Trajectory of Walking Function in Late-Stage Older Individuals Managed with a Regular Exercise Program: A 5-Year Longitudinal Tracking with an IoT Gait Analysis System Using Accelerometers

Purpose: This study focused on maintaining and improving the walking function of late-stage older individuals while longitudinally tracking the effects of regular exercise programs in a day-care service specialized for preventive care over 5 years, using detailed gait function measurements with an accelerometer-based system. Methods: Seventy individuals (17 male and 53 female) of a daycare service in Tokyo participated in a weekly exercise program, meeting 1 - 2 times. The average age of the participants at the start of the program was 81.4 years. Gait function, including gait speed, stride length, root mean square (RMS) of acceleration, gait cycle time and its standard deviation, and left-right difference in stance time, was evaluated every 6 months. Results: Gait speed and stride length improved considerably within six months of starting the exercise program, confirming an initial improvement in gait function. This suggests that regular exercise programs can maintain or improve gait function even age groups that predictably have a gradual decline in gait ability due to enhanced age. In the long term, many indicators tended to approach baseline values. However, the exercise program seemingly counteracts age-related changes in gait function and maintains a certain level of function. Conclusions: While a decline in gait ability with aging is inevitable, establishing appropriate exercise habits in late-stage older individuals may contribute to long-term maintenance of gait function.

The Immediate Analgesic Effect and Impact on Gait Function of Transcutaneous Electrical Nerve Stimulation in Late-Stage Elderly Individuals with Knee Pain: Examination of Gait Function Using an IoT-Based Gait Analysis Device

Purpose: This study verified the effects of transcutaneous electrical nerve stimulation (TENS), which can be worn during walking and exercise, in elderly individuals with late-stage knee pain who exercise regularly. Methods: Thirty-two late-stage elderly individuals were evaluated for knee pain during rest, walking, and program exercises, with and without TENS. Gait analysis was performed using an IoT-based gait analysis device to examine the effects of TENS-induced analgesia on gait. Results: TENS significantly reduced knee pain during rest, walking, and programmed exercises, with the greatest analgesic effect observed during walking. The greater the knee pain without TENS, the more significant the analgesic effect of TENS. A comparison of gait parameters revealed a significant difference only in the gait cycle time, with a trend towards faster walking with TENS;however, the effect was limited. Conclusion: TENS effectively relieves knee pain in late-stage elderly individuals and can be safely applied during exercise. Pain management using TENS provides important insights into the implementation of exercise therapy in this age group.

Assessment of hindlimb motor recovery affer severe thoracic spinal cord injury in rats: classification of CatWalk XT■ gait analysis parameters

Assessment of locomotion recovery in preclinical studies of experimental spinal cord injury remains challenging. We studied the CatWalk XT■gait analysis for evaluating hindlimb functional recovery in a widely used and clinically relevant thoracic contusion/compression spinal cord injury model in rats. Rats were randomly assigned to either a T9 spinal cord injury or sham laminectomy. Locomotion recovery was assessed using the Basso, Beattie, and Bresnahan open field rating scale and the CatWalk XT■gait analysis. To determine the potential bias from weight changes, corrected hindlimb(H) values(divided by the unaffected forelimb(F) values) were calculated. Six weeks after injury, cyst formation, astrogliosis, and the deposition of chondroitin sulfate glycosaminoglycans were assessed by immunohistochemistry staining. Compared with the baseline, a significant spontaneous recovery could be observed in the CatWalk XT■parameters max intensity, mean intensity, max intensity at%, and max contact mean intensity from 4 weeks after injury onwards. Of note, corrected values(H/F) of CatWalk XT■parameters showed a significantly less vulnerability to the weight changes than absolute values, specifically in static parameters. The corrected CatWalk XT■parameters were positively correlated with the Basso, Beattie, and Bresnahan rating scale scores, cyst formation, the immunointensity of astrogliosis and chondroitin sulfate glycosaminoglycan deposition. The CatWalk XT■gait analysis and especially its static parameters, therefore, seem to be highly useful in assessing spontaneous recovery of hindlimb function after severe thoracic spinal cord injury. Because many CatWalk XT■parameters of the hindlimbs seem to be affected by body weight changes, using their corrected values might be a valuable option to improve this dependency.

