Gait characterization for osteoarthritis patients using wearable gait sensors (H-Gait systems)

Gait variability and biomechanical distinctions in knee osteoarthritis: Insights from a 3D analysis in an adult elderly cohort

Background

This study employs 3D gait analysis to investigate normal gait patterns in individuals afflicted with knee Osteoarthritis (OA). Focusing on the adult osteoarthritic population, the research aims to establish reference values for joint angles, temporospatial parameters, Gait Profile Score (GPS), and Movement Analysis Profile (MAP) collected concurrently along a standardized walking path. Furthermore, the study delves into potential variations linked to gender and OA severity, comparing gait parameters between male and female participants and among individuals with grade 3 and grade 4 OA.

Method

The study involved 34 adults with a mean age of 68.6 ± 5.75 years, all experiencing OA knees and awaiting Total Knee Arthroplasty (TKA). Utilizing Qualisys Motion capture system, 3D gait analysis was conducted. Data were processed through Visual 3D C-Motion Software.

Results

Gait analysis revealed noteworthy differences between genders for various parameters, including stance time, GPS, MAP of the hip, and joint angle for the sagittal plane (ankle), coronal plane (knee), and transverse plane (hip and knee). Moreover, significant differences were observed between grade 3 and grade 4 OA knees in MAP and for the transverse plane joint angle (ankle).

Conclusion

This gait analysis study sheds light on distinctive gait patterns in the adult osteoarthritic population. The identified variations in temporospatial parameters, joint angles, GPS, and MAP provide valuable reference values for individuals suffering from knee OA. The observed differences between genders and across different OA severity grades emphasize the need for personalized approaches in managing knee OA and planning interventions like TKA.

A Novel Prediction Method of Transfer-Assisted Action Oriented to Individual Differences for the Excretion Care Robot

The excretion care robot's (ECR) accurate recognition of transfer-assisted actions is crucial during its usage. However, transfer action recognition is a challenging task, especially since the differentiation of actions seriously affects its recognition speed, robustness, and generalization ability. We propose a novel approach for transfer action recognition assisted by a bidirectional long- and short-term memory (Bi-LSTM) network combined with a multi-head attention mechanism. Firstly, we utilize posture sensors to detect human movements and establish a lightweight three-dimensional (3D) model of the lower limbs. In particular, we adopt a discrete extended Kalman filter (DEKF) to improve the accuracy and foresight of pose solving. Then, we construct an action prediction model that incorporates a fused Bi-LSTM with Multi-head attention (MHA Bi-LSTM). The MHA extracts key information related to differentiated movements from different dimensions and assigns varying weights. Utilizing the Bi-LSTM network effectively combines past and future information to enhance the prediction results of differentiated actions. Finally, comparisons were made by three subjects in the proposed method and with two other time series based neural network models. The reliability of the MHA Bi-LSTM method was verified. These experimental results show that the introduced MHA Bi-LSTM model has a higher accuracy in predicting posture sensor-based excretory care actions. Our method provides a promising approach for handling transfer-assisted action individual differentiation in excretion care tasks.

Technological Solutions for Human Movement Analysis in Obese Subjects: A Systematic Review

Obesity has a critical impact on musculoskeletal systems, and excessive weight directly affects the ability of subjects to realize movements. It is important to monitor the activities of obese subjects, their functional limitations, and the overall risks related to specific motor tasks. From this perspective, this systematic review identified and summarized the main technologies specifically used to acquire and quantify movements in scientific studies involving obese subjects. The search for articles was carried out on electronic databases, i.e., PubMed, Scopus, and Web of Science. We included observational studies performed on adult obese subjects whenever reporting quantitative information concerning their movement. The articles must have been written in English, published after 2010, and concerned subjects who were primarily diagnosed with obesity, thus excluding confounding diseases. Marker-based optoelectronic stereophotogrammetric systems resulted to be the most adopted solution for movement analysis focused on obesity; indeed, wearable technologies based on magneto-inertial measurement units (MIMUs) were recently adopted for analyzing obese subjects. Further, these systems are usually integrated with force platforms, so as to have information about the ground reaction forces. However, few studies specifically reported the reliability and limitations of these approaches due to soft tissue artifacts and crosstalk, which turned out to be the most relevant problems to deal with in this context. In this perspective, in spite of their inherent limitations, medical imaging techniques-such as Magnetic Resonance Imaging (MRI) and biplane radiography-should be used to improve the accuracy of biomechanical evaluations in obese people, and to systematically validate less-invasive approaches.

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.

Evaluation of Lower-Limb Kinematics during Timed Up and Go (TUG) Test in Subjects with Locomotive Syndrome (LS) Using Wearable Gait Sensors (H-Gait System)

Few studies have dealt with lower-limb kinematics during the timed up and go (TUG) test in subjects with locomotive syndrome (LS). This study aimed to evaluate the characteristics of lower-limb kinematics during the TUG test in subjects with LS using the wearable sensor-based H-Gait system. A total of 140 participants were divided into the non-LS (n = 28), the LS-stage 1 (n = 78), and LS-stage 2 (n = 34) groups based on the LS risk test. Compared with the non-LS group, the LS-stage 1 and LS-stage 2 groups showed significantly smaller angular velocity of hip and knee extension during the sit-to-stand phase. The LS-stage 2 group showed significantly smaller peak angles of hip extension and flexion during the walking-out phase compared to the non-LS group. These findings indicate that the evaluation of the lower-limb kinematics during the TUG test using the H-Gait system is highly sensitive to detect LS, compared with the evaluation of the lower-limb kinematics when simply walking.

