four studies with a total of 2,477 patients were included. At 6 weeks postoperative, increases were evident for walking speed (SMD: 0.32, 95% confidence intervals (CI) 0.14, 0.50), stride length (SMD: 0.40, 95% CI 0.19, 0.61), step length (SMD: 0.41, 95% CI 0.23, 0.59), and transverse plane hip range of motion (ROM) (SMD: 0.36, 95% CI 0.05, 0.67) compared to pre-operative gait. Sagittal, coronal and transverse hip ROM was significantly increased at 3 months (SMDs: 0.50 to 1.07). At 12 months postoperative, patients demonstrated deficits compared with healthy individuals for walking speed (SMD: -0.59, 95% CI -1.08 to -0.11), stride length (SMD: -1.27, 95% CI -1.63, -0.91), single limb support time (SMD: -0.82, 95% CI -1.23, -0.41) and sagittal plane hip ROM (SMD: -1.16, 95% CI -1.83, -0.49). Risk of bias scores ranged from seven to 24 out of 26.

CONCLUSIONS

Following THA for OA, early improvements were demonstrated for spatiotemporal and kinematic gait patterns compared to the pre-operative levels. Deficits were still observed in THA patients compared to healthy individuals at 12 months.

Gait and gait-related activities of daily living after total hip arthroplasty: a systematic review

BACKGROUND

Differences in the performance of gait and gait-related activities of daily living are known to persist after total hip arthroplasty compared to healthy controls, but the specific underlying deficits (spatiotemporal, kinematics and kinetics) are not completely understood. This review aimed to map the differences between patients and controls, and between the operated and non-operated limbs during various activities of daily living.

METHODS

A computerized search with broad search terms was performed in the MEDLINE database. Primary inclusion criteria were: primary osteoarthritis as indication, comparison with healthy controls or comparison between the operated and the non-operated limbs, and follow-up period at least six months after surgery.

FINDINGS

The literature search yielded 2177 citations, of which 35 articles were included. Compared to controls, reductions were identified in the operated hip in sagittal range of motion, peak extension, sagittal power generation, abduction moment and external rotation moment. During stair ascent, these reductions did not become more apparent, although deficits in hip kinetics in all three planes were found. Walking speed and step length were reduced compared to controls at longer-term follow-up, but not at short-term follow-up.

INTERPRETATION

The hip abduction moment deficit was present both in level walking and in stair ascent in total hip arthroplasty patients compared to controls. Reduced sagittal hip power generation and external rotation moment were also found, of which the clinical relevance remains to be established. Due to a low number of studies, many of the longer-term effects of THA on gait and gait-related ADL are not yet accurately known.

Measuring functional outcome after total hip replacement with subject-specific hip joint loading

Total hip replacement is an often-performed orthopedic surgical procedure; the amount of procedures undertaken will increase since our life expectancy is growing. In order to optimize function, hip biomechanics should be restored to as near normal as possible. The goal of this pilot study was to determine whether or not it is feasible to compute the vectorial hip reaction force pathways on the head of the prosthesis and the force angles relative to the cup of the prosthesis that occur during gait in total hip replacement patients, serving as an objective measurement of the functional outcome following hip replacement. A three-dimensional gait analysis, measuring ground reaction forces and kinematics, was performed. The data retrieved from the gait analysis was used as the input for the musculoskeletal model to compute vectorial joint reaction forces for data processing. To evaluate the position and orientation of the joint reaction forces, the force path, as well as the force angles for the operated and non-operated joint, has been calculated during the stance phase of the specific leg. The force path for subject 2 on the non-operated side is only located in the posterior-lateral quarter, as is the force path for subject 1. In contrast to this subject, the force path for subject 2 at the operated hip joint can be found only within the anterior quarter of the head of the implant, where it is nearly equally distributed in the medio-lateral half of the prosthesis head. The force-inclination angles on the cup of subject 1, with respect to the plane of the socket face, indicates that the force vector is mainly positioned in the same quadrant when compared with subject 2 (in a cup-fixed coordinate system). The force-anteversion angle behaves similarly to the force-inclination angle, even when the effects are not as pronounced. The proposed methods in this article are aiming to define two functional outcomes of total hip replacement that are related to wear and rim loading. It is accepted that wear is not only a function of time, but a function of use. Owing to the methods listed in this article, we are able to determine a) the applied force and b) the sliding distance (force pathway) in a subject-specific manner. The computed hip-reaction force angles and the distance to the rim cup are a measurement for cup or rim loading, and occurs in the so-called safe-zones. This method may well give us insight into the biomechanical situation during gait, after receiving total hip replacement, that we need to fully understand the mechanisms acting on a hip joint and to prove a possible increase of functional outcome after receiving total hip replacement.