The phantom sensation is a feeling on an amputated limb. The features of the phantom sensation can be variable from person to person. It may accompany the person continuously, be present occasionally or disappear completely. This sensation may be accompanied by pain, in which case it is called phantom pain. Although the effects of phantom pain on many functions are widely known, the effects of phantom sensation on gait was not been adequately clarified yet (1). How does the presence of phantom sensation during gait affect gait characteristics? Three unilateral transtibial amputees and one healthy individual were included in the study. Three questions of the Prosthesis Evaluation questionnaire were asked to amputees to assess the frequency, severity, and degree of discomfort caused by the phantom sensation over the past four weeks. The amputees who had additional health issues and experienced phantom pain or other disturbing phantom sensations were excluded. The gait of individuals was evaluated with a sensor-based gait analysis system (RehaGait-Pro) at the neutral and %5 perturbated treadmill (ReaxRun-Pro). Gait parameters were analyzed and all variables were compared with Perry’s normal expected values (2). The change in gait characteristics of individuals to adapt to the perturbated ground was classified as decrease/increase by taking the gait characteristics on flat ground as a reference, and these changes were evaluated according to their similarity to a healthy individual. Individuals were as follows: Case 1 had phantom sensation during walking, Case 2; had phantom sensation only during resting, Case 3; had no phantom sensation, and Case 4 was a healthy individual. The individual who showed the most similarity with the healthy individual in adaptation to perturbation was the individual who felt phantom sensation during walking (Case 1). Case 1 followed a similar strategy for seven gait parameters. Case 2 gave similar adaptive responses with the healthy individual in 6 gait parameters. The individual without phantom sensation showed adaptive responses similar to the healthy individual in 3 different parameters (Table).Download : Download high-res image (164KB)Download : Download full-size image These results showed that phantom sensation may be a functional sensation and that maintaining the holistic body schema of an amputee may contribute to the nature of gait (1). It is recommended that further research be conducted in large groups. Acknowledgements: This research was funded by The Scientific and Technological Research Council of Turkey (Project number: S219S809).
{"title":"Effect of feeling the phantom sensation during gait on spatiotemporal gait characteristics in individuals with transtibial amputation","authors":"Nimet Sermenli Aydın, İlke Kurt, Halit Selçuk, Sinem Salar, Sezer Ulukaya, Hilal Keklicek","doi":"10.1016/j.gaitpost.2023.07.228","DOIUrl":"https://doi.org/10.1016/j.gaitpost.2023.07.228","url":null,"abstract":"The phantom sensation is a feeling on an amputated limb. The features of the phantom sensation can be variable from person to person. It may accompany the person continuously, be present occasionally or disappear completely. This sensation may be accompanied by pain, in which case it is called phantom pain. Although the effects of phantom pain on many functions are widely known, the effects of phantom sensation on gait was not been adequately clarified yet (1). How does the presence of phantom sensation during gait affect gait characteristics? Three unilateral transtibial amputees and one healthy individual were included in the study. Three questions of the Prosthesis Evaluation questionnaire were asked to amputees to assess the frequency, severity, and degree of discomfort caused by the phantom sensation over the past four weeks. The amputees who had additional health issues and experienced phantom pain or other disturbing phantom sensations were excluded. The gait of individuals was evaluated with a sensor-based gait analysis system (RehaGait-Pro) at the neutral and %5 perturbated treadmill (ReaxRun-Pro). Gait parameters were analyzed and all variables were compared with Perry’s normal expected values (2). The change in gait characteristics of individuals to adapt to the perturbated ground was classified as decrease/increase by taking the gait characteristics on flat ground as a reference, and these changes were evaluated according to their similarity to a healthy individual. Individuals were as follows: Case 1 had phantom sensation during walking, Case 2; had phantom sensation only during resting, Case 3; had no phantom sensation, and Case 4 was a healthy individual. The individual who showed the most similarity with the healthy individual in adaptation to perturbation was the individual who felt phantom sensation during walking (Case 1). Case 1 followed a similar strategy for seven gait parameters. Case 2 gave similar adaptive responses with the healthy individual in 6 gait parameters. The individual without phantom sensation showed adaptive responses similar to the healthy individual in 3 different parameters (Table).Download : Download high-res image (164KB)Download : Download full-size image These results showed that phantom sensation may be a functional sensation and that maintaining the holistic body schema of an amputee may contribute to the nature of gait (1). It is recommended that further research be conducted in large groups. Acknowledgements: This research was funded by The Scientific and Technological Research Council of Turkey (Project number: S219S809).","PeriodicalId":94018,"journal":{"name":"Gait & posture","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135298375","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-01DOI: 10.1016/j.gaitpost.2023.07.200
Salvador Pitarch-Corresa, Helios De Rosario - Martínez, Juan López - Pascual, Rosa Porcar - Seder, Ana Ruescas - Nicolau, Fermín Basso - Della Vedova
4D scanners (4DSC) are innovative photogrammetry-based 3D/4D capture and analysis systems for anthropometric static and dynamic measurements. Recent research studies have been carried out to demonstrate its validity for kinematic gait assessment [1] and to evaluate the effects of technical marker location on traditional kinematic analysis [2]. Compared to 3D systems, 4DSC allow to capture more detail of human motion, including precise volumes and shapes of body segments that can be used to make more accurate calculations [3]. 4DSC also provides a 3D dynamic avatar reconstruction to visual analysis in 360º vision and information of anthropometric measures in motion. Due to these unique features, 4DSC have set a new direction in motion analysis, especially related with pathological conditions of the nervous system [4]. Can “4D scans” provide significant information related to dynamic soft tissue behavior to improve clinical understanding in neurological disorders gait motion analysis? A case study was conducted with 16-year-old male participant diagnosed of cerebellum ataxia with hypoplasia associated to motor alteration, but able to walk without assistance. Parents’ written consent was obtained. Participant performed consecutive gait repetitions (3 for each limb) at self-selected speed at IBV Human Analysis Laboratory. Tests were recorded with Move4D scanner and Dinascan/IBV force plate. Kinematic and dynamic gait parameters were calculated from the data recorded using AMHPlus/IBV software. Additionally, changes in the calf shape during gait were calculated from the Move4D data using custom developed Python algorithms. Leg calf surface was determined as the posterior area of the mesh at each leg, between tibial tuberosity projection and midpoint of Achilles tendon. At each instant of the gait cycle, the positions of the vertices of those areas were rotated and translated keeping their relative distances, in order to match their positions in the reference posture as closely as possible. Deformation of the skin was measured as the field of 3D distances between the reference points and their displaced positions. That amount of deformation at each instant was quantified for both legs, as the sum of the eigenvectors of that field of deformations (in mm). 