Spatiotemporal Gait Analysis Research Articles

Plantar Compartment Block Improves Enhanced Recovery after Hallux Valgus Surgery: A Randomized, Comparative, Double-blind Study.

Walking ability is a key factor in enhanced recovery after foot ambulatory surgery. Plantar compartment block offers an analgesic alternative to popliteal sciatic nerve block (PSNB) for hallux valgus surgery. The objective of this study was to compare these two regional anesthesia strategies on patients' ability to recover a painless unaided walk. This prospective double-blinded (patient; observing anesthesiologist) randomized study compared patients scheduled for hallux valgus surgery receiving PSNB with 1% mepivacaine, then combined plantar and peroneal nerve blocks (plantar compartment block [PCB] group) with ropivacaine 0.5% and dexamethasone, or PSNB with ropivacaine 0.5% and dexamethasone (control group). The primary outcome was the patient's ability to walk unaided 6 h after PSNB. The test was performed on a GAITRite, spatio-temporal gait analysis mat. For 3 days, the number of patient steps, pain levels, rescue analgesics, patient's experience, and adverse events were assessed. Sixty patients were included and 59 were analyzed. The number of patients walking unaided on the GAITRite mat was significantly higher in the PCB group (21 of 30, 70%) than in the control group (4 of 29, 13.8%; P < 0.001). Gait quality using the Functional Ambulation Profile score was 63 ± 13.6 in the PCB group and 49.5 ± 4.7 in the control group (P < 0.001). Median time to free ambulation at home was significantly lower in the PCB group (9 h [8.2 to 11.8]) than in the control group (33.5 h [24 to 47]; P < 0.001). Postoperative pain did not differ between the groups (β = -0.41 [-1.78 to 0.95]; P = 0.548). The number of steps on day 3, the time of first rescue analgesic, the number of patients using rescue analgesia, consumption of morphine, and patient's experience did not differ between the groups. PCB decreased the time to return to unaided walking, with improved gait, compared with PSNB, improving effective analgesia and low consumption of rescue analgesics. This innovative regional anesthesia strategy enhanced recovery after surgery.

Relationship between sensation and balance and gait in multiple sclerosis patients with mild disability

BackgroundPatients with Multiple Sclerosis (PwMS) often experience sensory, balance, and gait problems. Impairment in any sensation may increase imbalance and gait disorder in PwMS. This study aimed to (1) compare foot plantar sensations, knee position sense, balance, and gait in PwMS compared to Healthy Individuals (HI) and (2) examine the relationship between plantar sensations, knee position sense, balance, and gait in PwMS. MethodsThirty PwMS with mild disability and 10 HI participated in this study. Light touch threshold, two-point discrimination, vibration duration, and knee position sense were examined on the Dominant Side (DS) and Non-Dominant Side (NDS). Balance and spatio-temporal gait analysis were evaluated in all participants. ResultsPwMS had higher postural sway with eyes closed on the foam surface, longer swing phase of DS, longer single support phase of NDS, and shorter double support phase of DS compared to HI (p < 0.05). The results of regression analysis showed that the light touch thresholds of the 1st and 5th toes of the DS were associated with postural sway in different sensory conditions (p < 0.05). In contrast, the light touch thresholds of the 1st and 5th toes, two-point discrimination of the heel, vibration duration of the 1st metatarsal head and knee position sense of the NDS, and light touch threshold in the medial arch of both sides were associated with the gait parameters (p < 0.05). ConclusionPwMS, even with mild disabilities needs neurorehabilitation to improve plantar sensation and knee position sense.

