Independent and sensitive gait parameters for objective evaluation in knee and hip osteoarthritis using wearable sensors

Motion acquisition of gait characteristics one week after total hip arthroplasty: a factor analysis

INTRODUCTION

Clinical gait analysis can be used to evaluate the recovery process of patients undergoing total hip arthroplasty (THA). The postoperative walking patterns of these patients can be significantly influenced by the choice of surgical approach, as each procedure alters distinct anatomical structures. The aim of this study is twofold. The first objective is to develop a gait model to describe the change in ambulation one week after THA. The secondary goal is to describe the differences associated with the surgical approach.

MATERIALS AND METHODS

Thirty-six patients undergoing THA with lateral (n = 9), anterior (n = 15), and posterior (n = 12) approaches were included in the study. Walking before and 7 days after surgery was recorded using a markerless motion capture system. Exploratory Factor Analysis (EFA), a data reduction technique, condensed 21 spatiotemporal gait parameters to a smaller set of dominant variables. The EFA-derived gait domains were utilized to study post-surgical gait variations and to compare the post-surgical gait among the three groups.

RESULTS

Four distinct gait domains were identified. The most pronounced variation one week after surgery is in the Rhythm (gait cycle time: + 32.9 % ), followed by Postural control (step width: + 27.0 % ), Phases (stance time: + 11.0 % ), and Pace (stride length: -  9.3 % ). In postsurgical walking, Phases is statistically significantly different in patients operated with the posterior approach compared to lateral (p-value = 0.017) and anterior (p-value = 0.002) approaches. Furthermore, stance time in the posterior approach group is significantly lower than in healthy individuals (p-value < 0.001).

CONCLUSIONS

This study identified a four-component gait model specific to THA patients. The results showed that patients after THA have longer stride time but shorter stride length, wider base of support, and longer stance time, although the posterior group had a statistically significant shorter stance time than the others. The findings of this research have the potential to simplify the reporting of gait outcomes, reduce redundancy, and inform targeted interventions in regards to specific gait domains.

Individuals with knee osteoarthritis show few limitations in balance recovery responses after moderate gait perturbations

BACKGROUND

Knee osteoarthritis causes structural joint damage. The resultant symptoms can impair the ability to recover from unexpected gait perturbations. This study compared balance recovery responses to moderate gait perturbations between individuals with knee osteoarthritis and healthy individuals.

METHODS

Kinematic data of 35 individuals with end-stage knee osteoarthritis, and 32 healthy individuals in the same age range were obtained during perturbed walking on a treadmill at 1.0 m/s. Participants received anteroposterior (acceleration or deceleration) or mediolateral perturbations during the stance phase. Changes from baseline in margin of stability, step length, step time, and step width during the first two steps after perturbation were compared between groups using a linear regression model. Extrapolated center of mass excursion was descriptively analyzed.

FINDINGS

After all perturbation modes, extrapolated center of mass trajectories overlapped between individuals with knee osteoarthritis and healthy individuals. Participants predominantly responded to mediolateral perturbations by adjusting their step width, and to anteroposterior perturbations by adjusting step length and step time. None of the perturbation modes yielded between-group differences in changes in margin of stability and step width during the first two steps after perturbation. Small between-group differences were observed for step length (i.e. 2 cm) of the second step after mediolateral and anteroposterior perturbations, and for step time (i.e. 0.01-0.02 s) of first step after mediolateral perturbations and the second step after outward and belt acceleration perturbations.

INTERPRETATION

Despite considerable pain and damage to the knee joint, individuals with knee osteoarthritis showed comparable balance recovery responses after moderate gait perturbations to healthy participants.

Deficient gait function despite effect index of the Western Ontario and McMaster university osteoarthritis index score considered cured one year after bilateral total knee arthroplasty

BACKGROUND

To clarify the value of gait analysis and its consistency with traditional scoring scales for the evaluation of knee joint function after total knee arthroplasty (TKA).

METHODS

This study included 25 patients with knee osteoarthritis (KOA) who underwent bilateral TKA, and 25 conditionally matched healthy individuals, categorised into the experimental and control groups, respectively. Patients in the experimental group underwent gait analysis and Western Ontario and McMaster University Osteoarthritis Index (WOMAC) evaluation before and 1 year after TKA. Weight-bearing balance and walking stability were assessed using discrete trends of relevant gait indicators. Pearson's correlation analysis was performed on the gait and WOMAC score data of the experimental group before and after TKA.