Relation of gait measures with mild unilateral knee pain during walking using machine learning

Gait alterations in those with mild unilateral knee pain during walking may provide clues to modifiable alterations that affect progression of knee pain and osteoarthritis (OA). To examine this, we applied machine learning (ML) approaches to gait data from wearable sensors in a large observational knee OA cohort, the Multicenter Osteoarthritis (MOST) study. Participants completed a 20-m walk test wearing sensors on their trunk and ankles. Parameters describing spatiotemporal features of gait and symmetry, variability and complexity were extracted. We used an ensemble ML technique ("super learning") to identify gait variables in our cross-sectional data associated with the presence/absence of unilateral knee pain. We then used logistic regression to determine the association of selected gait variables with odds of mild knee pain. Of 2066 participants (mean age 63.6 [SD: 10.4] years, 56% female), 21.3% had mild unilateral pain while walking. Gait parameters selected in the ML process as influential included step regularity, sample entropy, gait speed, and amplitude dominant frequency, among others. In adjusted cross-sectional analyses, lower levels of step regularity (i.e., greater gait variability) and lower sample entropy(i.e., lower gait complexity) were associated with increased likelihood of unilateral mild pain while walking [aOR 0.80 (0.64-1.00) and aOR 0.79 (0.66-0.95), respectively].

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.

Knee braces and foot orthoses multimodal treatment of medial knee osteoarthritis

BACKGROUND

Knee braces and lateral wedge foot orthoses are two treatment options recommended for medial knee osteoarthritis, but the combination of both of them could further improve their effectiveness.

RESEARCH QUESTION

The aim was to evaluate whether the combination of lateral wedge foot orthoses with two types of knee brace enhances the biomechanical effects and pain relief during the stance phase of gait while maintaining comfort.

METHODS

Ten patients with medial knee osteoarthritis were fitted with a standard valgus brace, an unloader brace with valgus and external rotation functions, and 7° lateral wedge foot orthoses. The pain relief, comfort, kinematics and kinetics of the lower limb were measured during walking without orthotics, with the combined and with the isolated treatments.

RESULTS

The valgus and external rotation brace significantly reduced the knee adduction moment and allowed more knee flexion both in isolation and in combination to foot orthoses compared to the valgus brace or without treatment. Pain relief was not significant with the different orthotic treatment modalities. The valgus brace and combined treatment with either brace significantly increased the discomfort level, whereas the valgus and external rotation brace or foot orthoses in isolation did not induce significant discomfort.

SIGNIFICANCE

Amongst the tested orthotic treatment modalities, the valgus and external rotation brace obtained better biomechanical outcomes while maintaining comfort. The combined treatment with foot orthoses enhanced the effectiveness of the valgus brace, however foot orthoses may be unnecessary with the valgus and external rotation brace.

Evaluation of gait characteristics in subjects with locomotive syndrome using wearable gait sensors

BACKGROUND

Individuals with locomotive syndrome (LS) require nursing care services owing to problems with locomotion and the musculoskeletal system. Individuals with LS generally have a reduced walking speed compared with those without LS. However, differences in lower-limb kinematics and gait between individuals with and without LS are not fully understood. This study aimed to clarify the characteristics of the gait kinematics of individuals with LS using wearable sensors.

METHODS

We assessed 125 participants (mean age 73.0 ± 6.7 years) who used a public health promotion facility. Based on the 25-question Geriatric Locomotive Function Scale (GLFS-25), these participants were grouped into the non-LS (GLFS-25 < 7), LS-stage 1 (GLFS-25 7-16), and LS-stage 2 (GLFS-25 ≥ 16) groups (larger GLFS-25 scores indicate worse locomotive ability). Spatiotemporal parameters and lower-limb kinematics during the 10-m walk test were analyzed by the "H-Gait system", which is a motion analysis system that was developed by the authors and is based on seven inertial sensors. The peak joint angles during the stance and swing phases, as well as the gait speed, cadence, and step length were compared among all groups.

RESULTS

There were 69 participants in the non-LS group, 33 in the LS-stage 1 group, and 23 in the LS-stage 2 group. Compared with the non-LS group, the LS-stage 2 group showed significantly smaller peak angles of hip extension (9.5 ± 5.3° vs 4.2 ± 8.2°, P = 0.002), hip flexion (34.2 ± 8.8° vs 28.5 ± 9.5°, P = 0.026), and knee flexion (65.2 ± 18.7° vs 50.6 ± 18.5°, P = 0.005). The LS-stage 1 and LS-stage 2 groups had a significantly slower mean gait speed than the non-LS group (non-LS: 1.3 ± 0.2 m/s, LS-stage 1: 1.2 ± 0.2 m/s, LS-stage 2: 1.1 ± 0.2 m/s, P < 0.001).

CONCLUSIONS

The LS-stage 2 group showed significantly different lower-limb kinematics compared with the non-LS group, including smaller peak angles of hip extension, hip flexion, and knee flexion. It would be useful to assess and improve these small peak joint angles during gait for individuals classified as LS-stage 2.