Gait analysis in swine,sheep,and goats after neurologic injury:a literature review

Medical research on neurologic ailments requires representative animal models to validate treatments before they are translated to human clinical trials.Rodents are the predominant animal model used in neurological research despite limited anatomic and physiologic similarities to humans.As a result,functional testing designed to assess locomotor recovery after neurologic impairment is well established in rodent models.Comparatively,large r,more clinically relevant models have not been as well studied.To achieve similar locomotor testing standardization in larger animals,the models must be accessible to a wide array of researchers.Non-human primates are the most relevant animal model fo r translational research,however ethical and financial barriers limit their accessibility.This review focuses on swine,sheep,and goats as large animal alternatives for transitional studies between rodents and non-human primates.The objective of this review is to compare motor testing and data collection methods used in swine,sheep,and goats to encourage testing standardization in these larger animal models.The PubMed database was analyzed by searching combinations of swine,sheep,and goats,neurologic injuries,and functional assessments.Findings were categorized by animal model,data collection method,and assessment design.Swine and sheep were used in the majority of the studies,while only two studies were found using goats.The functional assessments included open pen analysis,treadmill walking,and guided free walking.Data collection methods included subjective behavioral rating scales and objective tools such as pressure-sensitive mats and image-based analysis software.Overall,swine and sheep were well-suited for a variety of assessment designs,with treadmill walking and guided free walking offering the most consistency across multiple trials.Data collection methods varied,but image-based gait analysis software provided the most robust analysis.Future studies should be conducted to standardize functional testing methods after neurologic impairment in large animals.

Efficient Gait Analysis Using Deep Learning Techniques

Human Activity Recognition(HAR)has always been a difficult task to tackle.It is mainly used in security surveillance,human-computer interaction,and health care as an assistive or diagnostic technology in combination with other technologies such as the Internet of Things(IoT).Human Activity Recognition data can be recorded with the help of sensors,images,or smartphones.Recognizing daily routine-based human activities such as walking,standing,sitting,etc.,could be a difficult statistical task to classify into categories and hence 2-dimensional Convolutional Neural Network(2D CNN)MODEL,Long Short Term Memory(LSTM)Model,Bidirectional long short-term memory(Bi-LSTM)are used for the classification.It has been demonstrated that recognizing the daily routine-based on human activities can be extremely accurate,with almost all activities accurately getting recognized over 90%of the time.Furthermore,because all the examples are generated from only 20 s of data,these actions can be recognised fast.Apart from classification,the work extended to verify and investigate the need for wearable sensing devices in individually walking patients with Cerebral Palsy(CP)for the evaluation of chosen Spatio-temporal features based on 3D foot trajectory.Case-control research was conducted with 35 persons with CP ranging in weight from 25 to 65 kg.Optical Motion Capture(OMC)equipment was used as the referral method to assess the functionality and quality of the foot-worn device.The average accuracy±precision for stride length,cadence,and step length was 3.5±4.3,4.1±3.8,and 0.6±2.7 cm respectively.For cadence,stride length,swing,and step length,people with CP had considerably high inter-stride variables.Foot-worn sensing devices made it easier to examine Gait Spatio-temporal data even without a laboratory set up with high accuracy and precision about gait abnormalities in people who have CP during linear walking.

Sensor-Based Gait Analysis for Parkinson’s Disease Prediction

Parkinson’s disease is identified as one of the key neurodegenerative disorders occurring due to the damages present in the central nervous system.The cause of such brain damage seems to be fully explained in many research studies,but the understanding of its functionality remains to be impractical.Specifically,the development of a quantitative disease prediction model has evolved in recent decades.Moreover,accelerometer sensor-based gait analysis is accepted as an important tool for recognizing the walking behavior of the patients during the early prediction and diagnosis of Parkinson’s disease.This type of minimal infrastructure equipment helps in analyzing the Parkinson’s gait properties without affecting the common behavioral patterns during the clinical practices.Therefore,the Accelerometer Sensor-based Parkinson’s Disease Identi-fication System(ASPDIS)is introduced with a kernel-based support vector machine classifier model to make an early prediction of the disease.consequently,the proposed classifier can easily predict various severity levels of Parkinson’s disease from the sensor data.The performance of the proposed classifier is com-pared against the existing models such as random forest,decision tree,and k-near-est neighbor classifiers respectively.As per the experimental observation,the proposed classifier has more capability to differentiate Parkinson’s from non-Parkinson patients depending upon the severity levels.Also,it is found that the model has outperformed the existing classifiers concerning prediction time and accuracy respectively.