4DSC results allowed to objectify gait kinetic and kinematic alterations and a different pattern in soft tissue deformation between legs (see Figure), which were consistent with the clinical impression. Figure. Differences in calf surface deformation and reaction forces between limbs during single leg support. Representation of mesh extracted from Move4D data during gait on top.Download : Download high-res image (105KB)Download : Download full-size image Information extracted from Move4D allows to eliminate remaining limitations of traditional gait motion analysis systems. Recent studies propose methodologies to predict human muscle activity from skin surface behavior [5,6]. Single system solution for
{"title":"Innovative use of 4D scanner for gait analysis of neurological disorders: A case study","authors":"Salvador Pitarch-Corresa, Helios De Rosario - Martínez, Juan López - Pascual, Rosa Porcar - Seder, Ana Ruescas - Nicolau, Fermín Basso - Della Vedova","doi":"10.1016/j.gaitpost.2023.07.200","DOIUrl":"https://doi.org/10.1016/j.gaitpost.2023.07.200","url":null,"abstract":"4D scanners (4DSC) are innovative photogrammetry-based 3D/4D capture and analysis systems for anthropometric static and dynamic measurements. Recent research studies have been carried out to demonstrate its validity for kinematic gait assessment [1] and to evaluate the effects of technical marker location on traditional kinematic analysis [2]. Compared to 3D systems, 4DSC allow to capture more detail of human motion, including precise volumes and shapes of body segments that can be used to make more accurate calculations [3]. 4DSC also provides a 3D dynamic avatar reconstruction to visual analysis in 360º vision and information of anthropometric measures in motion. Due to these unique features, 4DSC have set a new direction in motion analysis, especially related with pathological conditions of the nervous system [4]. Can “4D scans” provide significant information related to dynamic soft tissue behavior to improve clinical understanding in neurological disorders gait motion analysis? A case study was conducted with 16-year-old male participant diagnosed of cerebellum ataxia with hypoplasia associated to motor alteration, but able to walk without assistance. Parents’ written consent was obtained. Participant performed consecutive gait repetitions (3 for each limb) at self-selected speed at IBV Human Analysis Laboratory. Tests were recorded with Move4D scanner and Dinascan/IBV force plate. Kinematic and dynamic gait parameters were calculated from the data recorded using AMHPlus/IBV software. Additionally, changes in the calf shape during gait were calculated from the Move4D data using custom developed Python algorithms. Leg calf surface was determined as the posterior area of the mesh at each leg, between tibial tuberosity projection and midpoint of Achilles tendon. At each instant of the gait cycle, the positions of the vertices of those areas were rotated and translated keeping their relative distances, in order to match their positions in the reference posture as closely as possible. Deformation of the skin was measured as the field of 3D distances between the reference points and their displaced positions. That amount of deformation at each instant was quantified for both legs, as the sum of the eigenvectors of that field of deformations (in mm). 4DSC results allowed to objectify gait kinetic and kinematic alterations and a different pattern in soft tissue deformation between legs (see Figure), which were consistent with the clinical impression. Figure. Differences in calf surface deformation and reaction forces between limbs during single leg support. Representation of mesh extracted from Move4D data during gait on top.Download : Download high-res image (105KB)Download : Download full-size image Information extracted from Move4D allows to eliminate remaining limitations of traditional gait motion analysis systems. Recent studies propose methodologies to predict human muscle activity from skin surface behavior [5,6]. Single system solution for ","PeriodicalId":94018,"journal":{"name":"Gait & posture","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135298377","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Predictive and functional calibration methods can be used to estimate joint centre and axis localisation in 3D motion analysis (1-6). The method of Harrington and the geometric sphere fit method are implemented in Human Body Model (HBM-II) as they are the most accurate predictive and functional calibration method respectively (1-6). The effect of calibration methods on kinematics is less researched although relevant for clinical interpretations. Does the Harrington predictive and the combined functional knee and hip calibration method in 3D gait analysis produce comparable 3D joint kinematics? Gait of 12 healthy subjects (11 F, mean(SD) age 26.4 (9.3)years, BMI 24.6 (2.8)kg/m2) was measured at Computer Assisted Rehabilitation ENvironment using HBM-II. Subjects started with a 6 minutes familiarisation period. Afterwards, a static model initialization was done (5 s standing in Tpose) using the predictive method of Harrington (1) followed by a measurement of three minutes walking at 1.1 m/s. Next, the system was reset and a combined functional knee (performing knee extension/flexion movements) and hip (performing starARc movement (6)) calibration was done using the geometric sphere fit method (2). A similar gait measurement was done. Data of 3D joint angles were extrapolated to strides (0-100%). For each subject, the difference in joint angle between the methods was calculated for each instant of the gait cycle. Mean differences were calculated and statistical parametric mapping (paired t-test) was used for group comparisons. Although the waveform patterns were comparable for the methods (Fig. 1A), significant differences in amplitude were observed for sagittal hip, knee and ankle angles and transverse hip angle (Fig. 1C), with maximum mean differences ranging from 3.6° to 7.4° (Fig. 1B). Mean differences in sagittal trunk and pelvis angles and frontal plane angles were smaller (range 0.0°–1.1°) and non-significant. The kinematic differences between methods varied among subjects (e.g. maximum knee flexion difference range: 1.9°-12.5°, Fig. 1D). Download : Download high-res image (457KB)Download : Download full-size image 3D gait analysis using the Harrington predictive or combined functional knee and hip calibration method results in different sagittal hip, knee, ankle angles and transverse hip angle. Differences are clinically relevant as they exceed 5°, corresponding to the measurement error for 3D gait kinematics (7). The difference of 1° in other joint angles indicates no critically interfere of the calibration method. The choice for a calibration method should be consistent in a lab and should be based on the context (4, 6). The functional method is more reliable as it is independent on marker placement, but is sensitive for measurement artefacts and quality of movements (6). This reduces repeatability and limits its use in patients having restricted range of motion. The predictive method is sensitive for marker placement and anthropometric mea