RESULTS

One year after TKA, patients' gait indices (except gait cycle) were significantly better than before surgery, but significantly worse than that of the control group (P < 0.01). The shape of patients' plantar pressure curves did not return to normal. Additionally, the discrete trend of related gait indicators reflecting weight-bearing balance and walking stability were smaller than before TKA, but still greater than that of the control group. The WOMAC scores of patients 1 year after TKA were significantly lower than those before TKA (P < 0.001), and the efficacy index was > 80%. The WOMAC scores and gait analysis results were significantly correlated before TKA (P < 0.05).

CONCLUSIONS

Gait analysis should be used in conjunction with scoring scales to assess joint functions.

Effect of heel lift insertion on gait function in a patient with total hip arthroplasty with patient-perceived leg length difference: a case report

[Purpose] The effect of heel lift insertion on gait in patients who have undergone total hip arthroplasty (THA) with patient-perceived leg length difference is seldom referenced in the literature. We used an AB design to investigate the alterations of gait function before and after inserting a heel lift on the non-operative side. [Participant and Methods] The participant had a patient-perceived leg length difference after THA and presented with gait disturbance. The survey phase was 10 days (phase A: normal physiotherapy for five days, and phase B: normal physiotherapy and heel lift insertion for another five days) from the 17th day following THA. The ambulatory task was conducted at a self-determined, comfortable pace and objectively assessed using an inertial sensor. [Results] The insertion of a heel lift partially improved the gait symmetry and the ratio of lumbar acceleration in three directions; it also corrected the patient-perceived leg length difference. [Conclusion] An investigation was carried out to examine the impact of a heel lift on gait in a single case of THA with patient-reported leg length difference. The application of a heel lift may enhance the relationship between the patient-perceived leg length difference, gait symmetry, and the ratio of lumbar acceleration in three dimensions.

Mobile and Computer-Based Applications for Rehabilitation Monitoring and Self-Management After Knee Arthroplasty: Scoping Review

BACKGROUND

Successful post-knee replacement rehabilitation requires adequate access to health information, social support, and periodic monitoring by a health professional. Mobile health (mHealth) and computer-based technologies are used for rehabilitation and remote monitoring. The extent of technology use and its function in post-knee replacement rehabilitation care in low and middle-income settings are unknown.

OBJECTIVE

To inform future mHealth intervention development, we conducted a scoping review to map the features and functionality of existing technologies and determine users' perspectives on telerehabilitation and technology for self-management.

METHODS

We followed the Joanna Briggs Institute methodology for scoping reviews. We searched the Embase, Medline, PsycINFO via OVID, and Cochrane Central Register of Controlled Trials databases for manuscripts published from 2001 onward. We included original research articles reporting the use of mobile or computer-based technologies by patients, health care providers, researchers, or family members. Studies were divided into the following 3 categories based on the purpose: validation studies, clinical evaluation, and end user feedback. We extracted general information on study design, technology features, proposed function, and perspectives of health care providers and patients. The protocol for this review is accessible in the Open Science Framework.

RESULTS

Of the 5960 articles, 158 that reported from high-income settings contributed to the qualitative summary (64 studies on mHealth or telerehabilitation programs, 28 validation studies, 38 studies describing users' perceptions). The highest numbers of studies were from Europe or the United Kingdom and North America regarding the use of a mobile app with or without wearables and reported mainly in the last decade. No studies were from low and middle-income settings. The primary functions of technology for remote rehabilitation were education to aid recovery and enable regular, appropriate exercises; monitoring progress of pain (n=19), activity (n=20), and exercise adherence (n=30); 1 or 2-way communication with health care professionals to facilitate the continuum of care (n=51); and goal setting (n=23). Assessment of range of motion (n=16) and gait analysis (n=10) were the commonly validated technologies developed to incorporate into a future rehabilitation program. Few studies (n=14) reported end user involvement during the development stage. We summarized the reasons for satisfaction and dissatisfaction among users across various technologies.

CONCLUSIONS

Several existing mobile and computer-based technologies facilitate post-knee replacement rehabilitation care for patients and health care providers. However, they are limited to high-income settings and may not be extrapolated to low-income settings. A systematic needs assessment of patients undergoing knee replacement and health care providers involved in rehabilitation, involving end users at all stages of development and evaluation, with clear reporting of the development and clinical evaluation can make post-knee replacement rehabilitation care in resource-poor settings accessible and cost-effective.

