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

Assessment of an IMU-Based Experimental Set-Up for Upper Limb Motion in Obese Subjects

In recent years, wearable systems based on inertial sensors opened new perspectives for functional motor assessment with respect to the gold standard motion capture systems. The aim of this study was to validate an experimental set-up based on 17 body-worn inertial sensors (Awinda, Xsens, The Netherlands), addressing specific body segments with respect to the state-of-the art system (VICON, Oxford Metrics Ltd., Oxford, UK) to assess upper limb kinematics in obese, with respect to healthy subjects. Twenty-three obese and thirty healthy weight individuals were simultaneously acquainted with the two systems across a set of three tasks for upper limbs (i.e., frontal arm rise, lateral arm rise, and reaching). Root Mean Square error (RMSE) was computed to quantify the differences between the measurements provided by the systems in terms of range of motion (ROM), whilst their agreement was assessed via Pearson's correlation coefficient (PCC) and Bland-Altman (BA) plots. In addition, the signal waveforms were compared via one-dimensional statistical parametrical mapping (SPM) based on a paired t-test and a two-way ANOVA was applied on ROMs. The overall results partially confirmed the correlation and the agreement between the two systems, reporting only a moderate correlation for shoulder principal rotation angle in each task (r~0.40) and for elbow/flexion extension in obese subjects (r = 0.66), whilst no correlation was found for most non-principal rotation angles (r < 0.40). Across the performed tasks, an average RMSE of 34° and 26° was reported in obese and healthy controls, respectively. At the current state, the presence of bias limits the applicability of the inertial-based system in clinics; further research is intended in this context.

Minimum number of inertial measurement units needed to identify significant variations in walk patterns of overweight individuals walking on irregular surfaces

Gait data collection from overweight individuals walking on irregular surfaces is a challenging task that can be addressed using inertial measurement unit (IMU) sensors. However, it is unclear how many IMUs are needed, particularly when body attachment locations are not standardized. In this study, we analysed data collected from six body locations, including the torso, upper and lower limbs, to determine which locations exhibit significant variation across different real-world irregular surfaces. We then used deep learning method to verify whether the IMU data recorded from the identified body locations could classify walk patterns across the surfaces. Our results revealed two combinations of body locations, including the thigh and shank (i.e., the left and right shank, and the right thigh and right shank), from which IMU data should be collected to accurately classify walking patterns over real-world irregular surfaces (with classification accuracies of 97.24 and 95.87%, respectively). Our findings suggest that the identified numbers and locations of IMUs could potentially reduce the amount of data recorded and processed to develop a fall prevention system for overweight individuals.

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.

Evaluating the difference in walk patterns among normal-weight and overweight/obese individuals in real-world surfaces using statistical analysis and deep learning methods with inertial measurement unit data

Unusual walk patterns may increase individuals' risks of falling. Anthropometric features of the human body, such as the body mass index (BMI), influences the walk patterns of individuals. In addition to the BMI, uneven walking surfaces may cause variations in the usual walk patterns of an individual that will potentially increase the individual's risk of falling. The objective of this study was to statistically evaluate the variations in the walk patterns of individuals belonging to two BMI groups across a wide range of walking surfaces and to investigate whether a deep learning method could classify the BMI-specific walk patterns with similar variations. Data collected by wearable inertial measurement unit (IMU) sensors attached to individuals with two different BMI were collected while walking on real-world surfaces. In addition to traditional statistical analysis tools, an advanced deep learning-based neural network was used to evaluate and classify the BMI-specific walk patterns. The walk patterns of overweight/obese individuals showed a greater correlation with the corresponding walking surfaces than the normal-weight population. The results were supported by the deep learning method, which was able to classify the walk patterns of overweight/obese (94.8 ± 4.5%) individuals more accurately than those of normal-weight (59.4 ± 23.7%) individuals. The results suggest that application of the deep learning method is more suitable for recognizing the walk patterns of overweight/obese population than those of normal-weight individuals. The findings from the study will potentially inform healthcare applications, including artificial intelligence-based fall assessment systems for minimizing the risk of fall-related incidents among overweight and obese individuals.

3D Gait Analysis and Patient-reported Outcomes of Femoral Osteotomies for Torsional Deformity

BACKGROUND

Idiopathic torsional deformities causing pain and/or functional difficulty is an indication for a femoral derotational osteotomy (FDRO). Past studies have focused entirely on children with internal femoral torsional deformity (IFTD). This study aims to compare gait and outcomes between children with IFTD and those with external femoral torsional deformity (EFTD) after a FDRO.