Gait analysis of children with spastic hemiplegic cerebral palsy

An experiment was carried out in the key laboratory for Technique Diagnosis and Function Assessment of Winter Sports of China to investigate the differences in gait characteristics between healthy children and children with spastic hemiplegic cerebral palsy. With permission of their parents, 200 healthy children aged 3 to 6 years in the kindergarten of Northeastern University were enrolled in this experiment. Twenty children aged 3 to 6 years with spastic hemiplegic cerebral palsy from Shengjing Hospital, China were also enrolled in this experiment. Standard data were collected by simultaneously recording gait information from two digital cameras. DVracker was used to analyze the standard data. The children with hemiplegic cerebra palsy had a longer gait cycle, slower walking speed, and longer support phase than did the healthy children. The support phase was longer than the swing phase in the children with hemiplegic cerebral palsy. There were significant differences in the angles of the hip, knee, and ankle joint between children with cerebral palsy and healthy children at the moment of touching the ground and buffering, and during pedal extension. Children with hemiplegic cerebral palsy had poor motor coordination during walking, which basically resulted in a short stride, high stride frequency to maintain speed, more obvious swing, and poor stability.

Spinal alignment evolution with age:A prospective gait analysis study

AIM To describe,using gait analysis,the development of spinal motion in the growing child.METHODS Thirty-six healthy children aged from 3 to 16 years old were included in this study for a gait analysis(9m-walk).Various kinematic parameters were recorded and analyzed such as thoracic angle(TA),lumbar angle(LA)and sagittal vertical axis(SVA).The kinetic parameters were the net reaction moments(N.m/kg)at the thoracolumbar and lumbosacral junctions.RESULTS TA and LA curves were not statistically correlated to the age(respectively,P=0.32 and P=0.41).SVA increased significantly with age(P<0.001).Moments in sagittal plane at the lumbosacral junction were statistically correlated to the age(P=0.003),underlining the fact that sagittal mechanical constraints at the lumbosacral junction increase with age.Moments in transversal plane at the thoracolumbar and lumbosacral junctions were statistically correlated to the age(P=0.0002and P=0.0006),revealing that transversal mechanical constraints decrease with age.CONCLUSION The kinetic analysis showed that during growth,a decrease of torsional constraint occurs while an increase of sagittal constraint is observed.These changes in spine biomechanics are related to the crucial role of the trunk for bipedalism acquisition,allowing stabilization despite lower limbs immaturity.With the acquisition of mature gait,the spine will mainly undergo constraints in the sagittal plane.

Effect of Motor Relearning Combined with t DCS on Motor Function of Lower Extremities and Gait in Patients with Cerebral Infarction and 3D Gait Analysis

[Objectives]To observe the effect of motor relearning combined with transcranial direct current stimulation on the motor function of lower extremities in patients with cerebral infarction,and to observe its effect on gait by 3D gait analysis.[Methods]60 patients with cerebral infarction who met the inclusion criteria were randomly divided into 3 groups according to the order of treatment(n=20).Group A received motor relearning treatment,group B received transcranial direct current stimulation treatment,group C received motor relearning combined with transcranial direct current stimulation,and the curative effect was observed after 5 courses of treatment.[Results]Before treatment,FMA,MBI,spatio-temporal parameters for 3D gait analysis(gait frequency,gait cycle,stride length,gait speed,stride length deviation,double support)and lower limb joint motion parameters(affected side stride length,maximum hip flexion,maximum hip extension,maximum knee flexion,maximum knee extension,stance phase,swing phase)were compared among the three groups.After treatment,the FMA and MBI of the three groups increased,and the spatio-temporal parameters for 3D gait analysis(gait frequency,gait cycle,gait speed,double support)and the lower limb joint motion parameters(affected side stride length,maximum hip flexion,maximum hip extension,maximum knee flexion,swing phase)were all improved,while the spatio-temporal parameters(stride length and stride length deviation)and the lower limb joint motion parameters(maximum knee extension and stance phase)decreased.Compared with those before treatment,there were significant differences among the three groups(P<0.05).Through the comparison between groups,it was found that the FMA,MBI,spatio-temporal parameters for 3D gait analysis(gait frequency,gait cycle,gait speed,double support)and lower limb joint motion parameters(affected side stride length,maximum hip flexion,maximum hip extension,maximum knee flexion,swing phase)in group C were significantly higher than those in group A and B,while the spatio-temporal parameters(stride length and stride length deviation)and lower limb joint motion parameters(maximum knee extension and stance phase)in group C were significantly lower than those in group A and group B,and the difference was statistically significant(P<0.05).[Conclusions]Motor relearning combined with transcranial direct current stimulation could increase MBI and FMA,improve gait spatio-temporal parameters and lower limb joint motion parameters,and correct abnormal gait in patients with cerebral infarction.