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.

The Influence of Stride Selection on Gait Parameters Collected with Inertial Sensors

Different methods exist to select strides that represent preferred, steady-state gait. The aim of this study was to identify the effect of different stride-selection methods on spatiotemporal gait parameters to analyze steady-state gait. A total of 191 patients with hip or knee osteoarthritis (aged 38-85) wearing inertial sensors walked back and forth over 10 m for two minutes. After the removal of strides in turns, five stride-selection methods were compared: (ALL) include all strides, others removed (REFERENCE) two strides around turns, (ONE) one stride around turns, (LENGTH) strides <63% of median stride length, and (SPEED) strides that fall outside the 95% confidence interval of gait speed over the strides included in REFERENCE. Means and SDs of gait parameters were compared for each trial against the most conservative definition (REFERENCE). ONE and SPEED definitions resulted in similar means and SDs compared to REFERENCE, while ALL and LENGTH definitions resulted in substantially higher SDs of all gait parameters. An in-depth analysis of individual strides showed that the first two strides after and last two strides before a turn were significantly different from steady-state walking. Therefore, it is suggested to exclude the first two strides around turns to assess steady-state gait.

Trunk Biomechanics in Individuals with Knee Disorders: A Systematic Review with Evidence Gap Map and Meta-analysis

BACKGROUND

The trunk is the foundation for transfer and dissipation of forces throughout the lower extremity kinetic chain. Individuals with knee disorders may employ trunk biomechanical adaptations to accommodate forces at the knee or compensate for muscle weakness. This systematic review aimed to synthesize the literature comparing trunk biomechanics between individuals with knee disorders and injury-free controls.

METHODS

Five databases were searched from inception to January 2022. Observational studies comparing trunk kinematics or kinetics during weight-bearing tasks (e.g., stair negotiation, walking, running, landings) between individuals with knee disorders and controls were included. Meta-analyses for each knee disorder were performed. Outcome-level certainty was assessed using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE), and evidence gap maps were created.

RESULTS

A total of 81 studies investigating trunk biomechanics across six different knee disorders were included (i.e., knee osteoarthritis [OA], total knee arthroplasty [TKA], patellofemoral pain [PFP], patellar tendinopathy [PT], anterior cruciate ligament deficiency [ACLD], and anterior cruciate ligament reconstruction [ACLR]). Individuals with knee OA presented greater trunk flexion during squatting (SMD 0.88, 95% CI 0.58-1.18) and stepping tasks (SMD 0.56, 95% CI 0.13-.99); ipsilateral and contralateral trunk lean during walking (SMD 1.36; 95% CI 0.60-2.11) and sit-to-stand (SMD 1.49; 95% CI 0.90-2.08), respectively. Greater trunk flexion during landing tasks in individuals with PFP (SMD 0.56; 95% CI 0.01-1.12) or ACLR (SMD 0.48; 95% CI 0.21-.75) and greater ipsilateral trunk lean during single-leg squat in individuals with PFP (SMD 1.01; 95% CI 0.33-1.70) were also identified. No alterations in trunk kinematics of individuals with TKA were identified. Evidence gap maps outlined the lack of investigations for individuals with PT or ACLD, as well as for trunk kinetics across knee disorders.

CONCLUSION

Individuals with knee OA, PFP, or ACLR present with altered trunk kinematics in the sagittal and frontal planes. The findings of this review support the assessment of trunk biomechanics in these individuals in order to identify possible targets for rehabilitation and avoidance strategies.

TRIAL REGISTRATION

PROSPERO registration number: CRD42019129257.