预测和功能校准方法可用于估计三维运动分析中的关节中心和轴定位(1-6)。Harrington方法和几何球拟合方法分别是最准确的预测校准方法和功能校准方法，因此在Human Body Model (HBM-II)中实现(1-6)。校准方法对运动学的影响虽然与临床解释相关，但研究较少。在三维步态分析中，哈林顿预测和联合功能膝关节和髋关节校准方法是否产生可比较的三维关节运动学?采用HBM-II在计算机辅助康复环境下测量12名健康受试者(11名F，平均(SD)年龄26.4(9.3)岁，BMI 24.6 (2.8)kg/m2)的步态。受试者开始有6分钟的熟悉期。然后，使用Harrington(1)的预测方法进行静态模型初始化(在Tpose中站立5 s)，然后测量以1.1 m/s的速度行走3分钟。接下来，对系统进行复位，并使用几何球体拟合方法(2)对膝关节(进行膝关节伸展/屈曲运动)和髋关节(进行starARc运动)进行联合功能校准。三维关节角度数据外推至步长(0-100%)。对于每个受试者，在步态周期的每个瞬间计算两种方法之间的关节角度差异。计算均数差异，采用统计参数映射(配对t检验)进行组间比较。尽管两种方法的波形模式具有可比性(图1A)，但在髋矢状角、膝关节角和踝关节角以及髋横角的振幅上观察到显著差异(图1C)，最大平均差异范围为3.6°至7.4°(图1B)。躯干和骨盆矢状角和额平面角的平均差异较小(范围为0.0°-1.1°)，无统计学意义。不同方法的运动学差异因受试者而异(例如，最大膝关节屈曲差异范围:1.9°-12.5°，图1D)。下载:下载全尺寸图像3D步态分析，使用哈林顿预测或结合功能的膝关节和髋关节校准方法，得到不同的髋矢状、膝关节、踝关节角度和髋横角。差异超过5°时具有临床相关性，对应于三维步态运动学的测量误差(7)。其他关节角度相差1°表明校准方法没有严重干扰。校准方法的选择应在实验室中保持一致，并应基于环境(4,6)。功能方法更可靠，因为它独立于标记物的放置，但对测量伪像和运动质量敏感(6)。这降低了可重复性，限制了其在运动范围有限的患者中的使用。预测方法对标记位置和人体测量很敏感(8)，因此需要经验丰富的操作人员。然而，这种方法对患者来说是实用可行的，因此在荷兰被广泛使用。
{"title":"The predictive and functional calibration method in 3D gait analysis using Human Body Model-II produce different 3D joint angles","authors":"Rachel Senden, Rik Marcellis, Reinhard Claeys, Kenneth Meijer, Marianne Witlox, Paul Willems","doi":"10.1016/j.gaitpost.2023.07.227","DOIUrl":"https://doi.org/10.1016/j.gaitpost.2023.07.227","url":null,"abstract":"Predictive and functional calibration methods can be used to estimate joint centre and axis localisation in 3D motion analysis (1-6). The method of Harrington and the geometric sphere fit method are implemented in Human Body Model (HBM-II) as they are the most accurate predictive and functional calibration method respectively (1-6). The effect of calibration methods on kinematics is less researched although relevant for clinical interpretations. Does the Harrington predictive and the combined functional knee and hip calibration method in 3D gait analysis produce comparable 3D joint kinematics? Gait of 12 healthy subjects (11 F, mean(SD) age 26.4 (9.3)years, BMI 24.6 (2.8)kg/m2) was measured at Computer Assisted Rehabilitation ENvironment using HBM-II. Subjects started with a 6 minutes familiarisation period. Afterwards, a static model initialization was done (5 s standing in Tpose) using the predictive method of Harrington (1) followed by a measurement of three minutes walking at 1.1 m/s. Next, the system was reset and a combined functional knee (performing knee extension/flexion movements) and hip (performing starARc movement (6)) calibration was done using the geometric sphere fit method (2). A similar gait measurement was done. Data of 3D joint angles were extrapolated to strides (0-100%). For each subject, the difference in joint angle between the methods was calculated for each instant of the gait cycle. Mean differences were calculated and statistical parametric mapping (paired t-test) was used for group comparisons. Although the waveform patterns were comparable for the methods (Fig. 1A), significant differences in amplitude were observed for sagittal hip, knee and ankle angles and transverse hip angle (Fig. 1C), with maximum mean differences ranging from 3.6° to 7.4° (Fig. 1B). Mean differences in sagittal trunk and pelvis angles and frontal plane angles were smaller (range 0.0°–1.1°) and non-significant. The kinematic differences between methods varied among subjects (e.g. maximum knee flexion difference range: 1.9°-12.5°, Fig. 1D). Download : Download high-res image (457KB)Download : Download full-size image 3D gait analysis using the Harrington predictive or combined functional knee and hip calibration method results in different sagittal hip, knee, ankle angles and transverse hip angle. Differences are clinically relevant as they exceed 5°, corresponding to the measurement error for 3D gait kinematics (7). The difference of 1° in other joint angles indicates no critically interfere of the calibration method. The choice for a calibration method should be consistent in a lab and should be based on the context (4, 6). The functional method is more reliable as it is independent on marker placement, but is sensitive for measurement artefacts and quality of movements (6). This reduces repeatability and limits its use in patients having restricted range of motion. The predictive method is sensitive for marker placement and anthropometric mea","PeriodicalId":94018,"journal":{"name":"Gait & posture","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135298528","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-01DOI: 10.1016/j.gaitpost.2023.07.153
Pieter Meyns, Kyra Theunissen, Guy Plasqui, Annelies Boonen, Annick Timmermans, Peter Feys, Kenneth Meijer
Fatigue is a major complaint in patients with multiple sclerosis (pwMS) [1]. Previous research identified walking fatigability in pwMS by assessing the change in distance walked between minute 6 and 1 of the 6-Minute Walk Test (6MWT) [2]. Further, pwMS show lower limb gait deficits [3], resulting in decreased gait stability compared to healthy controls [4]. Additionally, upper limb movements can be altered in pwMS due to direct MS lesions [5], which have an important role during gait [6]. Therefore, the aim was to assess to what extent change in walking speed in pwMS is associated by changes in gait stability and arm swing from minute 6 to 1 of the 6MWT. Participants were included if they had: MS, age between 18–65, disease severity score from 1 to 5.5 on Expanded Disability Status Scale, ability to walk without walking aids. Participants were excluded if they had: a relapse 3 months, lower limb fracture 12 months, or lower limb botulinum toxin 6 months prior to the study. Participants performed the 6MWT on the CAREN (Motek), equipped with the Human Body lower limb and trunk model, including extra markers for arm swing (acromion and ulnar styloid). Participants walked as fast as possible using self-paced mode. Two familiarization rounds of 3 min, incl. breaks, were provided. Step width and variability of spatiotemporal parameters (i.e. step width, -length & -time) were used to assess gait stability [7]. Arm swing length was calculated as the difference between maximum anterior and posterior hand position. Most affected side was taken into account and defined as the side with greatest motor impairment (i.e. spasticity and/or weakness). Difference scores between minute 6 and 1 of the 6MWT were used for analyses. First, one-tailed Pearson correlations between gait stability measures & arm swing, and walking speed during the 6MWT were tested. Then one-tailed partial correlations were assessed to determine whether gait stability measures influenced walking speed when taking arm swing into account. Finally, significant factors were used in generalized estimation equations (GEE) to determine the extent of their effect on walking speed and possible interactions. Preliminary results included data of 11 pwMS(Table1/T1). Walking speed was significantly related to step length variability, step time variability and arm swing(T1). Partial correlation of step length variability and step time variability remained significant when controlling for arm swing(T1). GEE determined interaction effects between step length variability, step time variability and arm swing on walking speed(T1).Download : Download high-res image (390KB)Download : Download full-size image Results indicate that both gait stability and arm swing are significantly associated to walking speed during 6MWT in pwMS. These outcomes have a separate effect on walking speed as well as an interaction effect. Future studies could investigate whether gait stability and arm swing might be underlying factor
