Lower limb kinematics during the swing phase in patients with knee osteoarthritis measured using an inertial sensor

Accelerations Recorded by Simple Inertial Measurement Units with Low Sampling Frequency Can Differentiate between Individuals with and without Knee Osteoarthritis: Implications for Remote Health Care

Determining the presence and severity of knee osteoarthritis (OA) is a valuable application of inertial measurement units (IMUs) in the remote monitoring of patients. This study aimed to employ the Fourier representation of IMU signals to differentiate between individuals with and without knee OA. We included 27 patients with unilateral knee osteoarthritis (15 females) and 18 healthy controls (11 females). Gait acceleration signals were recorded during overground walking. We obtained the frequency features of the signals using the Fourier transform. The logistic LASSO regression was employed on the frequency domain features as well as the participant's age, sex, and BMI to distinguish between the acceleration data from individuals with and without knee OA. The model's accuracy was estimated by 10-fold cross-validation. The frequency contents of the signals were different between the two groups. The average accuracy of the classification model using the frequency features was 0.91 ± 0.01. The distribution of the selected features in the final model differed between patients with different severity of knee OA. In this study, we demonstrated that using logistic LASSO regression on the Fourier representation of acceleration signals can accurately determine the presence of knee OA.

Phase-dependent modulation of the vestibular-cerebellar network via combined alternating current stimulation influences human locomotion and posture

Background

Human locomotion induces rhythmic movements of the trunk and head. Vestibular signaling is relayed to multiple regions in the brainstem and cerebellum, and plays an essential role in maintaining head stability. However, how the vestibular-cerebellar network contributes to the rhythmic locomotor pattern in humans is unclear. Transcranial alternating current stimulation (tACS) has been used to investigate the effects of the task-related network between stimulation regions in a phase-dependent manner. Here, we investigated the relationship between the vestibular system and the cerebellum during walking imagery using combined tACS over the left cerebellum and alternating current galvanic vestibular stimulation (AC-GVS).

Methods

In Experiment 1, we tested the effects of AC-GVS alone at around individual gait stride frequencies. In Experiment 2, we then determined the phase-specificity of combined stimulation at the gait frequency. Combined stimulation was applied at in-phase (0° phase lag) or anti-phase (180° phase lag) between the left vestibular and left cerebellar stimulation, and the sham stimulation. We evaluated the AC-GVS-induced periodic postural response during walking imagery or no-imagery using the peak oscillatory power on the angular velocity signals of the head in both experiments. In Experiment 2, we also examined the phase-locking value (PLV) between the periodic postural responses and the left AC-GVS signals to estimate entrainment of the postural response by AC-GVS.

Results

AC-GVS alone induced the periodic postural response in the yaw and roll axes, but no interactions with imagery walking were observed in Experiment 1 (p > 0.05). By contrast, combined in-phase stimulation increased yaw motion (0.345 ± 0.23) compared with sham (-0.044 ± 0.19) and anti-phase stimulation (-0.066 ± 0.18) during imaginary walking (in-phase vs. other conditions, imagery: p < 0.05; no-imagery: p ≥ 0.125). Furthermore, there was a positive correlation between the yaw peak power of actual locomotion and in-phase stimulation in the imagery session (imagery: p = 0.041; no-imagery: p = 0.177). Meanwhile, we found no imagery-dependent effects in roll peak power or PLV, although in-phase stimulation enhanced roll motion and PLV in Experiment 2.

Conclusion

These findings suggest that combined stimulation can influence vestibular-cerebellar network activity, and modulate postural control and locomotion systems in a temporally sensitive manner. This novel combined tACS/AC-GVS stimulation approach may advance development of therapeutic applications.

Lower limb inter-joint coordination in individuals with osteoarthritis before and after a total knee arthroplasty

BACKGROUND

Total knee arthroplasty is the most common treatment for severe knee osteoarthritis. Coordination and variability analyses are effective measures of the injury stage or rehabilitation process. This study compared the inter-joint coordination before and after arthroplasty, compared to controls.

METHODS

Twenty-seven patients were evaluated before and 12 months after surgery, compared to 27 controls. Coordination and variability in the sagittal plane between the hip-knee and knee-ankle were calculated using vector coding and circular statistics. Coordination was categorized as in-phase, anti-phase, or distal or proximal joint-phase. The gait cycle was divided into sub-phases for the coordination, variability, and range of motion results.

FINDINGS

Coordination and range of motion differed significantly between the patient groups and controls, while small differences between pre- and post-operative groups were also detected. The hip-knee showed a reduced in-phase frequency in the patient group compared to control during stance, particularly mid-stance: pre-operative 24.3% ± 33.9, post-operative 29.5 ± 29.7, and controls 70.7 ± 17.0. This difference was compensated for by increasing proximal-phase (hip) frequency in the patient groups. For knee-ankle coordination, the patient groups showed higher distal-phase (ankle) frequency during the early and mid-stance. Coordination variability was higher post-operatively during swing and terminal swing phases, compared to controls.