OA-Pain-Sense: Machine Learning Prediction of Hip and Knee Osteoarthritis Pain from IMU Data

Joint pain is a prominent symptom of Hip and Knee Osteoarthritis (OA), impairing patients’ movements and affecting the joint mechanics of walking. Self-report questionnaires are currently the gold standard for Hip OA and Knee OA pain assessment, presenting several problems, including the fact that older individuals often fail to provide accurate self-pain reports. Passive methods to assess pain are desirable. This study aims to explore the feasibility of OA-Pain-Sense, a passive, automatic Machine Learning-based approach that predicts patients’ self-reported pain levels using SpatioTemporal Gait features extracted from the accelerometer signal gathered from an anterior-posterior wearable sensor. To mitigate inter-subject variability, we investigated two types of data rescaling: subject-level and dataset-level. We explored six different binary machine learning classification models for discriminating pain in patients with Hip OA or Knee OA from healthy controls. In rigorous evaluation, OA-Pain-Sense achieved an average accuracy of 86.79% using the Decision Tree and 83.57% using Support Vector Machine classifiers for distinguishing Hip OA and Knee OA patients from healthy subjects, respectively. Our results demonstrate that OA-Pain-Sense is feasible, paving the way for the development of a pain assessment algorithm that can support clinical decision-making and be used on any wearable device, such as smartphones.

Objective gait assessment in individuals with knee osteoarthritis using inertial sensors: A systematic review and meta-analysis

BACKGROUND

Objective assessment of gait using inertial sensors has shown promising results for functional evaluations in individuals with knee osteoarthritis (OA). However, the large number of possible outcome measures calls for a systematic evaluation of most relevant parameters to be used for scientific and clinical purposes.

AIM

This systematic review and meta-analysis aimed to identify gait parameters derived from inertial sensors that reflect gait deviations in individuals with knee OA compared to healthy control subjects (HC).

METHODS

A systematic search was conducted in five electronic databases (Medline, Embase, Web of Science, CINAHL, IEEE) to identify eligible articles. Risk of bias was assessed using a modified version of the Downs and Black scale. Data regarding study population, experimental procedures, and biomechanical outcomes were extracted. When a gait parameter was reported by a sufficient number of studies, a random-effects meta-analysis was conducted using the inverse variance method.

RESULTS

Twenty-three articles comparing gait between 411 individuals with knee OA and 507 HC were included. Individuals with knee OA had a lower gait speed than HC (standardized mean difference = -1.65), driven by smaller strides with a longer duration. Stride time variability was slightly higher in individuals with knee OA than in HC. Individuals with knee OA walked with a lower range of motion of the knee during the swing phase, less lumbar motion in the coronal plane, and a lower foot strike and toe-off angle compared to HC.

SIGNIFICANCE

This review shows that inertial sensors can detect gait impairments in individuals with knee OA. Large standardized mean differences found on spatiotemporal parameters support their applicability as sensitive endpoints for mobility in individuals with knee OA. More advanced measures, including kinematics of knee and trunk, may reveal gait adaptations that are more specific to knee OA, but compelling evidence was lacking.

Objective monitoring of functional recovery after total knee and hip arthroplasty using sensor-derived gait measures

Background

Inertial sensors hold the promise to objectively measure functional recovery after total knee (TKA) and hip arthroplasty (THA), but their value in addition to patient-reported outcome measures (PROMs) has yet to be demonstrated. This study investigated recovery of gait after TKA and THA using inertial sensors, and compared results to recovery of self-reported scores of pain and function.

Methods

PROMs and gait parameters were assessed before and at two and fifteen months after TKA (n = 24) and THA (n = 24). Gait parameters were compared with healthy individuals (n = 27) of similar age. Gait data were collected using inertial sensors on the feet, lower back, and trunk. Participants walked for two minutes back and forth over a 6m walkway with 180° turns. PROMs were obtained using the Knee Injury and Osteoarthritis Outcome Scores and Hip Disability and Osteoarthritis Outcome Score.

Results

Gait parameters recovered to the level of healthy controls after both TKA and THA. Early improvements were found in gait-related trunk kinematics, while spatiotemporal gait parameters mainly improved between two and fifteen months after TKA and THA. Compared to the large and early improvements found in of PROMs, these gait parameters showed a different trajectory, with a marked discordance between the outcome of both methods at two months post-operatively.

Conclusion

Sensor-derived gait parameters were responsive to TKA and THA, showing different recovery trajectories for spatiotemporal gait parameters and gait-related trunk kinematics. Fifteen months after TKA and THA, there were no remaining gait differences with respect to healthy controls. Given the discordance in recovery trajectories between gait parameters and PROMs, sensor-derived gait parameters seem to carry relevant information for evaluation of physical function that is not captured by self-reported scores.