{"title":"Do gait stability and arm swing affect walking speed during the 6-minute walk test in persons with Multiple Sclerosis?","authors":"Pieter Meyns, Kyra Theunissen, Guy Plasqui, Annelies Boonen, Annick Timmermans, Peter Feys, Kenneth Meijer","doi":"10.1016/j.gaitpost.2023.07.153","DOIUrl":"https://doi.org/10.1016/j.gaitpost.2023.07.153","url":null,"abstract":"Fatigue is a major complaint in patients with multiple sclerosis (pwMS) [1]. Previous research identified walking fatigability in pwMS by assessing the change in distance walked between minute 6 and 1 of the 6-Minute Walk Test (6MWT) [2]. Further, pwMS show lower limb gait deficits [3], resulting in decreased gait stability compared to healthy controls [4]. Additionally, upper limb movements can be altered in pwMS due to direct MS lesions [5], which have an important role during gait [6]. Therefore, the aim was to assess to what extent change in walking speed in pwMS is associated by changes in gait stability and arm swing from minute 6 to 1 of the 6MWT. Participants were included if they had: MS, age between 18–65, disease severity score from 1 to 5.5 on Expanded Disability Status Scale, ability to walk without walking aids. Participants were excluded if they had: a relapse 3 months, lower limb fracture 12 months, or lower limb botulinum toxin 6 months prior to the study. Participants performed the 6MWT on the CAREN (Motek), equipped with the Human Body lower limb and trunk model, including extra markers for arm swing (acromion and ulnar styloid). Participants walked as fast as possible using self-paced mode. Two familiarization rounds of 3 min, incl. breaks, were provided. Step width and variability of spatiotemporal parameters (i.e. step width, -length & -time) were used to assess gait stability [7]. Arm swing length was calculated as the difference between maximum anterior and posterior hand position. Most affected side was taken into account and defined as the side with greatest motor impairment (i.e. spasticity and/or weakness). Difference scores between minute 6 and 1 of the 6MWT were used for analyses. First, one-tailed Pearson correlations between gait stability measures & arm swing, and walking speed during the 6MWT were tested. Then one-tailed partial correlations were assessed to determine whether gait stability measures influenced walking speed when taking arm swing into account. Finally, significant factors were used in generalized estimation equations (GEE) to determine the extent of their effect on walking speed and possible interactions. Preliminary results included data of 11 pwMS(Table1/T1). Walking speed was significantly related to step length variability, step time variability and arm swing(T1). Partial correlation of step length variability and step time variability remained significant when controlling for arm swing(T1). GEE determined interaction effects between step length variability, step time variability and arm swing on walking speed(T1).Download : Download high-res image (390KB)Download : Download full-size image Results indicate that both gait stability and arm swing are significantly associated to walking speed during 6MWT in pwMS. These outcomes have a separate effect on walking speed as well as an interaction effect. Future studies could investigate whether gait stability and arm swing might be underlying factor","PeriodicalId":94018,"journal":{"name":"Gait & posture","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135298534","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Achondroplasia (ACH) is the most common skeletal dysplasia and characterized by shorter long bones relative to the torso. Concerning the upper body, frequent features are cranio-cervical compression, thoracolumbar kyphosis, lumbar lordosis and stenosis [1,2]. Secondary symptoms can be lower back pain, claudication, weakness and paresthesias. What is the sagittal spinopelvic alignment during gait in ACH and which characteristics affect the pelvic tilt? 34 paediatric and juvenile patients with ACH (age:10.5±4.2 years, height: 108±15 cm) were statistically compared to 27 age-matched typically developing controls (age: 10.8±4.4 years, height: 145±23 cm). All underwent a 3D gait analysis [Vicon Nexus, mod. PiG-Model] to capture upper and lower body kinematics. Thorax, pelvic and lumbar spine rotations were extracted. All subjects were clinically examined for anthropometrics, passive RoM and manual strength. The presence of symptoms was documented. Correlations between clinical parameters, anthropometrics and pelvic tilt were analyzed. 17 of 34 patients reported back pain, sensory deficits or sudden leg weakness. During gait, patients with ACH showed +11.1° more anterior pelvic tilt (P<0.001), -4.0° less anterior thorax tilt (P= 0.005) and - 15.9° more lumbar extension (P<0.001). In both cohorts, subjects who took longer steps, had more pelvic tilt (Fig. 1), yet the tilt was still significantly larger in ACH, irrespective of longer relative steps (P<0.01). In ACH, negative correlations with anterior pelvic tilt were found for popliteal angles (r= -0.40, P=0.018) and for limb length to body height ratio (r=-0.65, P<0.001). Passive hip flexion contracture (Thomas-Test) in ACH was not related to anterior pelvic tilt (r=-0.14, P=0.43). ACH patients with symptoms walked with similarly severe spinopelvic malignment than asymptomatic patients, yet at 11.2% reduced speed (P=0.025). Upon clinical exam, patients with more tilt showed less knee extensor and plantarflexor strength (r=-0.45 and -0.40, both P< 0.027). No such correlations were found in controls.Download : Download high-res image (123KB)Download : Download full-size image Pelvic tilt and hyperlordosis in ACH was pronounced and the rate of symptoms hinting to neurological deficits and spinal compression was 50%. The link of pelvic tilt and reduced knee and ankle extensor strength fits within this considerations. Although anterior pelvic tilt was not a sole compensation to increase step length, it seems to some degree be a consequence of disproportionally short leg length. Notably, after surgical femoral lengthening, sagittal lumbar lordosis has been reported to decrease [3]. Next to leg growth promoting therapeutics and drugs, interventions that increase hamstrings tone in ACH may potentially also be beneficial for the upper body.