METHODS

A retrospective review of all patients who underwent an FDRO between 1997 and 2020 at our institution. Data on typically developing (TD) children with no torsional deformity was used as a control group. We analyzed preoperative and postoperative standardized physical examination, 3-dimensional gait analysis, and Pediatric Outcomes Data Collection Instrument questionnaires.

RESULTS

There were 54 patients in total (IFTD=37, EFTD=17) and 20 patients in the control group. The EFTD cohort was older (IFTD=11.7, EFTD=14.7, P <0.05) and had a higher body mass index both preoperatively (IFTD=21.1 kg/m 2 , EFTD=32.1 kg/m 2 , P <0.05) and postoperatively (IFTD=20.2 kg/m 2 , EFTD=34.1 kg/m 2 , P <0.05). Preoperatively, 3-dimensional gait analysis elicited mean hip rotation in stance was more internal for IFTD cohort (10.8 degrees) and external for the EFTD cohort (-17.8 degrees) in comparison to the TD (2.4 degrees, P <0.001). Postoperatively, dynamic mean hip rotation during stance was -1.4 degrees for IFTD, whereas for EFTD, it was -5.4 degrees, which was different to the TD ( P <0.05). The IFTD group's Pediatric Outcomes Data Collection Instrument improved for transfer/basic mobility, sports/physical function, global functioning, and satisfaction with symptoms ( P <0.05). The EFTD group that only reported an improvement with the satisfaction with symptoms after surgery ( P <0.05).

CONCLUSIONS

Adolescents with surgically corrected IFTD show more improvement in gait and in patient-reported outcomes than those with surgically corrected EFTD. Children with EFTD persist in external rotation and have less satisfactory patient-reported outcomes after a FDRO in comparison those with IFTD.

LEVEL OF EVIDENCE

Level III-retrospective comparative study.

The ankle kinematic reference of normal gait pattern in Thai adults

Objective

This study was aimed to establish the reference values of ankle kinematics and factors associated with ankle kinematics of healthy Thai adults.

Methods

A prospective cohort was conducted among healthy volunteers aged between 18 and 40 years and evaluated gait analysis between 2016 and 2020. After applying the modified Halen Hayes marker set, participants were assigned to walk 8–10 rounds with their preferred speed. Demographic data i.e., age, gender and body mass index (BMI) and ankle kinematics (varus-valgus, dorsiflexion-plantar flexion, foot progression, and ankle rotation) using motion analysis software were recorded and analyzed.

Results

98 volunteers (60 females and 38 males) aged 28.6 ± 5.4 years with body mass index 21.2 ± 2.0 kg/m2 were included. The average ranges of ankle kinematics entire gait cycle were varus-valgus −1.62 to 3.17 degrees, dorsiflexion-plantar flexion 0.67 to 14.52 degrees, foot progression −21.73 to −8.47 degrees, and ankle rotation 5.22 to 9.74 degrees. The ankle kinematic data in this study population was significantly different from the normal values supplied by OrthoTrak software of the motion analysis program, especially more ankle internal rotation at mid-stance (5.22 vs. −12.10 degrees) and terminal stance (5.48 vs. −10.74 degrees) with P &lt; 0.001. Foot progression significantly exhibited more external rotation for 1.5 degrees on the right compared to the left side, and for 5 degrees more in males than females. One increment in age was significantly correlated with ankle internal rotation at mid-swing (coefficient 0.21 degrees, P = 0.039). BMI had no statistical association with ankle kinematics. Statistical parametric mapping for full-time series of angle assessments showed significantly different foot progression at initial contact and terminal stance between sides, and our ankle kinematics significantly differed from the reference values of the motion analysis program in all planes (P &lt; 0.05).

Conclusion

The reference of ankle kinematics of Thai adults was established and differences between sides and the normal values of the motion analysis program were identified. Advanced age was associated with ankle internal rotation, and male gender was related to external foot progression. Further studies are needed to define all-age group reference values.

The Effects of Overweight and Obesity on Obstacle Crossing During Walking: Protocol for a Systematic Review

BACKGROUND

Overweight and obesity are significant global health concerns that involve deficits in gait and balance that affect daily activities. Although much is reported about the effect of overweight and obesity on gait during unobstructed walking, not much is known about how overweight and obesity could impact gait under more challenging conditions, such as environments with obstacles.