Analysing Gait Patterns in Degenerative Lumbar Spine Disease Using Inertial Wearable Sensors: An Observational Study

OBJECTIVE

Using a chest-based inertial wearable sensor, we examined the quantitative gait patterns associated with lumbar disc herniation (LDH), lumbar spinal stenosis (LSS), and chronic mechanical low back pain (CMLBP). 'Pathological gait signatures' were reported as statistically significant group difference (%) from the 'normative' gait values of an age-matched control population.

METHODS

A sample of patients presenting to the Prince of Wales Private Hospital (Sydney, Australia) with primary diagnoses of LDH, LSS, or CMLBP were recruited. Spatial, temporal, asymmetry, and variability metrics were compared with age-matched (±2 years) control participants recruited from the community. Participants were fitted at the sternal angle with an inertial measurement unit, MetaMotionC, and walked unobserved (at a self-selected pace) for 120 m along an obstacle-free, carpeted hospital corridor.

RESULTS

LDH, CMLBP, and LSS groups had unique pathological signatures of gait impairment. The LDH group (n = 33) had marked asymmetry in terms of step length, step time, stance, and single-support asymmetry. The LDH group also involved gait variability with increased step length variation. However, distinguishing the CMLBP group (n = 33) was gait variability in terms increased single-support time variation. The gait of participants with LSS (n = 22) was both asymmetric and variable in step length.

CONCLUSIONS

Wearable sensor-based accelerometry was found to be capable of detecting the gait abnormalities present in patients with LDH, LSS, and CMLBP, when compared to age-matched controls. Objective and quantitative patterns of gait deterioration uniquely varied between these subtypes of lumbar spine disease. With further testing and validation, gait signatures may aid clinical identification of gait-altering pathologies.

Osteoarthritis year in review 2021: mechanics

Osteoarthritis (OA) has a complex, heterogeneous and only partly understood etiology. There is a definite role of joint cartilage pathomechanics in originating and progressing of the disease. Although it is still not identified precisely enough to design or select targeted treatments, the progress of this year's research demonstrates that this goal became much closer. On multiple scales - tissue, joint and whole body - an increasing number of studies were done, with impressive results. (1) Technology based instrument innovations, especially when combined with machine learning models, have broadened the applicability of biomechanics. (2) Combinations with imaging make biomechanics much more precise & personalized. (3) The combination of Musculoskeletal & Finite Element Models yield valid personalized cartilage loads. (4) Mechanical outcomes are becoming increasingly meaningful to inform and evaluate treatments, including predictive power from biomechanical models. Since most recent advancements in the field of biomechanics in OA are at the level of a proof op principle, future research should not only continue on this successful path of innovation, but also aim to develop clinical workflows that would facilitate including precision biomechanics in large scale studies. Eventually this will yield clinical tools for decision making and a rationale for new therapies in OA.

Fusion of Wearable Kinetic and Kinematic Sensors to Estimate Triceps Surae Work during Outdoor Locomotion on Slopes

Muscle–tendon power output is commonly assessed in the laboratory through the work loop, a paired analysis of muscle force and length during a cyclic task. Work-loop analysis of muscle–tendon function in out-of-lab conditions has been elusive due to methodological limitations. In this work, we combined kinetic and kinematic measures from shear wave tensiometry and inertial measurement units, respectively, to establish a wearable system for estimating work and power output from the soleus and gastrocnemius muscles during outdoor locomotion. Across 11 healthy young adults, we amassed 4777 strides of walking on slopes from −10° to +10°. Results showed that soleus work scales with incline, while gastrocnemius work is relatively insensitive to incline. These findings agree with previous results from laboratory-based studies while expanding technological capabilities by enabling wearable analysis of muscle–tendon kinetics. Applying this system in additional settings and activities could improve biomechanical knowledge and evaluation of protocols in scenarios such as rehabilitation, device design, athletics, and military training.