{"title":"The alignment of the trunk and pelvis during walking in achondroplasia and factors increasing anterior pelvic tilt","authors":"Antonia Thamm, Sylvie Marx, Nader Sean, Matthias Hösl","doi":"10.1016/j.gaitpost.2023.07.245","DOIUrl":"https://doi.org/10.1016/j.gaitpost.2023.07.245","url":null,"abstract":"Achondroplasia (ACH) is the most common skeletal dysplasia and characterized by shorter long bones relative to the torso. Concerning the upper body, frequent features are cranio-cervical compression, thoracolumbar kyphosis, lumbar lordosis and stenosis [1,2]. Secondary symptoms can be lower back pain, claudication, weakness and paresthesias. What is the sagittal spinopelvic alignment during gait in ACH and which characteristics affect the pelvic tilt? 34 paediatric and juvenile patients with ACH (age:10.5±4.2 years, height: 108±15 cm) were statistically compared to 27 age-matched typically developing controls (age: 10.8±4.4 years, height: 145±23 cm). All underwent a 3D gait analysis [Vicon Nexus, mod. PiG-Model] to capture upper and lower body kinematics. Thorax, pelvic and lumbar spine rotations were extracted. All subjects were clinically examined for anthropometrics, passive RoM and manual strength. The presence of symptoms was documented. Correlations between clinical parameters, anthropometrics and pelvic tilt were analyzed. 17 of 34 patients reported back pain, sensory deficits or sudden leg weakness. During gait, patients with ACH showed +11.1° more anterior pelvic tilt (P<0.001), -4.0° less anterior thorax tilt (P= 0.005) and - 15.9° more lumbar extension (P<0.001). In both cohorts, subjects who took longer steps, had more pelvic tilt (Fig. 1), yet the tilt was still significantly larger in ACH, irrespective of longer relative steps (P<0.01). In ACH, negative correlations with anterior pelvic tilt were found for popliteal angles (r= -0.40, P=0.018) and for limb length to body height ratio (r=-0.65, P<0.001). Passive hip flexion contracture (Thomas-Test) in ACH was not related to anterior pelvic tilt (r=-0.14, P=0.43). ACH patients with symptoms walked with similarly severe spinopelvic malignment than asymptomatic patients, yet at 11.2% reduced speed (P=0.025). Upon clinical exam, patients with more tilt showed less knee extensor and plantarflexor strength (r=-0.45 and -0.40, both P< 0.027). No such correlations were found in controls.Download : Download high-res image (123KB)Download : Download full-size image Pelvic tilt and hyperlordosis in ACH was pronounced and the rate of symptoms hinting to neurological deficits and spinal compression was 50%. The link of pelvic tilt and reduced knee and ankle extensor strength fits within this considerations. Although anterior pelvic tilt was not a sole compensation to increase step length, it seems to some degree be a consequence of disproportionally short leg length. Notably, after surgical femoral lengthening, sagittal lumbar lordosis has been reported to decrease [3]. Next to leg growth promoting therapeutics and drugs, interventions that increase hamstrings tone in ACH may potentially also be beneficial for the upper body.","PeriodicalId":94018,"journal":{"name":"Gait & posture","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135298543","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-01DOI: 10.1016/j.gaitpost.2023.07.166
Lenka Murínová, Miroslav Janura, Tomáš Klein
Minimalist footwear represents a footwear-wearing concept that aims to allow a human to move more naturally compared to conventional shoes [1]. There are several assumptions about the benefits of wearing minimalist footwear on human health [1–3], however, studies dealing with walking in minimalist footwear in adults have mainly evaluated their immediate or short-term effects [4–6]. For a better understanding of their effect on human health longitudinal research is needed.This study investigates the effect of 6 months of wearing minimalist footwear on the biomechanical parameters of gait during barefoot walking. What is the effect of 6 months of minimalist footwear wearing on ground reaction force and spatiotemporal parameters of gait in healthy adults during barefoot walking? The research sample consisted of 50 healthy adults divided into experimental and control groups by randomization. Ground reaction force (GRF) and spatiotemporal characteristics (speed, cadence, step length, stance phase duration) of gait were collected at two measurements during barefoot overground walking at a self-selected speed over a walkway with two embedded force platforms Kistler (Kistler, Winterthur, Switzerland) synchronized with a kinematic system Vicon Vantage V5 (Vicon Motion System, London, United Kingdom). The intervention period between the two measurements lasted 6 months. During this period, the experimental group wore minimalist footwear in the recommended, progressively increasing volume between the measurements. The minimalist footwear chosen for intervention was footwear Chitra bare (Walk free, s.r.o., Prague, Czech Republic). Intervention and group effect was detected by repeated measures ANOVA. Slightly, but no significant increase in speed and cadence of the experimental group after the intervention period was found. In other observed spatiotemporal parameters and conditions, no significant differences were found. A significant increase (p = 0.042) in the first peak of mediolateral GRF for the left foot was found in the experimental group after the intervention. No other significant differences in the magnitude of GRF were found. No significant differences were found in peak achievement in all components of GRF relative to the % of the stance phase of gait. Walking in minimalist footwear approximates barefoot walking in selected biomechanical parameters more than walking in conventional shoes [5–8]. Following the results of these studies, we hypothesize that prolonged walking in minimalist footwear may result in changes in gait patterns that should be similar to barefoot walking. The gait of habitually unshod walkers is characterized, e.g., by decreased step length, increased cadence, or decreased magnitude of the first peak vertical GRF compared to habitually shod walkers [9]. These findings are not consistent with ours. One of the possible explanations may be that 6 months of minimalist footwear wearing is a short period to create or produce changes
{"title":"The effect of minimalist footwear wearing on biomechanical parameters of gait","authors":"Lenka Murínová, Miroslav Janura, Tomáš Klein","doi":"10.1016/j.gaitpost.2023.07.166","DOIUrl":"https://doi.org/10.1016/j.gaitpost.2023.07.166","url":null,"abstract":"Minimalist footwear represents a footwear-wearing concept that aims to allow a human to move more naturally compared to conventional shoes [1]. There are several assumptions about the benefits of wearing minimalist footwear on human health [1–3], however, studies dealing with walking in minimalist footwear in adults have mainly evaluated their immediate or short-term effects [4–6]. For a better understanding of their effect on human health longitudinal research is needed.This study investigates the effect of 6 months of wearing minimalist footwear on the biomechanical parameters of gait during barefoot walking. What is the effect of 6 months of minimalist footwear wearing on ground reaction force and spatiotemporal parameters of gait in healthy adults during barefoot walking? The research sample consisted of 50 healthy adults divided into experimental and control groups by randomization. Ground reaction force (GRF) and spatiotemporal characteristics (speed, cadence, step length, stance phase duration) of gait were collected at two measurements during barefoot overground walking at a self-selected speed over a walkway with two embedded force platforms Kistler (Kistler, Winterthur, Switzerland) synchronized with a kinematic system Vicon Vantage V5 (Vicon Motion System, London, United Kingdom). The intervention period between the two measurements lasted 6 months. During this period, the experimental group wore minimalist footwear in the recommended, progressively increasing volume between the measurements. The minimalist footwear chosen for intervention was footwear Chitra bare (Walk free, s.r.o., Prague, Czech Republic). Intervention and group effect was detected by repeated measures ANOVA. Slightly, but no significant increase in speed and cadence of the experimental group after the intervention period was found. In other observed spatiotemporal parameters and conditions, no significant differences were found. A significant increase (p = 0.042) in the first peak of mediolateral GRF for the left foot was found in the experimental group after the intervention. No other significant differences in the magnitude of GRF were found. No significant differences were found in peak achievement in all components of GRF relative to the % of the stance phase of gait. Walking in minimalist footwear approximates barefoot walking in selected biomechanical parameters more than walking in conventional shoes [5–8]. Following the results of these studies, we hypothesize that prolonged walking in minimalist footwear may result in changes in gait patterns that should be similar to barefoot walking. The gait of habitually unshod walkers is characterized, e.g., by decreased step length, increased cadence, or decreased magnitude of the first peak vertical GRF compared to habitually shod walkers [9]. These findings are not consistent with ours. One of the possible explanations may be that 6 months of minimalist footwear wearing is a short period to create or produce changes","PeriodicalId":94018,"journal":{"name":"Gait & posture","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135298545","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-01DOI: 10.1016/j.gaitpost.2023.07.154
Arne Defour, Daan De Vlieger, Robbe De Baets, Kristine Oostra, Dirk Cambier, Hanne Maebe, Koen Matthys, Pieter Meyns, Anke Van Bladel
Visual gait assessment is a cost-effective and more feasible way to evaluate post-stroke gait deviations in a clinical setting. Most observation scales focus on the lower limb during walking and therefore contain little information concerning the upper limb1,2. However, the upper limbs also contributes to various aspects of functional ambulation3. Therefore, an observation scale was developed to assess the arm swing during walking in persons after stroke. The aim of this study is to examine the inter- and intra-tester reliability and concurrent validity of the upper limb observation scale using two-dimensional (2D) videos of the persons after stroke during walking. Twenty-four persons after stroke (14 female, 10 male; age 54.29 ± 10.9 years, 5.50 ± 29.6 months post-stroke) underwent clinical tests and walked along a 10-meter walkway at self-selected speed. Walking was videotaped (frontal and sagittal view) to score the upper limb observation scale (Fig. 1) afterwards by three different researchers who were blinded from one another. One researcher scored this scale twice with an interval of two weeks. To assess the inter- and intra-tester reliability, intraclass correlation coefficients (ICC), spearman rank correlations (r) and Cronbach’s alpha’s were calculated. Additionally, 3D data, collected from four participants using the Gait Real-time Analysis Interactive Lab (GRAIL, Motek), was compared to the scores on the U.L.O.H.S.W. to validate the 2D observation of the upper limb during walking.Download : Download high-res image (265KB)Download : Download full-size image Inter-tester reliability for the different items varied with ICC’s between 0.254 and 0.885, correlation coefficients (r) between 0.410 and 1.000 (p<0.05, p<0.01) and Cronbach’s alpha between 0.504 and 0.958. For the intra-tester reliability, the ICC’s ranged from 0.594 to 0.957, the correlation coefficients (r) from 0.585 to 0.945 (p<0.01) and the Cronbach’s alpha from 0.738 to 0.978. Scoring the items concerning the more distal parts of the upper limb and the arm swing itself tended to be more reliable compared to the more proximal parts. Percentages of agreement, calculated between the scores on the observation scale and the 3D data to investigate concurrent validity, ranged from 29% (elbow flexion item) to 83% (shoulder abduction item). This is the first study to investigate the inter- and intra-tester reliability and the validity of an observational scale concerning the hemiplegic arm swing during gait. The tool is not yet sufficiently validated as an observation tool of the arm swing during walking in persons after stroke. Scoring the proximal movements of the upper limb appeared to be least reliable. Further research with a larger study population and a renewed version of this scale should provide more information concerning its clinical usability.