Validation of wearable inertial sensor-based gait analysis system for measurement of spatiotemporal parameters and lower extremity joint kinematics in sagittal plane

Wearable inertial sensor-based motion analysis systems are promising alternatives to standard camera-based motion capture systems for the measurement of gait parameters and joint kinematics. These wearable sensors, unlike camera-based gold standard systems, find usefulness in outdoor natural environment along with confined indoor laboratory-based environment due to miniature size and wireless data transmission. This study reports validation of our developed (i-Sens) wearable motion analysis system against standard motion capture system. Gait analysis was performed at self-selected speed on non-disabled volunteers in indoor ( n = 15) and outdoor ( n = 8) environments. Two i-Sens units were placed at the level of knee and hip along with passive markers (for indoor study only) for simultaneous 3D motion capture using a motion capture system. Mean absolute percentage error (MAPE) was computed for spatiotemporal parameters from the i-Sens system versus the motion capture system as a true reference. Mean and standard deviation of kinematic data for a gait cycle were plotted for both systems against normative data. Joint kinematics data were analyzed to compute the root mean squared error (RMSE) and Pearson’s correlation coefficient. Kinematic plots indicate a high degree of accuracy of the i-Sens system with the reference system. Excellent positive correlation was observed between the two systems in terms of hip and knee joint angles (Indoor: hip 3.98° ± 1.03°, knee 6.48° ± 1.91°, Outdoor: hip 3.94° ± 0.78°, knee 5.82° ± 0.99°) with low RMSE. Reliability characteristics (defined using standard statistical thresholds of MAPE) of stride length, cadence, walking speed in both outdoor and indoor environment were well within the “Good” category. The i-Sens system has emerged as a potentially cost-effective, valid, accurate, and reliable alternative to expensive, standard motion capture systems for gait analysis. Further clinical trials using the i-Sens system are warranted on participants across different age groups.

Implantable biosensors for musculoskeletal health

PURPOSE

A healthy musculoskeletal system requires complex functional integration of bone, muscle, cartilage, and connective tissues responsible for bodily support, motion, and the protection of vital organs. Conditions or injuries to musculoskeeltal tissues can devastate an individual's quality of life. Some conditions that are particularly disabling include severe bone and muscle injuries to the extremities and amputations resulting from unmanageable musculoskeletal conditions or injuries. Monitoring and managing musculoskeletal health is intricate because of the complex mechanobiology of these interconnected tissues.

METHODS

For this article, we reviewed literature on implantable biosensors related to clinical data of the musculoskeletal system, therapeutics for complex bone injuries, and osseointegrated prosthetics as example applications.

RESULTS

As a result, a brief summary of biosensors technologies is provided along with review of noteworthy biosensors and future developments needed to fully realize the translational benefit of biosensors for musculoskeletal health.

CONCLUSIONS

Novel implantable biosensors capable of tracking biophysical parameters in vivo are highly relevant to musculoskeletal health because of their ability to collect clinical data relevant to medical decisions, complex trauma treatment, and the performance of osseointegrated prostheses.

A Portable Wearable Inertial System for Rehabilitation Monitoring and Evaluation of Patients With Total Knee Replacement

Knee osteoarthritis is a degenerative disease, which greatly affects the daily life of patients. Total knee replacement (TKR) is the most common method to treat knee joint disorders and relieve knee pain. Postoperative rehabilitation exercise is the key to restore knee joint function. However, there is a lack of a portable equipment for monitoring knee joint activity and a systematic assessment scheme. We have developed a portable rehabilitation monitoring and evaluation system based on the wearable inertial unit to estimate the knee range of motion (ROM). Ten TKR patients and ten healthy adults are recruited for the experiment, then the system performance is verified by professional rehabilitation equipment Baltimore Therapeutic Equipment (BTE) Primus RS. The average absolute difference between the knee ROM and BTE Primus RS of healthy subjects and patients ranges from 0.16° to 4.94°. In addition, the knee ROM of flexion-extension and gait activity between healthy subjects and patients showed significant differences. The proposed system is reliable and effective in monitoring and evaluating the rehabilitation progress of patients. The system proposed in this work is expected to be used for long-term effective supervision of patients in clinical and dwelling environments.

Gait metrics analysis utilizing single-point inertial measurement units: a systematic review

BACKGROUND

Wearable sensors, particularly accelerometers alone or combined with gyroscopes and magnetometers in an inertial measurement unit (IMU), are a logical alternative for gait analysis. While issues with intrusive and complex sensor placement limit practicality of multi-point IMU systems, single-point IMUs could potentially maximize patient compliance and allow inconspicuous monitoring in daily-living. Therefore, this review aimed to examine the validity of single-point IMUs for gait metrics analysis and identify studies employing them for clinical applications.

METHODS

The Preferred Reporting Items for Systematic Reviews and Meta-Analyses Guidelines (PRISMA) were followed utilizing the following databases: PubMed; MEDLINE; EMBASE and Cochrane. Four databases were systematically searched to obtain relevant journal articles focusing on the measurement of gait metrics using single-point IMU sensors.

RESULTS

A total of 90 articles were selected for inclusion. Critical analysis of studies was conducted, and data collected included: sensor type(s); sensor placement; study aim(s); study conclusion(s); gait metrics and methods; and clinical application. Validation research primarily focuses on lower trunk sensors in healthy cohorts. Clinical applications focus on diagnosis and severity assessment, rehabilitation and intervention efficacy and delineating pathological subjects from healthy controls.

DISCUSSION

This review has demonstrated the validity of single-point IMUs for gait metrics analysis and their ability to assist in clinical scenarios. Further validation for continuous monitoring in daily living scenarios and performance in pathological cohorts is required before commercial and clinical uptake can be expected.

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.