Wearable Sensor for Assessing Gait and Postural Alterations in Patients with Diabetes: A Scoping Review

Background and Objectives: Diabetes mellitus is considered a serious public health problem due to its high prevalence and related complications, including gait and posture impairments due to neuropathy and vascular alterations and the subsequent increased risk of falls. The gait of patients with diabetes is characterized by alterations of the main spatiotemporal gait parameters such as gait velocity, cadence, stride time and length, which are also known to worsen with disease course. Wearable sensor systems can be used for gait analysis by providing spatiotemporal parameters and postural control (evaluated from the perspective of body sway), useful for investigating the disease progression. Thanks to their small size and low cost of their components, inertial measurement units (IMUs) are easy to wear and are cheap tools for movement analysis. Materials and Methods: The aim of this study is to review articles published in the last 21 years (from 2000 to 2021) concerning the application of wearable sensors to assess spatiotemporal parameters of gait and body postural alterations in patients with diabetes mellitus. Relevant articles were searched in the Medline database using PubMed, Ovid and Cochrane libraries. Results: One hundred and four articles were initially identified while searching the scientific literature on this topic. Thirteen were selected and analysed in this review. Wearable motion sensors are useful, noninvasive, low-cost, and objective tools for performing gait and posture analysis in diabetic patients. The IMUs can be worn at the lumber levels, tibias or feet, and different spatiotemporal parameters of movement and static posture can be assessed. Conclusions: Future research should focus on standardizing the measurement setup and selecting the most informative spatiotemporal parameters for gait and posture analysis.

Inertial measurement units and application for remote healthcare in hip and knee osteoarthritis: a narrative review (Preprint)

Background

Measuring and modifying movement-related joint loading is integral to the management of lower extremity osteoarthritis (OA). Although traditional approaches rely on measurements made within the laboratory or clinical environments, inertial sensors provide an opportunity to quantify these outcomes in patients’ natural environments, providing greater ecological validity and opportunities to develop large data sets of movement data for the development of OA interventions.

Objective

This narrative review aimed to discuss and summarize recent developments in the use of inertial sensors for assessing movement during daily activities in individuals with hip and knee OA and to identify how this may translate to improved remote health care for this population.

Methods

A literature search was performed in November 2018 and repeated in July 2019 and March 2021 using the PubMed and Embase databases for publications on inertial sensors in hip and knee OA published in English within the previous 5 years. The search terms encompassed both OA and wearable sensors. Duplicate studies, systematic reviews, conference abstracts, and study protocols were also excluded. One reviewer screened the search result titles by removing irrelevant studies, and 2 reviewers screened study abstracts to identify studies using inertial sensors as the main sensing technology and a primary outcome related to movement quality. In addition, after the March 2021 search, 2 reviewers rescreened all previously included studies to confirm their relevance to this review.

Results

From the search process, 43 studies were determined to be relevant and subsequently included in this review. Inertial sensors have been successfully implemented for assessing the presence and severity of OA (n=11), assessing disease progression risk and providing feedback for gait retraining (n=7), and remotely monitoring intervention outcomes and identifying potential responders and nonresponders to interventions (n=14). In addition, studies have validated the use of inertial sensors for these applications (n=8) and analyzed the optimal sensor placement combinations and data input analysis for measuring different metrics of interest (n=3). These studies show promise for remote health care monitoring and intervention delivery in hip and knee OA, but many studies have focused on walking rather than a range of activities of daily living and have been performed in small samples (<100 participants) and in a laboratory rather than in a real-world environment.

Conclusions

Inertial sensors show promise for remote monitoring, risk assessment, and intervention delivery in individuals with hip and knee OA. Future opportunities remain to validate these sensors in real-world settings across a range of activities of daily living and to optimize sensor placement and data analysis approaches.

Does Posterior Cruciate Ligament Retention or Sacrifice in Total Knee Replacement Affect Proprioception? A Systematic Review

Background: Proprioception is an important part of the somatosensory system involved in human motion control, which is fundamental for activities of daily living, exercise, and sport-specific gestures. When total knee arthroplasty (TKA) is performed, the posterior cruciate ligament (PCL) can be retained, replaced, or discarded. The PCL seems to be responsible for maintaining the integrity of the joint position sense (JPS) and joint kinesthesia. The aim of this review was to assess the effect of PCL on knee joint proprioception in total knee replacement. Methods: This systematic review was conducted within five electronic databases: PubMed, Scopus, Web of Science, Cochrane, and PEDro with no data limit from inception to May 2021. Results: In total 10 publications were evaluated. The analysis was divided by proprioception assessment method: direct assessment (JPS, kinesthesia) and indirect assessment (balance). Conclusions: The current evidence suggest that the retention of the PCL does not substantially improve the joint proprioception after TKA. Due to the high heterogeneity of the studies in terms of design, proprioception outcomes, evaluation methods, further studies are needed to confirm the conclusions. In addition, future research should focus on the possible correlation between joint proprioception and walking function.