GAIT- AND BALANCE-RELATED FACTORS AFFECTING PARTICIPATION IN SCHOOL-AGED CHILDREN WITH UNILATERAL CEREBRAL PALSY

Although gait and balance impairments are prevalent in children with unilateral cerebral palsy (UCP), their effects on participation are not completely elucidated. This study aims to explore factors affecting participation in children with UCP, particularly those related to gait and balance. This descriptive relation-seeker study was completed with 40 children with UCP at Gross Motor Function Classification System (GMFCS) levels I and II (50% female; median age = 11 (7-12)years). "The Gross Motor Function Measure (GMFM-66)", "The Pediatric Balance Scale (PBS)", "The Timed Up and Go test (TUG) and The Functional Mobility Scale (FMS)", and "The BTS G-Walk Spatiotemporal Gait Analysis System" were used to evaluate the gross motor function, balance, functional mobility, and quantitative gait parameters, respectively. "The Canadian Occupational Performance Measure (COPM)" was employed to evaluate participation. Variables affecting the COPM scores were analyzed by multivariate regression analysis.The factors affecting the COPM-performance score were cadence (B = 79.859, p = 0.001) and FMS (B = 0.352, p

The effects of standard and modified LSVT BIG therapy protocols on balance and gait in Parkinson's disease: A randomized controlled trial.

Lee Silverman voice treatment (LSVT) BIG is an exercise program developed for patients with Parkinson's disease (PwPD), consisting of sets of exercises performed for 4 consecutive days a week for 4 weeks. However, the standard protocol suggests a treatment frequency difficult to follow for most patients who have difficulties reaching rehabilitation clinics. Our aim was to compare the standard LSVT BIG protocol with a modified LSVT (m-LSVT) BIG protocol (twice a week in the clinic for 4 weeks and twice a week at home for 4 weeks). In this randomized controlled trial, 16 PwPD (aged 18-80 years, Hoehn and Yahr stages I-III) were recruited into two groups. The LSVT group received standard LSVT BIG training (four times per week for 4 weeks at the clinic). The other group was given m-LSVT BIG exercises, but unlike the LSVT group, the m-LSVT group exercised twice a week at the clinic and twice a week at home for 4 weeks. The Berg Balance Scale was used to assess functional balance. Biodex Balance System was used to assess laboratory balance measures. Timed Up and Go test and G-Walk sensor system were used to assess functional mobility and spatiotemporal gait analysis. Significant group-by-time interactions on the eyes open-firm surface score of the modified clinical test of sensory integration of balance (F=10.138, p=.007) and gait cycle symmetry index (F=10.470, p=.010) were found to be in favor of the LSVT group. Additionally, post hoc analyses revealed that both groups significantly improved postural stability, gait speed, motor symptoms, and functional mobility (p<.05). The results revealed the beneficial effects of the modified protocol on balance and gait in PwPD, as well as the superiority of the standard LSVT BIG protocol. The m-LSVT BIG protocol may be an effective intervention method, especially for PwPD who have difficulty adapting to the treatment frequency of the standard protocol.

Parâmetros de referência espaço-temporais de um sensor inercial para sujeitos brasileiros sadios

Gait analysis in a laboratory may be expensive, time-consuming, and restricted to a controlled environment. Validated wearable technology may be an alternative to such analysis. However, wearable technologies should demonstrate reference values of a healthy population. Objective: To establish spatio-temporal gait reference values of an accelerometer (G-Walk) in a healthy Brazilian population. Methods: This is a cross-sectional study with 124 healthy subjects evaluated with G-Walk in the 6-minute and 10-meter walk tests (6MWT and 10MWT). Gait parameters of Velocity, Cadence, Distance, and gait symmetry variables were retrieved for analysis. Clinical and demographical characteristics were also collected and tested with simple linear regression as covariables of the gait characteristics. The bootstrapped 5th percentile of the gait parameter established the reference values. If a covariable influence was found, the reference values were established by subgroup analysis according to the covariable. Results: The study analyzed 114 subjects, mostly women (67.74%), aged 39.36 (SD 12.18). Height was a covariable of cadence for the 10MWT and cadence and stride length for the 6MWT. Age and sex combined were covariables of 6MWT velocity, and sex alone was a covariable of 6MWT. All reference values for symmetry were above 89%, velocity at the 10MWT was above 1.0m/s, and distance at the 6MWT was 354m and 359.5 for females and males, respectively. Conclusions: Our study generated reference values for spatio-temporal gait analysis with G-Walk of a population of a major urban area, considering the covariables of age, height, and sex.