The Correlation Between Technologies and Rating Scales in Gait Analysis

Gait is a key function of human movement which plays an important role in motion analysis. Both in the clinical field and in rehabilitation, gait analysis is useful to evaluate the parameters that are modified following the administration of a protocol of adapted physical activity （APA）. Gait parameters could be measured using traditional rating scales, such as the Short Physical Performance Battery （SPPB） and technologies as a support to provide an assessment of gait quality. The aim of this study is to increase the objectivity of gait data obtained before and after a targeted APA program for a group of elderly people by integrating the traditional SPPB rating scale with the G Walk digital system. The former is an assessment tool to evaluate the functioning of lower extremity, in terms of chair stand, walk, and standing balance; whereas the latter can objectively evaluate the parameters of the gait. The sample was composed of I 1 adults aged between 67 and 94 years. The participants were chosen on the basis of a number of tests carried out to analyze their levels of autonomy, intellectual capacities and motor functioning. It has planned a six months APA protocol： before and after it, SPPB and G-Walk were administered. The results showed that space-time characteristics generally improve after APA intervention; therefore, the use of technology is a useful support for the evaluation scales.

Validation of a Marker Model for Gait Analysis with Wearable Exoskeletons

The aim of the present study was to develop and validate a new marker model for optoelectronic systems adapted to wearable devices, in order to have an analysis tool for kinematic gait evaluation of reproduced patterns by exoskeletons. The marker model has a total of 36 retro-reflective markers attached bilaterally to anatomical landmarks during the static measures （without exoskeleton） and 28 markers at the dynamics measures （with exoskeleton）. The main difference between others kinematic models and the described adapted model was the placement of the three markers in the back thigh and the other three in the back calf, what allowed removing the hip, thigh, knee, tibia and ankle markers. The proposed adapted marker model could be an effective tool to validate the joint movement and velocities of those wearable exoskeletons that at present have been developing.

Clinical gait analysis in older children with autism spectrum disorder

Individuals with autism spectrum disorder(ASD)often exhibit motor deficits that increase their risk of falls.There is a lack of understanding regarding gait biomechanics demonstrated by older children with ASD.The purpose of the study was to determine differences in gait patterns between older children with ASD and typically developing children.Eleven children with ASD and 11 age-and gender-matched typically developing children were recruited for the study.Participants walked on a force-instrumented treadmill at a constant speed(1.1 m/s-1.2 m/s)for five minutes(min).Participants performed maximal voluntary contractions to assess their knee muscular strength.Differences between individuals with ASD and matched control participants were examined through paired t-tests with a significance level of p0.05.Individuals with ASD demonstrated a smaller knee extensor torque compared to controls(p=0.002).Participants with ASD exhibited a shorter stride length(p=0.04),a greater cadence(p=0.03),and a higher variation in stride width(p=0.04)compared to control participants.The individuals with ASD experienced a greater braking ground reaction force(p=0.03)during loading response.The results indicate older children with ASD develop a unique gait pattern signified by a reduced stride length,increased cadence,and an increase of variation in stride width.This unique gait pattern may represent a movement strategy used by the individuals with ASD to compensate for the weakness associated with their knee extensor muscles.Individuals with ASD who demonstrate these unique gait deviations may face reduced postural stability and an increased risk of fall-related injuries.

