Signatures of knee osteoarthritis in women in the temporal and fractal dynamics of human gait

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.

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.

A Review of the Relationships Between Knee Pain and Movement Neuromechanics

CONTEXT

Knee injury and disease are common, debilitating, and expensive. Pain is a chief symptom of knee injury and disease and likely contributes to arthrogenic muscle inhibition. Joint pain alters isolated motor function, muscular strength, and movement biomechanics. Because knee pain influences biomechanics, it likely also influences long-term knee joint health.

OBJECTIVE

The purpose of this article is 2-fold: (1) review effects of knee pain on lower-extremity muscular activation and corresponding biomechanics and (2) consider potential implications of neuromechanical alterations associated with knee pain for long-term knee joint health. Experimental knee pain is emphasized because it has been used to mimic clinical knee pain and clarify independent effects of knee pain. Three common sources of clinical knee pain are also discussed: patellofemoral pain, anterior cruciate ligament injury and reconstruction, and knee osteoarthritis.

DATA SOURCES

The PubMed, Web of Science, and SPORTDiscus databases were searched for articles relating to the purpose of this article.

CONCLUSION

Researchers have consistently reported that knee pain alters neuromuscular activation, often in the form of inhibition that likely occurs via voluntary and involuntary neural pathways. The effects of knee pain on quadriceps activation have been studied extensively. Knee pain decreases voluntary and involuntary quadriceps activation and strength and alters the biomechanics of various movement tasks. If allowed to persist, these neuromechanical alterations might change the response of articular cartilage to joint loads during movement and detrimentally affect long-term knee joint health. Physical rehabilitation professionals should consider neuromechanical effects of knee pain when treating knee injury and disease. Resolution of joint pain can likely help to restore normal movement neuromechanics and potentially improve long-term knee joint health and should be a top priority.