The Use of Spatiotemporal Gait Analysis in Diagnosing Pathologies: A Review

Background: Gait, particularly walking speed (WS), has emerged as an essential indicator of health. WS is indicative of current health and predicts future health trends, especially in older adults. Notably, a 0.1 m/s WS increase corresponds to a 12% rise in survival among this demographic, establishing WS as a powerful prognostic tool. This has resulted in the designation of WS as the "6th vital sign", which is applicable to a broad spectrum of medical conditions. Additionally, computerized gait analysis reveals nuanced differences in movement patterns across age groups. This review provides a detailed insight into the multifaceted nature of gait and its health implications. Purpose: This review's primary objective is to underscore the significance of gait and WS as pivotal health markers. By framing WS as the "6th vital sign" and delving into gait's complexities using digital analysis, the review aims to elucidate how gait metrics inform health trajectories in diverse medical scenarios. Methods: Our analysis employed laboratory-based three-dimensional gait techniques. Kinematic data were obtained using infrared markers on the body and triangulated with multiple cameras. Concurrently, force plates within electronic pathways captured kinetic data, such as ground reaction forces. Data collection was guided by a pre-established checklist encompassing specific conditions (including Parkinson’s Disease, Lumbar disk herniation, Chronic Mechanical Lower back pain, Lumbar Spinal Stenosis, Depression, Hip Osteoarthritis, COPD), analysis tools (e.g., type of cameras, force plates), kinematic and kinetic parameters (e.g., support moments, momentum), and potential psychological impacts on participants (e.g., Hawthorne and “white-coat” effects). The clinical significance of our data was validated against existing research on gait pattern variations in mentioned conditions, ensuring quality through stringent research standards. Conclusion: Spatiotemporal gait analysis, especially with machine learning application, is nascent. Although there's potential in its diagnostic capability, extensive research is needed for clinical use. Our focus was primarily on Parkinson’s Disease, aiming to gauge machine learning's role in discerning pathological from normal gait using spatiotemporal metrics. Future investigations should explore this approach for different gait-related conditions.

Spatiotemporal and kinematic gait analysis in patients with knee osteoarthritis and femoral varus deformity

BackgroundKnee osteoarthritis (OA) is commonly combined with the presentation of a coronal deformity of the knee. The bony origin of the knee varus deformity can be classified as tibial origin, femoral origin, or a combination of tibial and femoral causes. Deformities of tibial origin are mostly common clinically, while patients with knee OA with femoral varus deformity are less common. Research questionDo hip, knee and ankle kinematics and spatiotemporal parameters differ between patients with knee OA with femoral varus deformity and healthy subjects? MethodsTwenty-five patients (14 females and 11 males) with knee OA and femoral varus deformity and 20 healthy subjects (12 males and 8 females) as control group were included in this study. The kinematic parameters of the hip-knee-ankle joint and spatiotemporal gait parameters were included in the study. ResultsThis study found that the step speed and step length of the knee OA with femoral varus (KOAF) group were smaller than those of the control group, while double support period percentage was greater in the KOAF group. Significant differences were found in the maximum knee extension angle, maximum knee flexion angle, knee flexion range of motion, maximum hip flexion angle, maximum hip extension angle, and hip flexion range of motion between the two groups. After comparing the ankle motion between the two groups, significant differences were found in the maximum eversion angle, inversion range of motion, maximum ankle abduction angle, and abduction range of motion. SignificanceKnee OA with femoral varus deformity causes adaptive changes in the kinematic parameters of hip, knee and ankle joints and spatiotemporal gait parameters to alleviate symptoms and maintain normal activity.