OBJECTIVE

The aim of this study is to systematically review and synthesize the available data regarding the effects of overweight and obesity on obstacle crossing during walking.

METHODS

This review will follow the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-analyses) guidelines. PubMed, Web of Science, Scopus, and SPORTDiscus will be systematically searched with no limitations on publication date. Only full-text English-language articles published in a peer-reviewed journal will be included. Included articles must have compared obstacle crossing during walking in individuals with overweight or obesity to individuals of normal body weight. A total of 2 independent reviewers will select the articles and extract the following 4 sets of data: (1) study characteristics, (2) sample description, (3) obstacle crossing task protocol, and (4) main results obtained. If a considerable number of homogeneous papers are included, a meta-analysis will be conducted. A preliminary search was conducted in November 2021.

RESULTS

The results will include the article selection flowchart as well as tables and figures synthesizing the extracted data on the effects of overweight and obesity on obstacle crossing during walking. The preliminary search identified 73 original records, of which 5 articles met the inclusion criteria.

CONCLUSIONS

This review will present researchers and clinicians with an overview of published studies that have compared the performance of obstacle crossing for individuals with overweight and obesity to those of normal body weight. Gaining insight into the control strategies adopted by individuals with overweight and obesity is critical for safe and successful obstacle crossing in this population. We therefore believe that our findings could be useful for identifying people at risk of falls and developing and implementing fall prevention programs for individuals with overweight and obesity.

TRIAL REGISTRATION

PROSPERO CRD42021269949; https://tinyurl.com/3yrwccu4.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/36234.

Inertial Sensor-to-Segment Calibration for Accurate 3D Joint Angle Calculation for Use in OpenSim

Inertial capture (InCap) systems combined with musculoskeletal (MSK) models are an attractive option for monitoring 3D joint kinematics in an ecological context. However, the primary limiting factor is the sensor-to-segment calibration, which is crucial to estimate the body segment orientations. Walking, running, and stair ascent and descent trials were measured in eleven healthy subjects with the Xsens InCap system and the Vicon 3D motion capture (MoCap) system at a self-selected speed. A novel integrated method that combines previous sensor-to-segment calibration approaches was developed for use in a MSK model with three degree of freedom (DOF) hip and knee joints. The following were compared: RMSE, range of motion (ROM), peaks, and R² between InCap kinematics estimated with different calibration methods and gold standard MoCap kinematics. The integrated method reduced the RSME for both the hip and the knee joints below 5°, and no statistically significant differences were found between MoCap and InCap kinematics. This was consistent across all the different analyzed movements. The developed method was integrated on an MSK model workflow, and it increased the sensor-to-segment calibration accuracy for an accurate estimate of 3D joint kinematics compared to MoCap, guaranteeing a clinical easy-to-use approach.

Influence of obesity on spatiotemporal gait parameters among female students from Jouf University, Saudi Arabia

Study aim: The aim of the current study is to explore the effect of obesity on spatiotemporal parameters of gait in obese young female students.

Material and methods: A cross-sectional study with fifteen obese female university students (mean age = 20.3 ± 1.6, mean BMI = 36.2 ± 4.6) and fifteen normal weight female university students (mean age = 20.9 ± 2, mean BMI = 22.6 ± 2.4) was conducted. The spatiotemporal gait parameters were evaluated using GAITRite® walkway (Frankline, USA, Model No. TR30RAM090 with software version 4.89C2).

Results: Independent sample t-test showed statistical significant differences in some spatiotemporal gait parameters between normal and obese subjects with statistically significant reductions of single-limb support time, step length, stride length, and velocity in the obese subjects rather than normal subjects (p = 0.031, 0.015, 0.039, and 0.002, respectively). Moreover, there were statistically significant increases of step time, stride time in the obese subjects rather than the normal subjects (p = 0.038, 0.017, respectively).

Conclusion: These results suggested that obesity is a factor that adversely affects the spatiotemporal gait parameters in the obese young female. This may be contributed to decrease the joints’ mobility and increase the incidence of joint osteoarthritis. So, it is recommended to encourage the sufficient physical activity and weight reduction among obese female students.