Clinical Walking Tests and Gait Pattern Characterization During 6-Minute Walk Test Using Inertial Sensors: Follow-Up in Individuals With Lower Limb Amputation

Inertial measurement units and normative values enable clinicians to quantify clinical walking tests and set rehabilitation goals. Objectives of this study were (1) to compare time- and distance-based walking tests in individuals with lower limb amputation (iLLA) and normative values following rehabilitation discharge (T1) and 6 weeks after discharge (T2) and (2) to investigate spatiotemporal and foot kinematic parameters over a 6-minute walk test using inertial measurement units. Twelve iLLA participated in this study. Distance, cadence, stance ratio, loading rate ratio, push-up ratio, path length, and minimum toe clearance were analyzed during 6-minute walk test. Nonparametric repeated-measures analysis of variance tests, Bonferroni corrections, were performed. Time of distance-based walking tests diminished at T2 (P < .02). Compared with normative values, walking performance in iLLA was reduced. Cadence at T2 increased significantly (P = .026). Stance ratio increased in both legs at T2 (P < .05). Push-up ratio tended to decrease at T2 in the amputated leg (P = .0003). Variability of path length and minimum toe clearance at T2 were less than at T1 in the nonamputated leg (P < .05). Spatiotemporal improvement at T2 could be due to prosthesis adaptation in iLLA. The lower performance of the functional walk test compared with normative values could be due to amputation and pain-related fatigue.

Assessing Site Specificity of Osteoarthritic Gait Kinematics with Wearable Sensors and Their Association with Patient Reported Outcome Measures (PROMs): Knee versus Hip Osteoarthritis

There is a great need for quantitative outcomes reflecting the functional status in patients with knee or hip osteoarthritis (OA) to advance the development and investigation of interventions for OA. The purpose of this study was to determine if gait kinematics specific to the disease—i.e., knee versus hip OA—can be identified using wearable sensors and statistical parametric mapping (SPM) and whether disease-related gait deviations are associated with patient reported outcome measures. 113 participants (N = 29 unilateral knee OA; N = 30 unilateral hip OA; N = 54 age-matched asymptomatic persons) completed gait analysis with wearable sensors and the Knee/Hip Osteoarthritis Outcome Score (KOOS/HOOS). Data were analyzed using SPM. Knee and hip kinematics differed between patients with knee OA and patients with hip OA (up to 14°, p < 0.001 for knee and 8°, p = 0.003 for hip kinematics), and differences from controls were more pronounced in the affected than unaffected leg of patients. The observed deviations in ankle, knee and hip kinematic trajectories from controls were associated with KOOS/HOOS in both groups. Capturing gait kinematics using wearables has a large potential for application as outcome in clinical trials and for monitoring treatment success in patients with knee or hip OA and in large cohorts representing a major advancement in research on musculoskeletal diseases.

Analysis of 3-D Kinematics Using H-Gait System during Walking on a Lower Body Positive Pressure Treadmill

Recently, treadmills equipped with a lower-body positive-pressure (LBPP) device have been developed to provide precise body weight support (BWS) during walking. Since lower limbs are covered in a waist-high chamber of an LBPP treadmill, a conventional motion analysis using an optical method is impossible to evaluate gait kinematics on LBPP. We have developed a wearable-sensor-based three-dimensional motion analysis system, H-Gait. The purpose of the present study was to investigate the effects of BWS by a LBPP treadmill on gait kinematics using an H-Gait system. Twenty-five healthy subjects walked at 2.5 km/h on a LBPP treadmill under the following three conditions: (1) 0%BWS, (2) 25%BWS and (3) 50%BWS conditions. Acceleration and angular velocity from seven wearable sensors were used to analyze lower limb kinematics during walking. BWS significantly decreased peak angles of hip adduction, knee adduction and ankle dorsiflexion. In particular, the peak knee adduction angle at the 50%BWS significantly decreased compared to at the 25%BWS (p = 0.012) or 0%BWS (p < 0.001). The present study showed that H-Gait system can detect the changes in gait kinematics in response to BWS by a LBPP treadmill and provided a useful clinical application of the H-Gait system to walking exercises.

Side to side kinematic gait differences within patients and spatiotemporal and kinematic gait differences between patients with severe knee osteoarthritis and controls measured with inertial sensors

BACKGROUND

Kinematic changes associated with knee osteoarthritis (OA) have been traditionally measured with camera-based gait analysis. Lately, inertial sensors have become popular for gait analysis with the advantage of being less time consuming and not requiring a dedicated laboratory.

RESEARCH QUESTION

Do spatiotemporal and discrete kinematic gait parameters measured with the inertial sensor system RehaGait® differ between the affected and unaffected side in patients with unilateral knee OA and between patients with severe knee OA and asymptomatic control subjects? Do these differences have a similar magnitude as those reported in the literature?

METHODS

Twenty-two patients with unilateral knee OA scheduled for total knee replacement and 46 age matched control subjects were included in this study. Spatiotemporal parameters and sagittal kinematics at the hip, knee, and ankle joint were measured using the RehaGait® system while walking at a self-selected speed for a distance of 20 m and compared between groups.

RESULTS

Patients with knee OA had slower walking speed, longer stride duration, shorter stride length and lower cadence (P < 0.001). Peak knee flexion during stance and swing was lower in the affected than the unaffected leg (-4.8° and -6.1°; P < 0.01). Peak knee flexion during stance and swing (-5.2° and -8.8°; P < 0.01) and knee range of motion during loading response and swing (-3.6° and -4.4°; P < 0.01) were lower than in the control group.

SIGNIFICANCE

These side to side differences within patients and differences between patients with knee OA and control subjects agree with known gait alterations measured with camera-based systems. The RehaGait® inertial sensor system can detect gait alterations in patients with knee OA and is suitable for gait analysis in a clinical environment.