Pain severity, distribution, and duration are associated with spatiotemporal gait performance in community-dwelling older adults with chronic musculoskeletal pain

BackgroundOur current understanding of the impact of chronic pain on spatiotemporal gait performance has mainly been achieved through comparison studies between individuals with and without chronic pain. Further investigation into the relationship between specific outcome measures of chronic pain and gait may improve our understanding of the impact of pain on gait and may benefit future interventions that aim to improve mobility in this population. Research questionWhich pain outcome measures are associated with spatiotemporal gait performance in older adults with chronic musculoskeletal pain? MethodsThis study was secondary analysis of older adult participants enrolled in the Neuromodulatory Examination of Pain and Mobility Across the Lifespan (NEPAL) study (n = 43). Pain outcome measures were obtained using self-reported questionnaires, and spatiotemporal gait analysis was conducted using an instrumented gait mat. Separate multiple linear regressions were run to determine which pain outcome measurements were associated with gait performance. ResultsHigher pain severities were associated with shorter stride lengths (β = −0.336, p = 0.041), shorter swing times (β = −0.345, p = 0.037), and longer double support times (β = 0.342, p = 0.034). A greater number of pain sites was associated with a wider step width (β = 0.391, p = 0.024). Longer pain durations were associated with shorter double support times (β = −0.373, p = 0.022). SignificanceThe results of our study illustrate that specific pain outcomes measures are associated with specific gait impairments in community-dwelling older adults with chronic musculoskeletal pain. As such, pain severity, number of pain sites, and pain duration should be considered when developing mobility interventions in this population to reduce disability.

The Effect of Kinesio Taping Over the Gluteal Muscles on Activity and Participation in Children with Unilateral Cerebral Palsy: A Preliminary Randomized Controlled Study

Background: Insufficiencies of gluteus medius and maximus muscles in children with unilateral cerebral palsy (CP) may restrict activity and participation by affecting gait, gross motor functions, and balance. Objectives: The present study aimed to elucidate the effect of Kinesio taping (KT) applied to the gluteus medius and maximus muscles on activity and participation in children with CP. Methods: The study was completed with 20 children with unilateral CP who were randomly divided into 2 groups: The KT group received KT and physiotherapy (n = 11), and the control group received only physiotherapy (n = 9). The KT application was administered for 4 weeks. The activity was evaluated with a BTS G-Walk Spatiotemporal Gait Analysis System, Timed Up and Go test (TUG), Functional Mobility Scale (FMS), Gross Motor Function Measure (GMFM), and Pediatric Balance Scale (PBS); in addition, participation was evaluated using the Canadian Occupational Performance Measure (COPM). Results: The KT group showed significant improvements in the gait parameter (cadence; P = 0.009), pelvic tilt symmetry (P = 0.017), pelvic rotation symmetry (P = 0.018), gait symmetry (P &lt; 0.001), FMS (P = 0.07), TUG, GMFM, PBS, and COPM scores (P &lt; 0.001) in the medium-term compared to the control group. It was also found that gait (cadence; P = 0.004) and functional mobility (P &lt; 0.001) improved in the immediate term than in the KT group. Conclusions: KT combined with conventional physiotherapy can improve cadence and functional mobility in the immediate term, as well as gait and pelvic symmetry, functional mobility, gross motor function, balance, and participation in the medium term in children with unilateral CP. Further randomized controlled studies addressing large samples and long-term effects are warranted.

The Effect of Kinesio Taping Over the Gluteal Muscles on Activity and Participation in Children with Unilateral Cerebral Palsy: A Preliminary Randomized Controlled Study