Neural network-based estimation of lower limb joint kinematics:A minimally intrusive approach for gait analysis

The establishment of a quantitative gait analysis system holds paramount importance,particularly in the context of functional rehabilitation of the lower limbs.Clinicians emphasize the imperative for sensors to be portable,compact,integrated,and non-intrusive,crucial characteristics in the rehabilitation field to facilitate their use and ensure optimal integration into care protocols.This study investigates an innovative approach aimed at reducing the reliance on body-fixed sensors by harnessing their data within a neural network,thus concentrating on the joint kinematics of the lower limbs.The primary objective is to estimate the flexion-extension angles of the hip,knee,and ankle during walking,utilizing data collected by two sensors positioned on the subject's legs.Initially,the neural network undergoes training with calculated data(leg tilt angles and angular velocities)sourced from the OpenSim database,followed by further refinement with experimental data obtained from a subject walking on a treadmill,wherein leg tilt angles and angular velocities are measured.The significance of this research is underscored by the demonstrated capability,through conducted tests,of the implemented networks to efficiently fuse data from a minimal set of sensors.Consequently,the proposed approach emerges as both practical and minimally intrusive,facilitating a robust evaluation of gait kinematic parameters.

Gait Kinematic Analysis Facilitates Rapid Early Recovery Following Total Knee Arthroplasty

Objective: To explore gait kinematics analysis and evaluate the surgical efficacy of total knee arthroplasty (TKA), as well as its guiding significance for postoperative rehabilitation. Method: Fifty patients admitted to TKA treatment for knee osteoarthritis from December 2022 to July 2023 were included, which were divided into an intervention group (gait kinematics analysis group, n = 25) and a control group (conventional rehabilitation program group, n = 25). All patients underwent HSS score and KSS score before surgery (T0), 1 month after surgery (T1), 3 months after surgery (T2), and 6 months after surgery (T3). The intervention group underwent gait kinematics analysis at 1 month after surgery (T1) and 3 months after surgery (T2). Two groups measured the hip knee ankle angle (HKA), distal femoral lateral angle (LDFA), and proximal tibial medial angle (MPTA) on knee joint radiographs before and after surgery. Results: There was no significant difference in general information, preoperative imaging parameters, and functional scores between the two groups of patients. There was no significant difference in functional scores and postoperative prosthesis alignment between the two groups of patients in the first month after surgery. The intervention group showed a significant decrease in gait kinematic scores in the first month, with hip joint scores being particularly prominent (P 0.05). Conclusion: Gait kinematic analysis is helpful in evaluating the postoperative efficacy of TKA and can guide early and rapid recovery after TKA.

Study on the correlation between early three-dimensional gait analysis and clinical efficacy after robot-assisted total knee arthroplasty

Purpose:Robot-assisted technology is a forefront of surgical innovation that improves the accuracy of total knee arthroplasty (TKA).But whether the accuracy of surgery can improve the clinical efficacy still needs further research.The purpose of this study is to perform three-dimensional (3D) analysis in the early postoperative period of patients who received robot-assisted total knee arthroplasty (RATKA),and to study the trend of changes in gait parameters after RATKA and the correlation with the early clinical efficacy.Methods:Patients who received RATKA in the Center of Joint Surgery,the First Hospital Affiliated to Army Military Medical University from October 2020 to January 2021 were included.The imaging parameters,i.e.,hip-knee-ankle angle,lateral distal femoral angle,medial proximal tibial angle,posterior condylar angle were measured 3 months post-TKA.The 3D gait analysis and clinical efficacy by Western Ontario Mac Master University Index (WOMAC) score were performed pre-TKA,3 and 6 months post-TKA.The differences in spatiotemporal parameters of gait,kinetic parameters,and kinematic parameters of the operated limb and the contralateral limb were compared.The correlation between gait parameters and WOMAC scores was analyzed.Paired samplet-test and Wilcoxon rank-sum test were used to analyze the difference between groups,and Spearman correlation coefficient was used to analyze the correlation.Results:There were 31 patients included in this study,and the imaging indexes showed that all of them returned to normal post-TKA.The WOMAC score at 3 months post-TKA was significantly lower than that pre-TKA,and there was no significant difference between at 3 and 6 months.The 3D gait analysis results showed that the double support time of the operated limb reduced at 3 and 6 months (allp < 0.05),the maximum extension and maximum external rotation of the knee joint increased at stance phase,and the maximum flexion angle,the range of motion and the maximum external rotation increased at swing phase.Compared with the preoperative data,there were significant improvements (allp < 0.05).Compared with the contralateral knee joint,the maximum external rotation of the knee joint at swing phase was smaller than that of the contralateral side,and the maximum flexion and extension moment was greater than that of the contralateral knee.The maximum external rotation moment of the joint was greater than that of the contralateral knee joint (p < 0.05).There was a negative correlation between the single support time pre-TKA and the WOMAC score at 3 months (p = 0.017),and the single support time at 3 months was negatively correlated with the WOMAC score at 6 months (p = 0.043).The cadence at 6 months was negatively correlated with the WOMAC score at 6 months (p = 0.031).The maximum knee extension at stance phase at 6 months was negatively correlated with the WOMAC score at 6 month (p = 0.048).The maximum external rotation at stance phase at 6 months was negatively correlated with the WOMAC score at 6 months (p = 0.024).Conclusion:The 3D gait analysis of RATKA patients is more sensitive than WOMAC score in evaluating the clinical efficacy.Trend of changes in gait parameters shows that the knee joint support,flexion and extension function,range of motion,external rotation and varus deformity moment of the patient were significantly improved at 3 months after surgery,and continued to 6 months after surgery.Compared with the contralateral knee,the gait parameters of the operated limb still has significant gaps in functionality,such as the external rotation and flexion and extension.The single support time,cadence,knee extension,and knee external rotation of the operated limb have a greater correlation with the postoperative WOMAC score.Postoperative rehabilitation exercises should be emphasized,which is of great value for improving the early efficacy of RATKA.