Effects of unweighting on gait kinematics during walking on a lower-body positive-pressure treadmill in patients with hip osteoarthritis

Background

Hip osteoarthritis (OA) is a musculoskeletal condition that makes walking difficult due to pain induced by weight-bearing activities. Treadmills that support the body weight (BW) reduce the load on the lower limbs, and those equipped with a lower-body positive-pressure (LBPP) device, developed as a new method for unweighting, significantly reduce pain in patients with knee OA. However, the effects of unweighting on gait kinematics remain unclear in patients with hip OA. Therefore, we investigated the effects of unweighting on kinematics in patients with hip OA during walking on a treadmill equipped with an LBPP device.

Methods

A total of 15 women with hip OA and 15 age-matched female controls wore a three-dimensional (3-D) motion analysis system and walked at a self-selected speed on the LBPP treadmill. Data regarding self-reported hip pain using a numeric rating scale (NRS) in which the scores 0 and 10 represented no pain and the worst pain, respectively, under three different BW conditions (100, 75, and 50%) were collected. Moreover, 3-D peak joint angles during gait under each condition were calculated and compared.

Results

In the hip OA group, the NRS pain scores at 50 and 75% BW conditions significantly decreased compared with that at 100% BW condition (50%, P = 0.002; 75%, P = 0.026), and the peak hip extension angle decreased compared with that in the healthy controls (P = 0.044). In both groups, unweighting significantly decreased the peak hip (P < 0.001) and knee (P < 0.001) flexion angles and increased the peak ankle plantar flexion angle (P < 0.001) during walking.

Conclusions

Unweighting by the LBPP treadmill decreased pain in the hip OA group but did not drastically alter the gait kinematics compared with that in the control group. Therefore, regarding the use of the LBPP treadmill for patients with hip OA, clinicians should consider the benefits of pain reduction rather than the kinematic changes.

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.

Percentiles and Reference Values for Accelerometric Gait Assessment in Women Aged 50-80 Years

Background: The identification of factors that alter postural stability is fundamental in the design of interventions to maintain independence and mobility. This is especially important for women because of their longer life expectancy and higher incidence of falls than in men. We constructed the percentile box charts and determined the values of reference for the accelerometric assessment of the gait in women. Methods: We used a cross-sectional study with 1096 healthy adult women, who were asked to walk a distance of 20 m three times. Results: In all of the variables, a reduction in the magnitude of accelerations was detected as the age of the group advanced. The box charts show the amplitude of the interquartile ranges, which increases as the age of the participants advances. In addition, the interquartile ranges were greater in the variables that refer to the maximum values of the accelerations. Conclusions: The values obtained can be used to assess changes in gait due to aging, trauma and orthopaedic alterations that may alter postural stability and neurodegenerative processes that increase the risk of falling.

Gait acquisition and analysis system for osteoarthritis based on hybrid prediction model

Osteoarthritis (OA) is the most common type of joint-related diseases, which affects millions of people worldwide. Expensive and time-consuming medical imaging can provide precise structural description of knee joints, but lacks the functional descriptions. Gait analysis can provide functional descriptions of knee joints. However, orthopedic surgeons always observe the patient's gait qualitatively and perform subjective assessments through rating scales at present due to the lack of a quantitative gait analysis system. To solve these problems, a gait acquisition and analysis system is developed to provide a cheap, easy-to-use solution for quantitative recording and functional description of OA patients. Firstly, an automatic gait acquisition platform is designed for the clinical setting based on the RGB-D camera and the developed software of gait data recording. In addition, the effective working space of gait acquisition platform is evaluated for clinical applications by comparing with the ground-truth from infrared optical trackers. Secondly, the acquired gait data is analyzed with a novel hybrid prediction model to assess the gait anomalies quantitatively and objectively. In the hybrid model, the extracted features of gait data contain the manually-extracted features and the automatically-extracted features from Long Short-Term Memory network. Experimental results on real patients demonstrate that the proposed gait analysis system can quantitatively predict gait anomalies with a high accuracy of 98.77 %. Therefore, this gait acquisition and analysis system achieves quantitative recording and objective assessment of gait anomalies for clinical OA treatments.

Kinematic changes in patients with severe knee osteoarthritis are a result of reduced walking speed rather than disease severity

BACKGROUND

Kinematic changes in patients with knee osteoarthritis (OA) have been extensively studied. Concerns have been raised whether the measured spatiotemporal and kinematic alterations are associated with disease progression or merely a result of reduced walking speed.

RESEARCH QUESTION

The purpose of this study was to investigate the effect of walking speed on kinematic parameters in patients with knee OA using statistical parametric mapping (SPM).

METHODS

Twenty-three patients with unilateral knee OA scheduled for a total knee replacement and 28 age matched control subjects were included in this study. Spatiotemporal parameters and sagittal plane kinematics were measured in the hip, knee, and ankle using the inertial sensors system RehaGait® while walking at a self-selected normal (patients and controls) and slow walking speed (controls) for a distance of 20 m. Gait parameters were compared between groups for self-selected walking speed and for matched walking speed using SPM with independent sample t tests.

RESULTS

At self-selected walking speed, patients had significantly lower knee flexion during stance (maximum difference, -6.8°) and during swing (-11.0°), as well as higher ankle dorsiflexion during stance phase (+12.5°) and lower peak hip extension at the end of stance compared to controls (+4.2°). At matched speed, there were no significant differences in joint kinematics between groups.