Background: Insufficiencies of gluteus medius and maximus muscles in children with unilateral cerebral palsy (CP) may restrict activity and participation by affecting gait, gross motor functions, and balance. Objectives: The present study aimed to elucidate the effect of Kinesio taping (KT) applied to the gluteus medius and maximus muscles on activity and participation in children with CP. Methods: The study was completed with 20 children with unilateral CP who were randomly divided into 2 groups: The KT group received KT and physiotherapy (n = 11), and the control group received only physiotherapy (n = 9). The KT application was administered for 4 weeks. The activity was evaluated with a BTS G-Walk Spatiotemporal Gait Analysis System, Timed Up and Go test (TUG), Functional Mobility Scale (FMS), Gross Motor Function Measure (GMFM), and Pediatric Balance Scale (PBS); in addition, participation was evaluated using the Canadian Occupational Performance Measure (COPM). Results: The KT group showed significant improvements in the gait parameter (cadence; P = 0.009), pelvic tilt symmetry (P = 0.017), pelvic rotation symmetry (P = 0.018), gait symmetry (P &lt; 0.001), FMS (P = 0.07), TUG, GMFM, PBS, and COPM scores (P &lt; 0.001) in the medium-term compared to the control group. It was also found that gait (cadence; P = 0.004) and functional mobility (P &lt; 0.001) improved in the immediate term than in the KT group. Conclusions: KT combined with conventional physiotherapy can improve cadence and functional mobility in the immediate term, as well as gait and pelvic symmetry, functional mobility, gross motor function, balance, and participation in the medium term in children with unilateral CP. Further randomized controlled studies addressing large samples and long-term effects are warranted.

Dual tasking affects gait performance but not automaticity in functional gait disorders: A new diagnostic biomarker

IntroductionFunctional gait disorders (FGDs) are disabling symptoms of Functional Motor Disorders. Clinical observations show improvement with distraction suggesting an association with higher-level control mechanisms. Dual tasking is a valuable tool for exploring the interplay between gait and cognition. Our research question was: how do different dual task paradigms shape spatio-temporal gait parameters in FGDs?. MethodsIn all, 29 patients with FGDs (age 43.48 ± 15.42 years; female 75%) and 49 healthy controls (age 43.33 ± 15.41 years; female 62%) underwent spatio-temporal gait analysis during a single task and during performance on a motor, a cognitive, and a visual-fixation dual-task. The dual-task effect was a measure of interference of the concurrent task on gait speed, stride length (a measure of gait performance), and stride time variability (a measure of automaticity and steadiness). ResultsOverall lower gait speed, shorter stride length, and higher stride time variability were noted in FGDs compared to healthy controls (for all, p < 0.019). The was a significant effect of group and Task × Group interaction for the dual-task effect on gait speed (p = 0.023) and stride length (p = 0.01) but not for stride time variability. ConclusionPoorer gait performance and less automaticity and steadiness were noted in FGDs. However, dual tasking affected gait performance but, unlike different neurological diseases, not automaticity and steadiness compared to controls. Our findings shed light on higher-level gait control mechanisms in FGDs and suggest stride time variability could be a diagnostic and prognostic biomarker.

Methods for Spatiotemporal Analysis of Human Gait Based on Data from Depth Sensors.

Gait analysis may serve various purposes related to health care, such as the estimation of elderly people's risk of falling. This paper is devoted to gait analysis based on data from depth sensors which are suitable for use both at healthcare facilities and in monitoring systems dedicated to household environments. This paper is focused on the comparison of three methods for spatiotemporal gait analysis based on data from depth sensors, involving the analysis of the movement trajectories of the knees, feet, and centre of mass. The accuracy of the results obtained using those methods was assessed for different depth sensors' viewing angles and different types of subject clothing. Data were collected using a Kinect v2 device. Five people took part in the experiments. Data from a Zebris FDM platform were used as a reference. The obtained results indicate that the viewing angle and the subject's clothing affect the uncertainty of the estimates of spatiotemporal gait parameters, and that the method based on the trajectories of the feet yields the most information, while the method based on the trajectory of the centre of mass is the most robust.