INTERPRETATION

The results indicated reduced degrees of freedom for the knee during stance phase with a reduced capacity to move the knee and hip in opposing directions before and one year after surgery. The patient group after the surgery increased knee range of motion and coordination compared to pre-operative during swing phase.

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.

Automatic Upper-Limb Brunnstrom Recovery Stage Evaluation via Daily Activity Monitoring

Motor function assessment is crucial for post-stroke rehabilitation. Conventional evaluation methods are subjective, heavily depending on the experience of therapists. In light of the strong correlation between the stroke severity level and the performance of activities of daily living (ADLs), we explored the possibility of automatically evaluating the upper-limb Brunnstrom Recovery Stage (BRS) via three typical ADLs (tooth brushing, face washing and drinking). Multimodal data (acceleration, angular velocity, surface electromyography) were synchronously collected from 5 upper-limb-worn sensor modules. The performance of BRS evaluation system is known to be variable with different system parameters (e.g., number of sensor modules, feature types and classifiers). We systematically searched for the optimal parameters from different data segmentation strategies (five window lengths and four overlaps), 42 types of features, 12 feature optimization techniques and 9 classifiers with the leave-one-subject-out cross-validation. To achieve reliable and low-cost monitoring, we further explored whether it was possible to obtain a satisfactory result using a relatively small number of sensor modules. As a result, the proposed approach can correctly recognize the stages of all 27 participants using only three sensor modules with the optimized data segmentation parameters (window length: 7s, overlap: 50%), extracted features (simple square integral, slope sign change, modified mean absolute value 1 and modified mean absolute value 2), the feature optimization method (principal component analysis) and the logistic regression classifier. According to the literature, this is the first study to comprehensively optimize sensor configuration and parameters in each stage of the BRS classification framework. The proposed approach can serve as a factor-screening tool towards the automatic BRS classification and is promising to be further used at home.

Gait cycle time variability in patients with knee osteoarthritis and its possible associating factors

[Purpose] Knee osteoarthritis can alter gait variability; however, few studies have investigated the associating factors with gait cycle time variability. The first objective was to compare gait cycle variability between female patients with knee osteoarthritis and healthy elderly females and to determine gait characteristics in patients with knee osteoarthritis. The second objective was to identify the associating factors with gait cycle time variability. [Participants and Methods] The participants included 24 female patients diagnosed with knee osteoarthritis and 12 healthy elderly females. Gait cycle variability (coefficient of variation of gait cycle time), knee extension range of motion, knee extension strength, 5-m walk test, Timed Up & Go Test, and Western Ontario and McMaster Universities Osteoarthritis Index were measured. All assessment results were compared between the knee osteoarthritis and healthy groups. [Results] Gait cycle time variability was significantly higher in the knee osteoarthritis group than in the healthy group. Further, it showed a significant positive correlation with the 5-m walk test and the Western Ontario and McMaster Universities Osteoarthritis Index. [Conclusion] Patients with knee osteoarthritis presented greater gait cycle variability than that of healthy individuals. Therefore, rehabilitation to improve gait variability might enhance the quality of life of patients with knee osteoarthritis.

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.

Hip Sway in Patients With Hip Osteoarthritis During One-Leg Standing With a Focus on Time Series Data

This study aimed to investigate the hip sway and the relationship between the center of pressure (CoP) and kinematic parameters regarding the time series scaling component α in patients with hip osteoarthritis (OA) during a one-leg standing task. The scaling exponent α, SD, hip sway maximal acceleration change, and balance performance, which was measured using CoP parameters, were compared between hip OA and control groups during a one-leg standing task. The relationships between balance performance with CoP parameters and kinematic parameters were investigated with the regression analysis. In the hip OA group, the scaling exponent α was smaller in the medial-lateral direction, and the SD and maximal amount of change in hip sway acceleration were larger in the anterior-posterior direction in the hip OA group. In this group, the CoP parameters were significantly associated with α in the medial-lateral direction (negatively) and in the anterior-posterior direction (positively). In the hip OA group, hip sway adaptability in the medial-lateral direction was limited, while the anterior-posterior direction showed greater movement.

Diagnostic Accuracy of the Mobile Assessment of Varus Thrust Using Nine-axis Inertial Measurement Units

Objectives:

The purpose of this study was to clarify the diagnostic accuracy of the mobile assessment of varus thrust using inertial measurement units (IMUs).

Methods:

A total of 80 knees in 49 patients were enrolled in this study. On visual analysis of gait to determine the presence or absence of varus thrust, 23 knees were assigned to the Present group, 17 to the Ambiguous group, and 40 to the Absent group. The peak knee varus angular velocities (PVVs), measured by quantitative gait analysis using nine-axis IMUs, were compared between these three groups. A receiver operating characteristic curve for the relationship between the visual assessment of varus thrust (Present and Ambiguous) and the measured PVV was created, and the cut-off PVV for visualized varus thrust was determined as the highest point for both sensitivity and specificity.