Gait analysis combined with the expression of TGF-β1,TGF-β3 and CREB during Achilles tendon healing in rat

Purpose:To observe the changes of gait behavior and the expression of wound healing factors of transforming growth factor-β1(TGF-β1),TGF-β3 and cAMP response element binding protein-1(CREB-1)during the healing of Achilles tendon in a rat model,and to investigate whether gait analysis can be used to evaluate the tendon healing.Methods:Achilles tendon of 40 healthy male Sprague-Dawley rats were transected and sutured to establish the Achilles tendon injury(ATI)model.They were randomly divided into 4 groups based on the observational time point at 1,2,4 and 6 weeks after injury(n=10 for each group).Before modeling,9 rats were randomly selected for CatWalk gait analysis,which contained step cycle,single stance time and average speed.Data were recorded as the normal controls.After then,ATI models were established in the left hind limbs of the all 40 rats(ATI group),while the right hind limbs were only cut and sutured without injury of the Achilles tendon(sham operation group).At 1,2,4 and 6 weeks after injury,the gait behavior of the corresponding group of rats(n=9)as observed and recorded by CatWalk platform.After then,the rats were sacrificed and Achilles tendon of both limbs was harvested.The tendon healing was observed by gross anatomy and histological examination,and the protein and mRNA expression of TGF-β1,TGF-β3,CREB-1 were observed by immunohistochemistry and qPCR.The results of tendon gross grading were analyzed by Wilcoxon rank sum test,and other data were analyzed by one-way analysis of variance among multiple groups.Results:Compared with normal controls,all gait indexes(step cycle,single stance time and average speed)were greatly affected following ATI,which however improved with time.The step cycle was significantly lower at 1,2 and 4 weeks after ATI(compared with normal controls,allp<0.05),but almost returned to the normal level at 6 weeks((0.694±0.102)vs.(0.503±0.094)s,p>0.05).The single stance time of the ATI group was significantly shorter at 1 and 2 weeks after operation((0.078±0.010)s at 1 week,(0.078±0.020)s at 2 weeks,allp<0.001)and revealed no significant difference at 4 weeks(p=0.120).The average speed of ATI group at 1,2,4,6 weeks was significantly lower than that in the normal control group(allp<0.001).Conclusion:Gait behavior indexes are associated with Achilles tendon healing.The study gives an insight of TGF-β1,TGF-β3,CREB-1 changes in the coursing of Achilles tendon healing and these cytokines may be able to be used to regulate the Achilles tendon healing.

View-invariant Gait Authentication Based on Silhouette Contours Analysis and View Estimation

In this paper, we propose a novel view-invariant gait authentication method based on silhouette contours analysis and view estimation. The approach extracts Lucas-Kanade based gait flow image and head and shoulder mean shape (LKGFI-HSMS) of a human by using the Lucas-Kanade0s method and procrustes shape analysis (PSA). LKGFI-HSMS can preserve the dynamic and static features of a gait sequence. The view between a person and a camera is identified for selecting the target's gait feature to overcome view variations. The similarity scores of LKGFI and HSMS are calculated. The product rule combines the two similarity scores to further improve the discrimination power of extracted features. Experimental results demonstrate that the proposed approach is robust to view variations and has a high authentication rate. © 2014 Chinese Association of Automation.