A kinematic-geometric model based on ankles’ depth trajectory in frontal plane for gait analysis using a single RGB-D camera

The emergence of RGB-D cameras and the development of pose estimation algorithms offer opportunities in biomechanics. However, some challenges still remain when using them for gait analysis, including noise which leads to misidentification of gait events and inaccuracy.Therefore, we present a novel kinematic-geometric model for spatio-temporal gait analysis, based on ankles’ trajectory in the frontal plane and distance-to-camera data (depth). Our approach consists of three main steps: identification of the gait pattern and modeling via parameterized curves, development of a fitting algorithm, and computation of locomotive indices. The proposed fitting algorithm applies on both ankles’ depth data simultaneously, by minimizing through numerical optimization some geometric and biomechanical error functions.For validation, 15 subjects were asked to walk inside the walkway of the OptoGait, while the OptoGait and an RGB-D camera (Microsoft Azure Kinect) were both recording. Then, the spatio-temporal parameters of both feet were computed using the OptoGait and the proposed model. Validation results show that the proposed model yields good to excellent absolute statistical agreement (0.86 ≤ Rc ≤ 0.99).Our kinematic-geometric model offers several benefits: (1) It relies only on the ankles’ depth trajectory both for gait events extraction and spatio-temporal parameters’ calculation; (2) it is usable with any kind of RGB-D camera or even with 3D marker-based motion analysis systems in absence of toes’ and heels’ markers; and (3) it enables improving the results by denoising and smoothing the ankles’ depth trajectory. Hence, the proposed kinematic-geometric model facilitates the development of portable markerless systems for accurate gait analysis.

Ecological Validation of Machine Learning Models for Spatiotemporal Gait Analysis in Free-Living Environments Using Instrumented Insoles

Continuous gait monitoring may aid the early diagnosis of neurological and musculoskeletal conditions and help validate the effectiveness of new treatments. However, consumer-grade activity trackers can only capture summary gait metrics, whereas most of the research-grade devices capable of estimating fine-grained gait parameters are too cumbersome for extended-time use in real-life environments. Instrumented footwear may offer a promising alternative tool owing to their good accuracy and relatively small form factor, but their ability to detect stride-by-stride spatial gait parameters in free-living conditions has not been well explored to date. This work describes machine learning (ML) inference models for an insole system capable of accurately estimating stride time (ST), length (SL), and velocity (SV) in real-life environments. Functional validity was assessed through unstructured tests including straight-line walking, curve walking, and turns. Ecological validity was examined in free-living conditions. The ML models demonstrated better accuracy than conventional data processing methods (mean absolute errors in unstructured conditions were 3.55% for SL and 3.59% for SV). Real-life gait parameters estimated with the ML models showed stronger associations with a standardized walking test compared with the same parameters obtained with conventional methods. These results indicate proof-of-concept feasibility of using instrumented insoles and ML inference models for free-living spatiotemporal gait analysis.