SIGNIFICANCE

Differences in sagittal plane gait kinematics between patients with knee OA and asymptomatic controls appear to be mainly a result of reduced walking speed. These results emphasize the importance of considering walking speed in research on gait kinematics in patients with knee OA and in clinical trials using gait parameters as outcome measures.

Wireless Motion Sensors-Useful in Assessing the Effectiveness of Physiotherapeutic Methods Used in Patients with Knee Osteoarthritis-Preliminary Report

Osteoarthritis of the knee (OAK) is characterized by pain, limitation of joint mobility, and significant deterioration of proprioception resulting in functional decline. This study assessed proprioception in OAK patients following two ten-day rehabilitation programs using the Orthyo® system. Fifty-four study participants with clinical symptoms and radiological signs of OAK were randomly divided into an exercise group (n = 27) or a manual therapy group (n = 27). The control group consisted of 27 volunteers with radiological signs of OAK, but with no clinical symptoms or prior history of rehabilitation. The following parameters were assessed: knee proprioception using inertial sensors and a mobile application, patients' function using Western Ontario and McMaster Universities osteoarthritis index (WOMAC), and pain intensity using the visual analog scale (VAS). Following rehabilitation, knee proprioception tests did not improve in either study group. Both study groups showed significant improvement of the WOMAC-assessed function (exercise group: p < 0.01, manual therapy group: p = 0.01) and a significant decrease (p < 0.01) of VAS-assessed pain following rehabilitation, but the post-therapy results did not differ significantly between the aforementioned groups. The Orthyo® system provided a quick and accurate assessment of the knee joint position sense. There was no direct relationship between functionality, pain, and proprioception threshold in the knee joint.

Detection of Gait From Continuous Inertial Sensor Data Using Harmonic Frequencies

Mobile gait analysis using wearable inertial measurement units (IMUs) provides valuable insights for the assessment of movement impairments in different neurological and musculoskeletal diseases, for example Parkinson's disease (PD). The increase in data volume due to arising long-term monitoring requires valid, robust and efficient analysis pipelines. In many studies an upstream detection of gait is therefore applied. However, current methods do not provide a robust way to successfully reject non-gait signals. Therefore, we developed a novel algorithm for the detection of gait from continuous inertial data of sensors worn at the feet. The algorithm is focused not only on a high sensitivity but also a high specificity for gait. Sliding windows of IMU signals recorded from the feet of PD patients were processed in the frequency domain. Gait was detected if the frequency spectrum contained specific patterns of harmonic frequencies. The approach was trained and evaluated on 150 clinical measurements containing standardized gait and cyclic movement tests. The detection reached a sensitivity of 0.98 and a specificity of 0.96 for the best sensor configuration (angular rate around the medio-lateral axis). On an independent validation data set including 203 unsupervised, semi-standardized gait tests, the algorithm achieved a sensitivity of 0.97. Our algorithm for the detection of gait from continuous IMU signals works reliably and showed promising results for the application in the context of free-living and non-standardized monitoring scenarios.

Validity of Measurement for Trailing Limb Angle and Propulsion Force during Gait Using a Magnetic Inertial Measurement Unit

Propulsion force and trailing limb angle (TLA) are meaningful indicators for evaluating quality of gait. This study examined the validity of measurement for TLA and propulsion force during various gait conditions using magnetic inertial measurement units (IMU), based on measurements using a three-dimensional motion analysis system and a force platform. Eighteen healthy males (mean age 25.2  ±  3.2 years, body height 1.70   ±  0.06 m) walked with and without trunk fluctuation at preferred, slow, and fast velocities. IMU were fixed on the thorax, lumbar spine, and right thigh and shank. IMU calculated the acceleration and tilt angles in a global coordinate system. TLA, consisting of a line connecting the hip joint with the ankle joint, and the laboratory's vertical axis at late stance in the sagittal plane, was calculated from thigh and shank segment angles obtained by IMU, and coordinate data from the motion analysis system. Propulsion force was estimated by the increment of velocity calculated from anterior acceleration measured by IMU fixed on the thorax and lumbar spine, and normalized impulse of the anterior component of ground reaction force (AGRF) during late stance. Similarity of TLA measured by IMU and the motion analysis system was tested by the coefficient of multiple correlation (CMC), intraclass correlation coefficient (ICC), and root mean square (RMS) of measurement error. Relationships between normalized impulse of AGRF and increments of velocity, as measured by IMU, were tested using correlation analysis. CMC of TLA was 0.956–0.959. ICC between peak TLAs was 0.831–0.876 (p < 0.001), and RMS of error was 1.42°–1.92°. Velocity increment calculated from acceleration on the lumbar region showed strong correlations with normalized impulse of AGRF (r = 0.755–0.892, p < 0.001). These results indicated a high validity of estimation of TLA and propulsion force by IMU during various gait conditions; these methods would be useful for best clinical practice.

Influence of BMI on Gait Characteristics of Young Adults: 3D Evaluation Using Inertial Sensors

Overweight/obesity is a physical condition that affects daily activities, including walking. The main purpose of this study was to identify if there is a relationship between body mass index (BMI) and gait characteristics in young adults. 12 normal weight (NW) and 10 overweight/obese (OW) individuals walked at a self-selected speed along a 14 m indoor path. H-Gait system, combining seven inertial sensors (fixed on pelvis and lower limbs), was used to record gait data. Walking speed, spatio-temporal parameters and joint kinematics in 3D were analyzed. Differences between NW and OW and correlations between BMI and gait parameters were evaluated. Conventional spatio-temporal parameters did not show statistical differences between the two groups or correlations with the BMI. However, significant results were pointed out for the joint kinematics. OW showed greater hip joint angles in frontal and transverse planes, with respect to NW. In the transverse plane, OW showed a greater knee opening angle and a shorter length of knee and ankle trajectories. Correlations were found between BMI and kinematic parameters in the frontal and transverse planes. Despite some phenomena such as soft tissue artifact and kinematics cross-talk, which have to be more deeply assessed, current results show a relationship between BMI and gait characteristics in young adults that should be looked at in osteoarthritis prevention.