{"title":"Reliability and validity of a new observation scale to evaluate the upper limb during gait in persons after stroke","authors":"Arne Defour, Daan De Vlieger, Robbe De Baets, Kristine Oostra, Dirk Cambier, Hanne Maebe, Koen Matthys, Pieter Meyns, Anke Van Bladel","doi":"10.1016/j.gaitpost.2023.07.154","DOIUrl":"https://doi.org/10.1016/j.gaitpost.2023.07.154","url":null,"abstract":"Visual gait assessment is a cost-effective and more feasible way to evaluate post-stroke gait deviations in a clinical setting. Most observation scales focus on the lower limb during walking and therefore contain little information concerning the upper limb1,2. However, the upper limbs also contributes to various aspects of functional ambulation3. Therefore, an observation scale was developed to assess the arm swing during walking in persons after stroke. The aim of this study is to examine the inter- and intra-tester reliability and concurrent validity of the upper limb observation scale using two-dimensional (2D) videos of the persons after stroke during walking. Twenty-four persons after stroke (14 female, 10 male; age 54.29 ± 10.9 years, 5.50 ± 29.6 months post-stroke) underwent clinical tests and walked along a 10-meter walkway at self-selected speed. Walking was videotaped (frontal and sagittal view) to score the upper limb observation scale (Fig. 1) afterwards by three different researchers who were blinded from one another. One researcher scored this scale twice with an interval of two weeks. To assess the inter- and intra-tester reliability, intraclass correlation coefficients (ICC), spearman rank correlations (r) and Cronbach’s alpha’s were calculated. Additionally, 3D data, collected from four participants using the Gait Real-time Analysis Interactive Lab (GRAIL, Motek), was compared to the scores on the U.L.O.H.S.W. to validate the 2D observation of the upper limb during walking.Download : Download high-res image (265KB)Download : Download full-size image Inter-tester reliability for the different items varied with ICC’s between 0.254 and 0.885, correlation coefficients (r) between 0.410 and 1.000 (p<0.05, p<0.01) and Cronbach’s alpha between 0.504 and 0.958. For the intra-tester reliability, the ICC’s ranged from 0.594 to 0.957, the correlation coefficients (r) from 0.585 to 0.945 (p<0.01) and the Cronbach’s alpha from 0.738 to 0.978. Scoring the items concerning the more distal parts of the upper limb and the arm swing itself tended to be more reliable compared to the more proximal parts. Percentages of agreement, calculated between the scores on the observation scale and the 3D data to investigate concurrent validity, ranged from 29% (elbow flexion item) to 83% (shoulder abduction item). This is the first study to investigate the inter- and intra-tester reliability and the validity of an observational scale concerning the hemiplegic arm swing during gait. The tool is not yet sufficiently validated as an observation tool of the arm swing during walking in persons after stroke. Scoring the proximal movements of the upper limb appeared to be least reliable. Further research with a larger study population and a renewed version of this scale should provide more information concerning its clinical usability.","PeriodicalId":94018,"journal":{"name":"Gait & posture","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135298555","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Hallux valgus deformity (HV), which is among the most common foot deformities in adulthood, has been associated with impaired quality of life and function [1–4]. On the other hand, not only the presence of HV but also unilateral or bilateral involvement and whether it is painful or not may affect self-reported and performance-based measures [1,4]. Do foot function, physical performance, and quality of life differ between women with and without symptomatic bilateral HV? Forty-four women with bilateral HV (average HV angle for dominant foot=27.98±9.51° and for non-dominant foot=29.48±9.12°, average age=37.68±12.1 years, average BMI=25.30±5.17 kg/m2) and forty-three controls (average age=37.47±10.35 years, average BMI=24.87±4.52 kg/m2) were included. The HV angles of women presenting to orthopedic outpatient clinics with HV complaints were calculated from weight-bearing dorsoplantar radiographs. Women having HV angles equal to or greater than 15° in both feet were included in the HV group, also severity of HV was classified according to the HV angle of the dominant foot as mild (15-20°), moderate (21-39°), and severe (equal or greater than 40°). Volunteer women classified using the Manchester scale as normal were included in the control group. Foot pain and foot function were assessed using the Foot Function Index (FFI) and American Orthopaedic Foot and Ankle Society Hallux Metatarsophalangeal Interphalangeal Joints Scale (AOFAS Hallux MTF-IP). To assess physical performance, the time required to complete the following tasks was measured: (1) Walking 10 meter-walkway, (2) ascending ten stairs as fast as possible, and (3) descending ten stairs as fast as possible. Also, single-limb stance time with eyes-open was measured for both limbs. The Manchester-Oxford Foot Questionnaire was used to assess health-related quality of life. The Mann-Whitney U test was used to compare women with and without HV, also the Kruskal-Wallis test with Dunn’s post-hoc test was used to compare women with mild HV (n=16), moderate HV (n=19), and severe HV (n=9). Women with HV had poorer foot function, physical performance, and quality of life than those without HV according to the subscores and total scores of all assessment tools (p<0.05). Women with mild HV had less foot pain according to AOFAS Hallux MTF-IP and better foot function according to both AOFAS Hallux MTF-IP and FFI than those with severe HV (p<0.05). Furthermore, women with mild HV also had better foot function according to AOFAS Hallux MTF-IP than those with moderate HV (p<0.05). No difference was found between women with moderate and severe HV (p>0.05). Women with symptomatic bilateral HV had poorer self-reported foot function, self-reported quality of life, and physical performance. Furthermore, self-reported foot function differed between women with mild HV and moderate to severe HV, and the mild HV group had better foot function than the moderate HV and severe HV groups.