E-Textile smart socks for gait analysis: a preliminary validation study

In the last years wearable technologies and smart fabrics are arousing a great deal of interest in the healthcare field. The possibility to directly interact with the body, along with the comfort of fabrics, represent great opportunities to develop interesting applications. Smart sensing socks, able to collect kinematic and/or foot pressure signals, are attractive solutions to perform gait analysis also outside clinical laboratories, e.g., in the home environment for remote continuous monitoring of patients. In this study we analyse the performance of Sensoria smart socks (Sensoria Health Inc. Seattle, WA, USA) in detecting the major spatio-temporal gait analysis metrics. We validate the results provided by the system in comparison with those of the IMU-based gait analysis system OPAL Mobility Lab by APDM (APDM Inc, Portland, OR, USA). Three textile pressure sensors are embedded in the Sensoria Sock to monitor plantar pressure, while the hardware unit is connected on the lateral part of the ankle to measure kinematic signals and transmit data to a smartphone. Twelve records were acquired on five healthy subjects (2 women). Each subject wore the sensing Sensoria smart socks and three OPAL Inertial Measurement Units (two on the feet and one in lumbar position), in order to perform simultaneous recording of the walking. The trial consisted of walking 10 metres, turning and returning to the starting point at preferred speed. The following resulting gait metrics were considered from the two systems and compared: Gait Cycle Time (GCT) [s], Stance Phase [%GCT], Cadence [steps/min]. Statistical comparison was performed by means of Bland-Altman test. Fig. 1 shows the results of the statistical analysis. Fig. 1 a presents the principal statistics of the considered metrics for the two systems. The table in Fig. 1 a also reports the numeric results of Bland- Altman test, expressed as the average bias (Sensoria minus OPAL) and its 95% Confidence Interval (CI) (Lower Bound LB – Upper Bound UB). Fig. 1 b, c and d respectively represent the Bland- Altman Plots for GCT, Stance Phase and Cadence. In this preliminary study we investigate the performances of the wearable Sensoria smart socks in evaluating the major temporal gait metrics. Results underline a general agreement in measuring GCT ( bias = − 0.00593 s ) and Cadence ( bias = − 0.0820 steps / min ). The confidence interval of bias includes the zero for both metrics, indicating that the differences randomly occur and are not systematic. The Bland-Altman plot for Stance Phase metric shows a significant difference between the measures provided by the two systems: Sensoria smart socks underestimate the foot stance phase duration with respect to the reference system OPAL Mobility Lab. In this case the average bias is − 7.75 % and its confidence interval does not include zero. The agreement in GCT values and the simultaneous disagreement of stance phase demonstrate discrepancies between the two systems in the detection of intermediate gait events (initial and terminal contact). In conclusion, smart socks performance in the detection of GCT and cadence are satisfactory, however improvements are needed in order to assess more specific gait metrics. In future studies, we aim to test the socks on a larger population and in the assessment of other temporal and spatial gait metrics.

Decreased cognitive function is associated with impaired spatiotemporal gait performance in community dwelling older adults with chronic musculoskeletal pain

ObjectiveOlder adults with chronic musculoskeletal pain often suffer from cognitive impairments and diminished lower extremity physical function. Prior work suggests that these impairments may be interrelated, however, the relationship between cognition and spatiotemporal gait performance in this population is understudied. Therefore, the purpose of this study was to examine the association between cognition and spatiotemporal gait performance and determine if cognition mediates the relationship between pain severity and spatiotemporal gait performance in older adults with chronic musculoskeletal pain without cognitive impairment. MethodsOlder adults with chronic musculoskeletal pain (n = 36) completed the Montreal Cognitive Assessment (MoCA) to assess global cognitive function. Spatiotemporal gait analysis was completed using an automated gait mat. Hierarchical regressions and mediation analyses were used to assess the relationship between chronic musculoskeletal pain, cognition, and spatiotemporal gait performance. ResultsMoCA scores were significantly associated with double support time, with lower MoCA scores relating with longer double support times (β = -0.686, p = 0.039). After accounting for cognition, pain severity was also associated with slower gait speed (β = -0.422, p = 0.019), and double support time (β = 0.454, p = 0.008). Cognition, however, did not mediate the relationship between pain severity and double support time. ConclusionsGlobal cognition and pain severity were associated with spatiotemporal gait performance in older adults with chronic pain. Pain severity, but not cognition, however, primarily explained spatiotemporal gait performance in our sample. Future work is needed to elucidate the role of cognition in spatiotemporal gait performance in older adults with chronic musculoskeletal pain.

Transductive Learning Models for Accurate Ambulatory Gait Analysis in Elderly Residents of Assisted Living Facilities.