Identification of the Visually Prominent Gait Parameters for Forensic Gait Analysis

Walking patterns can be used as a key parameter in identifying individuals, as it varies visually depending on one’s body size as well as their habits, gender, and age group. In this study, we measure the gait characteristics of a large number of subjects using 34 visual parameters to identify significant parameters that can be used to distinguish individual walking features. We recorded 291 subjects’ walking on a constructed footpath using four video cameras, and data on parameters was calculated at the points of double support, toe-off, and heel-strike. K-means Clustering Analysis and ANOVA were conducted to determine the difference between age, gender, and BMI. As a result, we confirm that parameters related to the spine, neck, and feet are useful for identifying individuals. In the comparative analysis between age groups, the older the age, the more significant variables appeared in the upper body. The difference between genders showed significant parameters in both the upper and lower bodies of males. Similarly, among the large BMI groups, we also derived significant results in the upper and lower bodies. The key parameters derived from this study can be used more effectively in the real-world visual analysis of gait, as the walking characteristics of a large number of subjects have been measured with a similar view as real-world CCTV. This study will be effectively utilized as a foundation for future research attempting to identify people through their gait by distinguishing major gait characteristic differences.

Determine the kinematics and kinetics parameters associated with bilateral gait patterns among healthy, overweight, and obese adults

BACKGROUND AND AIM

Biomechanical analysis of gait is important to obtain information regarding the lower limb impairments and dysfunction during locomotion. This study aimed to determine the potential difference among healthy, overweight, and obese participants and their impact on gait parameters by observing the kinematic and kinetics parameters.

METHODS

A cross-sectional study conducted with forty (15 healthy, 12, overweight, 13 obese) male participants. All participants were non-smokers, and their physical activity level was 7000±2142 steps per day. Participants anthropometric characteristics were age:21.57±1.46 years; height:173. 63±6.43 cm, body mass;86.15±23.36 kg., body mass index (BMI) :28.57±7.68 kg/m2, body fat:29.93±9.44%. A bioelectrical impedance device was used to determine participants' body composition and health status. A portable pressure sensor mat (Walkway) from Tekscan was used to measure bilateral gait parameters kinematically and kinetically. One-way analysis of variance was used to determine the differences between groups.

RESULTS

Significant differences were found between health, overweight, and obese participant for different bilateral gait's kinematic and kinetic parameters as cadence, gait velocity, step time, step length, step velocity, step width, stride time, stride length, stride velocity, maximum force, maximum peak pressure, active propulsion, and passive propulsion except impulse at .05 level of significance.

CONCLUSIONS

The findings shows that kinematics and kinetics parameters of gait were affected by the status of their BMI. Current research suggests that increased body weight interferes with normal musculoskeletal function via a range of kinematic and kinetic deficits. More research is required to accurately understand the structural and functional restriction imposed by overweight and obese individuals.

Association between body mass index and spatial gait parameters in primary school children

Background

Increasing BMI is associated with increased risk of mortality, cardiovascular disease, and some cancers whereas a lower BMI is associated with an increased risk of mortality, postsurgical complications, infection, and length of hospital stay as a result. Locomotion is a unique feature of the animal kingdom. It allows individuals to meet others, to find better food and a better climate, to pursue prey, or to escape impending danger. The aim of the current study was to determine the correlation between body mass index (BMI) and spatial gait parameters in primary school children.

Results

A total of 320 healthy children from primary schools were enrolled. The participants comprised 185 boys and 135 girls with a mean age of 10.05 ± 0.95 years, mean weight of 38.49 ± 12.2 kg, a mean height of 139.25 ± 10.12 cm, and a mean BMI of 19.35 ± 4.55 kg/m2. BMI was evaluated by the KINLEE Electronic Personal Scale with Height Measurement and CDC charts for boys and girls and equation of BMI. Spatial gait parameters were evaluated by a pediatric run-based anaerobic sprint test with an Omron pedometer to assess step and stride length.

Statistical analysis was performed by Pearson’s correlation coefficient to study the relationship between variables. A correlation was performed between the variables, and the coefficient of determination was calculated. The significance level was set at 5% for all analyses. There was no significant relationship between BMI and spatial gait parameters (step length and stride length) (r = 0.008, p = 0.88 and r = 0.02, p = 0.7, respectively).

Conclusion

According to the results, we concluded that there was no significant relationship between BMI and the measured gait parameters (step length and stride length).

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.