{"title":"Comparison of foot function, physical performance, and quality of life between women with and without symptomatic bilateral hallux valgus deformity","authors":"Busra Sacli, Sevtap Gunay Ucurum, Müge Kırmızı, Gokhan Cansabuncu","doi":"10.1016/j.gaitpost.2023.07.125","DOIUrl":"https://doi.org/10.1016/j.gaitpost.2023.07.125","url":null,"abstract":"Hallux valgus deformity (HV), which is among the most common foot deformities in adulthood, has been associated with impaired quality of life and function [1–4]. On the other hand, not only the presence of HV but also unilateral or bilateral involvement and whether it is painful or not may affect self-reported and performance-based measures [1,4]. Do foot function, physical performance, and quality of life differ between women with and without symptomatic bilateral HV? Forty-four women with bilateral HV (average HV angle for dominant foot=27.98±9.51° and for non-dominant foot=29.48±9.12°, average age=37.68±12.1 years, average BMI=25.30±5.17 kg/m2) and forty-three controls (average age=37.47±10.35 years, average BMI=24.87±4.52 kg/m2) were included. The HV angles of women presenting to orthopedic outpatient clinics with HV complaints were calculated from weight-bearing dorsoplantar radiographs. Women having HV angles equal to or greater than 15° in both feet were included in the HV group, also severity of HV was classified according to the HV angle of the dominant foot as mild (15-20°), moderate (21-39°), and severe (equal or greater than 40°). Volunteer women classified using the Manchester scale as normal were included in the control group. Foot pain and foot function were assessed using the Foot Function Index (FFI) and American Orthopaedic Foot and Ankle Society Hallux Metatarsophalangeal Interphalangeal Joints Scale (AOFAS Hallux MTF-IP). To assess physical performance, the time required to complete the following tasks was measured: (1) Walking 10 meter-walkway, (2) ascending ten stairs as fast as possible, and (3) descending ten stairs as fast as possible. Also, single-limb stance time with eyes-open was measured for both limbs. The Manchester-Oxford Foot Questionnaire was used to assess health-related quality of life. The Mann-Whitney U test was used to compare women with and without HV, also the Kruskal-Wallis test with Dunn’s post-hoc test was used to compare women with mild HV (n=16), moderate HV (n=19), and severe HV (n=9). Women with HV had poorer foot function, physical performance, and quality of life than those without HV according to the subscores and total scores of all assessment tools (p<0.05). Women with mild HV had less foot pain according to AOFAS Hallux MTF-IP and better foot function according to both AOFAS Hallux MTF-IP and FFI than those with severe HV (p<0.05). Furthermore, women with mild HV also had better foot function according to AOFAS Hallux MTF-IP than those with moderate HV (p<0.05). No difference was found between women with moderate and severe HV (p>0.05). Women with symptomatic bilateral HV had poorer self-reported foot function, self-reported quality of life, and physical performance. Furthermore, self-reported foot function differed between women with mild HV and moderate to severe HV, and the mild HV group had better foot function than the moderate HV and severe HV groups.","PeriodicalId":94018,"journal":{"name":"Gait & posture","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135298686","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-01DOI: 10.1016/j.gaitpost.2023.07.220
Wouter Schallig, Astrid Bieger, Melinda Witbreuk, Annemieke Buizer, Marjolein van der Krogt
Foot deformities are common in children with cerebral palsy (CP)1, but it is hard to predict how they develop. They are likely caused by a disturbed interplay of forces within the foot during gait, which can be quantified with multi-segment foot kinetics. Differences in foot joint kinetics have been shown between several foot deformity types and typically-developed feet2. These differences seem to indicate that mainly the misalignment of the foot causes further deterioration of the deformity rather than muscle actions2. Altered joint moments due to this malalignment are expected to lead to more deformation, which again results in more affected joint moments, entering a negative vicious circle. Assessing the relation between foot deformity severity and joint moments might provide support for this theory and it will allow to identify whether specific kinetic variables could serve as predictors. Is there an association between foot deformity severity and multi-segment foot kinetics in children with CP? 31 children (48 feet) with a spastic paresis (27 CP, 4 hereditary spastic paresis) were included, with a total of 6 equinovarus, 8 cavovarus, 16 planovalgus and 18 neutral feet. Additionally, 13 typically-developed (TD) feet with a normal foot posture were included. All children performed a gait analysis with the Amsterdam Foot Model3 marker set attached, while walking over a pressure plate on top of a force plate to be able to calculate the multi-segment foot kinetics4. The CP and TD children walked at 100% and 75% of comfortable speed respectively, to match their speed for further analyses. Peak foot joint moments were associated to a static measure (the foot posture index5) and a dynamic measure (the foot profile score6) of foot deformity severity, using Pearson correlations. Moderate significant correlations (r=0.60-0.65) were found between the static foot deformity score and the internal plantar flexion peak moment in the Lisfranc joint and the frontal plane peak moment in the ankle and Chopart joints (Fig. 1). For the dynamic foot deformity score, strong significant correlations (r>0.8) were present with peak plantar flexion moment for the equinovarus deformity in all joints. Low to moderate correlations (r=0.4-0.6) were found in the Chopart and Lisfranc joints for the cavovarus deformity in the sagittal and frontal plane and for the planovalgus deformity in the transverse plane. Fig. 1.Download : Download high-res image (154KB)Download : Download full-size image The significant associations between foot deformity severity and specific peak joint moments suggests that foot joint moments may play a role in the deterioration of foot deformities. Furthermore, specific joint moments per foot deformity group were identified which might have a predictive value for the progression of the deformation. However, longitudinal data is required to actually establish this predictive value. Identifying foot deformity predictors will allow for early interventio
{"title":"The predictive value of multi-segment foot kinetics in the development of foot deformities in cerebral palsy","authors":"Wouter Schallig, Astrid Bieger, Melinda Witbreuk, Annemieke Buizer, Marjolein van der Krogt","doi":"10.1016/j.gaitpost.2023.07.220","DOIUrl":"https://doi.org/10.1016/j.gaitpost.2023.07.220","url":null,"abstract":"Foot deformities are common in children with cerebral palsy (CP)1, but it is hard to predict how they develop. They are likely caused by a disturbed interplay of forces within the foot during gait, which can be quantified with multi-segment foot kinetics. Differences in foot joint kinetics have been shown between several foot deformity types and typically-developed feet2. These differences seem to indicate that mainly the misalignment of the foot causes further deterioration of the deformity rather than muscle actions2. Altered joint moments due to this malalignment are expected to lead to more deformation, which again results in more affected joint moments, entering a negative vicious circle. Assessing the relation between foot deformity severity and joint moments might provide support for this theory and it will allow to identify whether specific kinetic variables could serve as predictors. Is there an association between foot deformity severity and multi-segment foot kinetics in children with CP? 31 children (48 feet) with a spastic paresis (27 CP, 4 hereditary spastic paresis) were included, with a total of 6 equinovarus, 8 cavovarus, 16 planovalgus and 18 neutral feet. Additionally, 13 typically-developed (TD) feet with a normal foot posture were included. All children performed a gait analysis with the Amsterdam Foot Model3 marker set attached, while walking over a pressure plate on top of a force plate to be able to calculate the multi-segment foot