Critical review of the use and scientific basis of forensic gait analysis

This review summarizes the scientific basis of forensic gait analysis and evaluates its use in the Netherlands,United Kingdom and Denmark,following recent critique on the admission of gait evidence in Canada.A useful forensic feature is(1)measurable,(2)consistent within and(3)different between individuals.Reviewing the academic literature,this article found that(1)forensic gait features can be quantified or observed from surveillance video,but research into accuracy,validity and reliability of these methods is needed;(2)gait is variable within individuals under differing and constant circumstances,with speed having major influence;(3)the discriminative strength of gait features needs more research,although clearly variation exists between individuals.Nevertheless,forensic gait analysis has contributed to several criminal trials in Europe in the past 15 years.The admission of gait evidence differs between courts.The methods are mainly observer-based:multiple gait analysts(independently)assess gait features on video footage of a perpetrator and suspect.Using gait feature databases,likelihood ratios of the hypotheses that the observed individuals have the same or another identity can be calculated.Automated gait recognition algorithms calculate a difference measure between video clips,which is compared with a threshold value derived from a video gait recognition database to indicate likelihood.However,only partly automated algorithms have been used in practice.We argue that the scientific basis of forensic gait analysis is limited.However,gait feature databases enable its use in court for supportive evidence with relatively low evidential value.The recommendations made in this review are(1)to expand knowledge on inter-and intra-subject gait variabilities,discriminative strength and interdependency of gait features,method accuracies,gait feature databases and likelihood ratio estimations;(2)to compare automated and observer-based gait recognition methods;to design(3)an international standard method with known validity,reliability and proficiency tests for analysts;(4)an international standard gait feature data collection method resulting in database(s);(5)(inter)national guidelines for the admission of gait evidence in court;and(6)to decrease the risk for cognitive and contextual bias in forensic gait analysis.This is expected to improve admission of gait evidence in court and judgment of its evidential value.Several ongoing research projects focus on parts of these recommendations.

Gait Analysis in Primary Total Knee Arthroplasty with and without Patellar Resurfacing:A Randomized Control Study

It is still controversial whether or not to resurface patella during primary total knee arthroplasty (TKA).One of the reasons may be insensitive measurement tools.We conducted a randomized controlled study to compare kinematic and kinetic parameters of resurfacing and nonresurfacing patella with the Vicon gait analysis system.The results show that patient post-operative gait of the two groups improved compared to pre-operative gait.Part of gait parameters,knee flexion at heel-strike,double limb support time and maximum adduction angle appeared to be statistically difference in 3 months,but 12 months later,the gait parameters of the two groups had no significant difference.Therefore,it seems that the final function of knee after TKA is not related whether or not to resurface patella.

Gait Image Classification Using Deep Learning Models for Medical Diagnosis

Gait refers to a person’s particular movements and stance while moving around.Although each person’s gait is unique and made up of a variety of tiny limb orientations and body positions,they all have common characteristics that help to define normalcy.Swiftly identifying such characteristics that are difficult to spot by the naked eye,can help in monitoring the elderly who require constant care and support.Analyzing silhouettes is the easiest way to assess and make any necessary adjustments for a smooth gait.It also becomes an important aspect of decision-making while analyzing and monitoring the progress of a patient during medical diagnosis.Gait images made publicly available by the Chinese Academy of Sciences(CASIA)Gait Database was used in this study.After evaluating using the CASIA B and C datasets,this paper proposes a Convolutional Neural Network(CNN)and a CNN Long Short-TermMemory Network(CNN-LSTM)model for classifying the gait silhouette images.Transfer learningmodels such as MobileNetV2,InceptionV3,Visual Geometry Group(VGG)networks such as VGG16 and VGG19,Residual Networks(ResNet)like the ResNet9 and ResNet50,were used to compare the efficacy of the proposed models.CNN proved to be the best by achieving the highest accuracy of 94.29%.This was followed by ResNet9 and CNN-LSTM,which arrived at 93.30%and 87.25%accuracy,respectively.