Establishing outcome measures in early knee osteoarthritis

The classification and monitoring of individuals with early knee osteoarthritis (OA) are important considerations for the design and evaluation of therapeutic interventions and require the identification of appropriate outcome measures. Potential outcome domains to assess for early OA include patient-reported outcomes (such as pain, function and quality of life), features of clinical examination (such as joint line tenderness and crepitus), objective measures of physical function, levels of physical activity, features of imaging modalities (such as of magnetic resonance imaging) and biochemical markers in body fluid. Patient characteristics such as adiposity and biomechanics of the knee could also have relevance to the assessment of early OA. Importantly, research is needed to enable the selection of outcome measures that are feasible, reliable and validated in individuals at risk of knee OA or with early knee OA. In this Perspectives article, potential outcome measures for early symptomatic knee OA are discussed, including those measures that could be of use in clinical practice and/or the research setting.

Measuring clinically relevant knee motion with a self-calibrated wearable sensor

Low-cost sensors provide a unique opportunity to continuously monitor patient progress during rehabilitation; however, these sensors have yet to demonstrate the fidelity and lack the calibration paradigms necessary to be viable tools for clinical research. The purpose of this study was to validate a low-cost wearable sensor that accurately measured peak knee extension during clinical exercises and needed no additional equipment for calibration. Sagittal plane knee motion was quantified using a 9-axis motion sensor and directly compared to motion capture data. The motion sensor measured the field strength of a strong earth magnet secured to the distal femur, which was correlated with knee angle during a simple calibration process. Peak knee motions and kinematic patterns were compared with motion capture data using paired t-tests and cross correlation, respectively. Peak extension values during seated knee extensions were accurate within 5 degrees across all subjects (root mean square error: 2.6 degrees, P = 0.29). Knee flexion during gait strongly correlated (0.84 ≤ r_xy ≤ 0.99) with motion capture measurements but demonstrated peak flexion errors of 10 degrees. In this study, we present a low-cost sensor (≈$ 35 US) that accurately determines knee extension angle following a calibration procedure that did not require any other equipment. Our findings demonstrate that this sensor paradigm is a feasible tool to monitor patient progress throughout physical therapy. However, dynamic motions that are associated with soft-tissue artifact may limit the accuracy of this type of wearable sensor.

The Role of Patient Education in Arthritis Management: The Utility of Technology

Technologies continue to shape the path of medical treatment. Orthopedic surgeons benefit from becoming more aware of how twenty-first century information technology (IT) can benefit patients. The percentage of orthopedic patients utilizing IT resources is increasing, and new IT tools are becoming utilized. These include disease-specific applications. This article highlights the opportunity for developing IT tools applicable to the growing population of patients with osteoarthritis (OA), and presents a potential solution that can facilitate the way OA education and treatment are delivered, and thereby maximize efficiency for the health care system, the physician, and the patient.

A Review on Accelerometry-Based Gait Analysis and Emerging Clinical Applications

Gait analysis continues to be an important technique for many clinical applications to diagnose and monitor certain diseases. Many mental and physical abnormalities cause measurable differences in a person's gait. Gait analysis has applications in sport, computer games, physical rehabilitation, clinical assessment, surveillance, human recognition, modeling, and many other fields. There are established methods using various sensors for gait analysis, of which accelerometers are one of the most often employed. Accelerometer sensors are generally more user friendly and less invasive. In this paper, we review research regarding accelerometer sensors used for gait analysis with particular focus on clinical applications. We provide a brief introduction to accelerometer theory followed by other popular sensing technologies. Commonly used gait phases and parameters are enumerated. The details of selecting the papers for review are provided. We also review several gait analysis software. Then we provide an extensive report of accelerometry-based gait analysis systems and applications, with additional emphasis on trunk accelerometry. We conclude this review with future research directions.

Mobile assessment of the lower limb kinematics in healthy persons and in persons with degenerative knee disorders: A systematic review

Inertial sensor systems are increasingly used in the assessment of persons with knee osteoarthritis (KOA) and total knee replacement (TKR). This systematic review aims to (1) investigate the application of inertial sensor systems and kinematics derived from these systems, and (2) assess if current assessment protocols consist of tasks which are, according to the International Classification of Functioning, Disability and Health (ICF) for KOA, relevant for persons with KOA and TKR. A search was conducted in six electronic databases (ACM, CINAHL, EMBASE, IEEE, PubMed, Web of Science) to include papers assessing the knee and one or more adjacent joints by means of inertial sensors in healthy persons or persons with KOA or TKR. Two reviewers checked the methodological quality. Twenty-three papers were included: 18 in healthy persons and five in persons with KOA or TKR. In healthy persons, 11 tasks were related to metrics of the ICF-function and ICF-activity level. In persons with KOA, only walking was assessed. Apart from walking, four additional tasks were related to the ICF-function and ICF-activity level in persons with TKR. In healthy persons, joints located proximally and distally to the knee were assessed, while in persons with KOA and TKR, only the knee and ankle were assessed. This is a shortcoming since hip and trunk motion potentially contain clinically relevant information, in terms of identifying (mal)adaptive compensatory movement strategies. Additionally, physically more demanding tasks should be evaluated as these might be superior in detecting compensatory movement strategies. Former considerations warrant attention in future research.