kinetics4. The CP and TD children walked at 100% and 75% of comfortable speed respectively, to match their speed for further analyses. Peak foot joint moments were associated to a static measure (the foot posture index5) and a dynamic measure (the foot profile score6) of foot deformity severity, using Pearson correlations. Moderate significant correlations (r=0.60-0.65) were found between the static foot deformity score and the internal plantar flexion peak moment in the Lisfranc joint and the frontal plane peak moment in the ankle and Chopart joints (Fig. 1). For the dynamic foot deformity score, strong significant correlations (r>0.8) were present with peak plantar flexion moment for the equinovarus deformity in all joints. Low to moderate correlations (r=0.4-0.6) were found in the Chopart and Lisfranc joints for the cavovarus deformity in the sagittal and frontal plane and for the planovalgus deformity in the transverse plane. Fig. 1.Download : Download high-res image (154KB)Download : Download full-size image The significant associations between foot deformity severity and specific peak joint moments suggests that foot joint moments may play a role in the deterioration of foot deformities. Furthermore, specific joint moments per foot deformity group were identified which might have a predictive value for the progression of the deformation. However, longitudinal data is required to actually establish this predictive value. Identifying foot deformity predictors will allow for early interventio","PeriodicalId":94018,"journal":{"name":"Gait & posture","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135298696","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-01DOI: 10.1016/j.gaitpost.2023.07.232
Djordje Slijepcevic, Fabian Horst, Marvin Simak, Wolfgang Immanuel Schöllhorn, Matthias Zeppelzauer, Brian Horsak
Personalizing gait rehabilitation requires a comprehensive understanding of the unique gait characteristics of an individual patient, i.e., personal gait signature. Utilizing machine learning to classify individuals based on their gait can help to identify gait signatures [1]. This work exemplifies how an explainable artificial intelligence method can identify the most important input features that characterize the personal gait signature. How robust can gait signatures be identified with machine learning and how sensitive are these signatures with respect to the amount of training data per person? We utilized subsets of the AIST Gait Database 2019 [2], the GaitRec dataset [3], and the Gutenberg Gait Database [4] containing bilateral ground reaction forces (GRFs) during level walking at a self-selected speed. Eight GRF samples from each of 2,092 individuals (1,410/680 male/female, 809/1,283 health control/gait disorder, 1,355/737 shod/barefoot) were used for a gait-based person classification with a (linear) support vector machine (SVM). Two randomly selected samples from each individual served as test data. Gait signatures were identified using relevance scores obtained with layer-wise relevance propagation [5]. To assess the robustness of the identified gait signatures, we compared the relevance scores using Pearson’s correlation coefficient between step-wise reduced training data, from k=6 to k=1 training samples per individual. For the baseline setup (k=6), the SVM achieved a test classification accuracy of 99.1% with 36 out of 4184 test samples being misclassified. The results for the setups with reduced training samples are visualized in Fig. 1. Fig. 1: Overview of the experimental results.Download : Download high-res image (210KB)Download : Download full-size image A reduction of training samples per individual causes a decrease in classification accuracy (e.g., by 17.7% in the case of one training sample per individual). The results show that at least five training samples per individual are necessary to achieve a classification accuracy of approximately 99% for over 2,000 individuals. A similar effect is observed for gait signatures, which also show a slight degradation in robustness as the number of training samples decreases. In some cases, a model trained with less data per individual learns a different gait signature than a model trained with more data. In the test sample with the lowest correlation (see Fig. 1E), we observe a significant deviation in relevance for some input features. However, only 114 test samples (2.7%) are below a moderate correlation of r=0.4 [6], indicating that gait signatures are quite robust, even when using one training sample per individual. This is supported by a strong median correlation of r=0.71 [6] (and the highest correlation of r=0.96) between the gait signatures. As automatically identified gait signatures seem to be robust, this approach has the potential to serve as a basis for tailoring interven
{"title":"Towards personalized gait rehabilitation: How robustly can we identify personal gait signatures with machine learning?","authors":"Djordje Slijepcevic, Fabian Horst, Marvin Simak, Wolfgang Immanuel Schöllhorn, Matthias Zeppelzauer, Brian Horsak","doi":"10.1016/j.gaitpost.2023.07.232","DOIUrl":"https://doi.org/10.1016/j.gaitpost.2023.07.232","url":null,"abstract":"Personalizing gait rehabilitation requires a comprehensive understanding of the unique gait characteristics of an individual patient, i.e., personal gait signature. Utilizing machine learning to classify individuals based on their gait can help to identify gait signatures [1]. This work exemplifies how an explainable artificial intelligence method can identify the most important input features that characterize the personal gait signature. How robust can gait signatures be identified with machine learning and how sensitive are these signatures with respect to the amount of training data per person? We utilized subsets of the AIST Gait Database 2019 [2], the GaitRec dataset [3], and the Gutenberg Gait Database [4] containing bilateral ground reaction forces (GRFs) during level walking at a self-selected speed. Eight GRF samples from each of 2,092 individuals (1,410/680 male/female, 809/1,283 health control/gait disorder, 1,355/737 shod/barefoot) were used for a gait-based person classification with a (linear) support vector machine (SVM). Two randomly selected samples from each individual served as test data. Gait signatures were identified using relevance scores obtained with layer-wise relevance propagation [5]. To assess the robustness of the identified gait signatures, we compared the relevance scores using Pearson’s correlation coefficient between step-wise reduced training data, from k=6 to k=1 training samples per individual. For the baseline setup (k=6), the SVM achieved a test classification accuracy of 99.1% with 36 out of 4184 test samples being misclassified. The results for the setups with reduced training samples are visualized in Fig. 1. Fig. 1: Overview of the experimental results.Download : Download high-res image (210KB)Download : Download full-size image A reduction of training samples per individual causes a decrease in classification accuracy (e.g., by 17.7% in the case of one training sample per individual). The results show that at least five training samples per individual are necessary to achieve a classification accuracy of approximately 99% for over 2,000 individuals. A similar effect is observed for gait signatures, which also show a slight degradation in robustness as the number of training samples decreases. In some cases, a model trained with less data per individual learns a different gait signature than a model trained with more data. In the test sample with the lowest correlation (see Fig. 1E), we observe a significant deviation in relevance for some input features. However, only 114 test samples (2.7%) are below a moderate correlation of r=0.4 [6], indicating that gait signatures are quite robust, even when using one training sample per individual. This is supported by a strong median correlation of r=0.71 [6] (and the highest correlation of r=0.96) between the gait signatures. As automatically identified gait signatures seem to be robust, this approach has the potential to serve as a basis for tailoring interven","PeriodicalId":94018,"journal":{"name":"Gait & posture","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135298697","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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