Instrumented footwear represents a promising technology for spatiotemporal gait analysis in out-of-the-lab conditions. However, moderate accuracy impacts this technology's ability to capture subtle, but clinically meaningful, changes in gait patterns that may indicate adverse outcomes or underlying neurological conditions. This limitation hampers the use of instrumented footwear to aid functional assessments and clinical decision making. This paper introduces new transductive-learning inference models that substantially reduce measurement errors relative to conventional data processing techniques, without requiring subject-specific labelled data. The proposed models use subject-optimized input features and hyperparameters to adjust the spatiotemporal gait metrics (i.e., stride time, length, and velocity, swing time, and double support time) obtained with conventional techniques, resulting in computationally simpler models compared to end-to-end machine learning approaches. Model validity and reliability were evaluated against a gold-standard electronic walkway during a clinical gait performance test (6-minute walk test) administered to N = 95 senior residents of assisted living facilities with diverse levels of gait and balance impairments. Average reductions in absolute errors relative to conventional techniques were -42.0% and -33.5% for spatial and gait-phase parameters, respectively, indicating the potential of transductive learning models for improving the accuracy of instrumented footwear for ambulatory gait analysis.

Orientation-Invariant Spatio-Temporal Gait Analysis Using Foot-Worn Inertial Sensors.

Inertial sensors can potentially assist clinical decision making in gait-related disorders. Methods for objective spatio-temporal gait analysis usually assume the careful alignment of the sensors on the body, so that sensor data can be evaluated using the body coordinate system. Some studies infer sensor orientation by exploring the cyclic characteristics of walking. In addition to being unrealistic to assume that the sensor can be aligned perfectly with the body, the robustness of gait analysis with respect to differences in sensor orientation has not yet been investigated—potentially hindering use in clinical settings. To address this gap in the literature, we introduce an orientation-invariant gait analysis approach and propose a method to quantitatively assess robustness to changes in sensor orientation. We validate our results in a group of young adults, using an optical motion capture system as reference. Overall, good agreement between systems is achieved considering an extensive set of gait metrics. Gait speed is evaluated with a relative error of cm/s, but precision improves when turning strides are excluded from the analysis, resulting in a relative error of cm/s. We demonstrate the invariance of our approach by simulating rotations of the sensor on the foot.

Simple Video-Based Spatiotemporal Gait Analysis Is Not Better than Subjective Visual Assessment of Lameness in Dogs

Abstract Introduction Visual gait analysis is prone to subjectivity, but objective analysis systems are not widely available to clinicians. Simple video analysis using high-definition recordings might enable identification of temporal or spatial variations that could permit objective and repeatable assessments of lameness in general practice. Methods Cohorts of normal and mildly to moderately lame dogs were filmed using a standardized protocol. Using freely available software, measurements of stance, swing and stride time were obtained, along with measurements of pelvic, shoulder, and head height for each limb. Symmetry ratios were calculated, and distributions of normal and lame dogs compared using Mann–Whitney U test and Kruskal–Wallis test. Results Recordings from 35 normal dogs were assessed along with 30 dogs with grade 1 to 3/5 lameness. While no consistent significant differences in temporal characteristics could be found, head height asymmetry was significantly different between lame and normal dogs (p = 0.003), with pairwise comparison showing this difference was restricted to forelimb-lame dogs (p = 0.03). Conclusion While potentially useful for patient records, use of video recordings at walking speeds for simple spatiotemporal gait analysis does not appear to offer clinically significant advantages over visual gait analysis in a typical clinical population of lame dogs.

Biomechanical analysis of spatio-temporal gait factors in determining gender gait maturation in school children

Background: Spatio-temporal gait analysis includes identification of distance (Spatio) and time (temporal) related events during entire gait cycle for characterizing the gait.Research question: Although quantitative norms have been developed for various spatial and temporal characteristics of gait but less information is available of childhood, especially during early school years. There is a lack of adequate description of biomechanics in typically developing healthy children. Subsequently, the study was focused on both the genders of human population with ages ranging from 5-8 years, because this is the transition period in relation to the development of steady gait.Methods: The approach consisted of designing an experimental set up to gather kinematic data of running of school children at optimum gait speeds. A total of numbers of four hundred and two (402) school children were randomly selected for the study. The Spatio-temporal gait parameters were recorded during a complete gait cycle and were analyzed using “Silicon Coach Pro-7”motion analysis software. The statistical analysis was done using SPSSv17.0. Results: The outcome showed significant difference in Step Length (t = 2.92; p