Toward Pervasive Gait Analysis With Wearable Sensors: A Systematic Review

After decades of evolution, measuring instruments for quantitative gait analysis have become an important clinical tool for assessing pathologies manifested by gait abnormalities. However, such instruments tend to be expensive and require expert operation and maintenance besides their high cost, thus limiting them to only a small number of specialized centers. Consequently, gait analysis in most clinics today still relies on observation-based assessment. Recent advances in wearable sensors, especially inertial body sensors, have opened up a promising future for gait analysis. Not only can these sensors be more easily adopted in clinical diagnosis and treatment procedures than their current counterparts, but they can also monitor gait continuously outside clinics - hence providing seamless patient analysis from clinics to free-living environments. The purpose of this paper is to provide a systematic review of current techniques for quantitative gait analysis and to propose key metrics for evaluating both existing and emerging methods for qualifying the gait features extracted from wearable sensors. It aims to highlight key advances in this rapidly evolving research field and outline potential future directions for both research and clinical applications.

A Wearable Magneto-Inertial System for Gait Analysis (H-Gait): Validation on Normal Weight and Overweight/Obese Young Healthy Adults

Background: Wearable magneto-inertial sensors are being increasingly used to obtain human motion measurements out of the lab, although their performance in applications requiring high accuracy, such as gait analysis, are still a subject of debate. The aim of this work was to validate a gait analysis system (H-Gait) based on magneto-inertial sensors, both in normal weight (NW) and overweight/obese (OW) subjects. The validation is performed against a reference multichannel recording system (STEP32), providing direct measurements of gait timings (through foot-switches) and joint angles in the sagittal plane (through electrogoniometers). Methods: Twenty-two young male subjects were recruited for the study (12 NW, 10 OW). After positioning body-fixed sensors of both systems, each subject was asked to walk, at a self-selected speed, over a 14-m straight path for 12 trials. Gait signals were recorded, at the same time, with the two systems. Spatio-temporal parameters, ankle, knee, and hip joint kinematics were extracted analyzing an average of 89 ± 13 gait cycles from each lower limb. Intraclass correlation coefficient and Bland-Altmann plots were used to compare H-Gait and STEP32 measurements. Changes in gait parameters and joint kinematics of OW with respect NW were also evaluated. Results: The two systems were highly consistent for cadence, while a lower agreement was found for the other spatio-temporal parameters. Ankle and knee joint kinematics is overall comparable. Joint ROMs values were slightly lower for H-Gait with respect to STEP32 for the ankle (by 1.9° for NW, and 1.6° for OW) and for the knee (by 4.1° for NW, and 1.8° for OW). More evident differences were found for hip joint, with ROMs values higher for H-Gait (by 6.8° for NW, and 9.5° for OW). NW and OW showed significant differences considering STEP32 (p = 0.0004), but not H-Gait (p = 0.06). In particular, overweight/obese subjects showed a higher cadence (55.0 vs. 52.3 strides/min) and a lower hip ROM (23.0° vs. 27.3°) than normal weight subjects. Conclusions: The two systems can be considered interchangeable for what concerns joint kinematics, except for the hip, where discrepancies were evidenced. Differences between normal and overweight/obese subjects were statistically significant using STEP32. The same tendency was observed using H-Gait.

Development of an Inertial Motion Capture System for Clinical Application

The ability to capture human motion based on wearable sensors has a wide range of applications, e.g., in healthcare, sports, well-being, and workflow analysis. This article focuses on the development of an online-capable system for accurately capturing joint kinematics based on inertial measurement units (IMUs) and its clinical application, with a focus on locomotion analysis for rehabilitation. The article approaches the topic from the technology and application perspectives and fuses both points of view. It presents, in a self-contained way, previous results from three studies as well as new results concerning the technological development of the system. It also correlates these with new results from qualitative expert interviews with medical practitioners and movement scientists. The interviews were conducted for the purpose of identifying relevant application scenarios and requirements for the technology used. As a result, the potentials of the system for the different identified application scenarios are discussed and necessary next steps are deduced from this analysis.

Towards Mobile Gait Analysis: Concurrent Validity and Test-Retest Reliability of an Inertial Measurement System for the Assessment of Spatio-Temporal Gait Parameters

The purpose of this study was to assess the concurrent validity and test–retest reliability of a sensor-based gait analysis system. Eleven healthy subjects and four Parkinson’s disease (PD) patients were asked to complete gait tasks whilst wearing two inertial measurement units at their feet. The extracted spatio-temporal parameters of 1166 strides were compared to those extracted from a reference camera-based motion capture system concerning concurrent validity. Test–retest reliability was assessed for five healthy subjects at three different days in a two week period. The two systems were highly correlated for all gait parameters (r>0.93). The bias for stride time was 0±16 ms and for stride length was 1.4±6.7 cm. No systematic range dependent errors were observed and no significant changes existed between healthy subjects and PD patients. Test-retest reliability was excellent for all parameters (intraclass correlation (ICC) > 0.81) except for gait velocity (ICC > 0.55). The sensor-based system was able to accurately capture spatio-temporal gait parameters as compared to the reference camera-based system for normal and impaired gait. The system’s high retest reliability renders the use in recurrent clinical measurements and in long-term applications feasible.