Results:

The mean PVVs were significantly different between the three groups (Present, 47.7 ± 8.2 degree/s, Ambiguous, 34.1 ± 10.5 degree/s, and Absent, 28.1 ± 8.3 degree/s, respectively, ANOVA P=0.000). The PVV cut-off value for visualized varus thrust was 28.1 degree/s, yielding a sensitivity of 0.957 and a specificity of 0.579.

Conclusions:

A PVV <28.1 degree/s is useful for ruling out varus thrust during gait. This quantitative varus thrust assessment method using IMUs has clinical utility as a screening test.

Coordination of lower limbs in patients with knee osteoarthritis during walking

BACKGROUND

The movement coordination in patients with knee osteoarthritis may be impaired and the identification of the deficits in lower limb inter-segmental coordination is crucial to understand the effect of knee osteoarthritis on knee function.

RESEARCH QUESTION

This study utilizes continuous relative phase to investigate the pattern and variability of lower limb inter-segmental coordination in patients with knee osteoarthritis and in healthy subjects during walking, and to evaluate inter-segmental coordination alterations in patients.

METHODS

Gait was measured by a three-dimensional motion capture system for 44 patients with late-stage knee osteoarthritis and 22 healthy subjects. Segmental kinematic parameters, continuous relative phase and its variability were calculated. Independent samples t-tests were used to detect differences between patients and healthy subjects.

RESULTS

Thigh-shank continuous relative phase of patients is significantly decreased by 16.04° and 16.18° during late stance and swing phase as compared with healthy subjects (P < 0.05). Shank-foot continuous relative phase of patients is significantly decreased by 6.89° during early stance and significantly increased by 5.49° and 6.39° during late stance and swing phase (P < 0.05). Patients also exhibit increased variability of thigh-shank continuous relative phase during late stance and swing phase by 1.90° and 1.65° respectively, and increased variability of shank-foot continuous relative phase during early stance and swing phase by 0.83° and 0.88° respectively as compared to healthy subjects (P < 0.05).

SIGNIFICANCE

Patients with knee osteoarthritis exhibit altered coordination patterns and increased coordination variability of thigh-shank and shank-foot. Knee dysfunction results in altered lower limbs coordination and unstable motor control during walking. Investigation of inter-segmental coordination could therefore provide insights into changes in neuromuscular control of gait in patients with knee osteoarthritis.

Wearable Inertial Sensors for Gait Analysis in Adults with Osteoarthritis-A Scoping Review

Our objective was to conduct a scoping review which summarizes the growing body of literature using wearable inertial sensors for gait analysis in lower limb osteoarthritis. We searched six databases using predetermined search terms which highlighted the broad areas of inertial sensors, gait, and osteoarthritis. Two authors independently conducted title and abstract reviews, followed by two authors independently completing full-text screenings. Study quality was also assessed by two independent raters and data were extracted by one reviewer in areas such as study design, osteoarthritis sample, protocols, and inertial sensor outcomes. A total of 72 articles were included, which studied the gait of 2159 adults with osteoarthritis (OA) using inertial sensors. The most common location of OA studied was the knee (n = 46), followed by the hip (n = 22), and the ankle (n = 7). The back (n = 41) and the shank (n = 40) were the most common placements for inertial sensors. The three most prevalent biomechanical outcomes studied were: mean spatiotemporal parameters (n = 45), segment or joint angles (n = 33), and linear acceleration magnitudes (n = 22). Our findings demonstrate exceptional growth in this field in the last 5 years. Nevertheless, there remains a need for more longitudinal study designs, patient-specific models, free-living assessments, and a push for "Code Reuse" to maximize the unique capabilities of these devices and ultimately improve how we diagnose and treat this debilitating disease.

Osteoarthritis year in review 2018: mechanics

OBJECTIVE

To review recent biomechanics literature focused on the interactions between biomechanics and articular cartilage health, particularly focused on macro-scale and human studies.

DESIGN

A literature search was conducted in PubMed using the search terms (biomechanics AND osteoarthritis) OR (biomechanics AND cartilage) OR (mechanics AND osteoarthritis) OR (mechanics AND cartilage) for publications from April 2017 to April 2018.

RESULTS

Abstracts from the 559 articles generated from the literature search were reviewed. Due to the wide range of topics, 62 full texts with a focus on in vivo biomechanical studies were included for further discussion. Several overarching themes in the recent literature were identified and are summarized, including 1) new methods to detect early osteoarthritis (OA) development, 2) studies describing healthy and OA cartilage and biomechanics, 3) ACL injury and OA development, 4) meniscus injury and OA development, and 5) OA prevention, treatment, and management.

CONCLUSIONS

Mechanical loading is a critical factor in the maintenance of joint health. Abnormal mechanical loading can lead to the onset and progression of OA. Thus, recent studies have utilized various biomechanical models to better describe the etiology of OA development and the subsequent effects of OA on the mechanics of joint tissues and whole body biomechanics.