Gait Kinematic and Kinetic Characteristics of Older Adults With Mild Cognitive Impairment and Subjective Cognitive Decline: A Cross-Sectional Study

Background

Older adults with mild cognitive impairment (MCI) have slower gait speed and poor gait performance under dual-task conditions. However, gait kinematic and kinetic characteristics in older adults with MCI or subjective cognitive decline (SCD) remain unknown. This study was designed to explore the difference in gait kinematics and kinetics during level walking among older people with MCI, SCD, and normal cognition (NC).

Methods

This cross-sectional study recruited 181 participants from July to December 2019; only 82 met the inclusion criteria and consented to participate and only 79 completed gait analysis. Kinematic and kinetic data were obtained using three-dimensional motion capture system during level walking, and joint movements of the lower limbs in the sagittal plane were analyzed by Visual 3D software. Differences in gait kinematics and kinetics among the groups were analyzed using multivariate analysis of covariance (MANCOVA) with Bonferroni post-hoc analysis. After adjusting for multiple comparisons, the significance level was p < 0.002 for MANCOVA and p < 0.0008 for post-hoc analysis.

Results

Twenty-two participants were MCI [mean ± standard deviation (SD) age, 71.23 ± 6.65 years], 33 were SCD (age, 72.73 ± 5.25 years), and 24 were NC (age, 71.96 ± 5.30 years). MANCOVA adjusted for age, gender, body mass index (BMI), gait speed, years of education, diabetes mellitus, and Geriatric Depression Scale (GDS) revealed a significant multivariate effect of group in knee peak extension angle (F = 8.77, p < 0.0001) and knee heel strike angle (F = 8.07, p = 0.001) on the right side. Post-hoc comparisons with Bonferroni correction showed a significant increase of 5.91° in knee peak extension angle (p < 0.0001) and a noticeable decrease of 6.21°in knee heel strike angle (p = 0.001) in MCI compared with NC on the right side. However, no significant intergroup difference was found in gait kinetics, including dorsiflexion, plantar flexion, knee flexion, knee extension, hip flexion, and hip extension(p > 0.002).

Conclusion

An increase of right knee peak extension angle and a decrease of right knee heel strike angle during level walking were found among older adults with MCI compared to those with NC.

Comparison of gluteus medius strength between individuals with obesity and normal-weight individuals: a cross-sectional study

Background

The hip abductor muscles, primarily the gluteus medius, play an important role in stabilizing the pelvis during gait. Gluteus medius weakness is associated with biomechanical changes and musculoskeletal disorders. Individuals with obesity can have great difficulty maintaining abductor muscular function due to being overweight and possibly experiencing a decrease in muscle mass. However, it is still unclear whether the musculature of person with obesity can compensate for these changes. Therefore, the aim of this study was to compare gluteus medius strength between individuals with obesity and normal-weight individuals using a digital hand-held dynamometer.

Methods

Twenty-five participants with obesity (BMI > 35 kg/m²) were matched for sex, age, and height with normal-weight individuals. Gluteus medius strength was measured by a single examiner using a belt-stabilized hand-held digital dynamometer placed on the knee of the individuals positioned in lateral decubitus. Three measurements were recorded with rest intervals, and only the highest value measured for each limb was used for analysis. The differences between pairs were calculated, and the normality of the data was assessed using the Shapiro-Wilk test (p < 0.05). The matrices of the variables were standardized and analysed using principal component analysis (PCA).

Results

For the strength variables (Newtons) on both sides, no significant differences were detected between the groups (p > 0.05). However, significant differences were detected in these variables between the groups (p < 0.05) when the measurements were normalized to body weight (Newtons/kilograms). PCA indicated that both the absolute and normalized values of strength are lower in participants with obesity than in normal-weight.

Conclusions

These findings suggest that people with obesity could have the same or less strength (PCA) to move more mass, which may imply a relative weakness that induces functional limitations.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12891-021-04470-8.

Surface Electromyography Applied to Gait Analysis: How to Improve Its Impact in Clinics?

Surface electromyography (sEMG) is the main non-invasive tool used to record the electrical activity of muscles during dynamic tasks. In clinical gait analysis, a number of techniques have been developed to obtain and interpret the muscle activation patterns of patients showing altered locomotion. However, the body of knowledge described in these studies is very seldom translated into routine clinical practice. The aim of this work is to analyze critically the key factors limiting the extensive use of these powerful techniques among clinicians. A thorough understanding of these limiting factors will provide an important opportunity to overcome limitations through specific actions, and advance toward an evidence-based approach to rehabilitation based on objective findings and measurements.