There are a number of methods for determining the centre of the hip joint (HJ). The most common are regression equations or functional methods. In individual cases, however, we do not know how well the HJ centre is actually determined. Several papers present Harrington's regression formula as the best choice (Harrington et al., 2007; Kainz et al., 2015; Peters et al., 2012). If an image of the pelvis is available, the HJCD can be determined from it, and this can be used to optimise the determination of the joint centre in the regression formula. Does using the hip joint distance (x-ray) as an input change the joint parameters? A retrospective analysis of the gait laboratory database identified patients who had a calibrated radiograph and a 3D gait analysis. The calculated HJCD from the gait data was compared with that from the radiograph. In addition, the ASIS distance was calculated using the hip joint distance from the radiograph, and again the HJ position was determined using the newly obtained ASIS distance in the Harrington formula. The gait data were statistically compared using SPM analysis and the maximum distance between the two methods was determined over all curves. This was compared with the minimal detectable changes (MDC) (Wilken et al., 2012). Data from 349 patients (legs n=698, age: 4-22 years) with anterior knee malalignment without neuromuscular disease were analysed. HJCD correlations between radiographs and 3DGA values were 0.662 (p<0.001) using the Harrington method. The Bland-Altman plots for HJCD showed minimal differences using the Harrington regression formula. However, there were differences of up to 40 mm between the two methods of determining the HJCD. A comparison of the gait results with the two calculated equations shows significant differences (SPM). In most cases the differences between the two methods were negligible, but in some patients (legs) they were above the MDC value.Download : Download high-res image (85KB)Download : Download full-size image On average, the HJ distance from the radiograph and the gait analysis data were in good agreement, but not in every patient (up to 40 mm). The gait curves show significantly different results according to SPM analysis. In most cases the differences are below the MDC, but in individual patients there may well be clinically relevant differences in the results. Therefore, if pelvic imaging is available, we recommend using it to calculate the HJ centre.
有许多确定髋关节中心(HJ)的方法。最常见的是回归方程或泛函方法。然而，在个别情况下，我们不知道HJ中心实际上是如何确定的。有几篇论文将Harrington的回归公式作为最佳选择(Harrington et al.， 2007;Kainz et al.， 2015;Peters et al.， 2012)。如果骨盆的图像是可用的，HJCD可以从中确定，这可以用来优化回归公式中的关节中心的确定。使用髋关节距离(x线)作为输入是否会改变关节参数?步态实验室数据库的回顾性分析确定了有校准的x光片和3D步态分析的患者。将步态数据计算的HJCD与x线片的HJCD进行比较。此外，根据髋关节与x线片的距离计算出ASIS距离，再根据哈林顿公式中新获得的ASIS距离确定HJ位置。采用SPM分析对步态数据进行统计比较，并确定两种方法在所有曲线上的最大距离。这与最小可检测变化(MDC)进行了比较(Wilken et al.， 2012)。分析了349例无神经肌肉疾病的膝关节前位失调患者(腿数698，年龄4-22岁)的数据。采用Harrington方法，x线片与3DGA值的HJCD相关性为0.662 (p<0.001)。使用哈林顿回归公式，HJCD的Bland-Altman图显示最小的差异。然而，有差异高达40毫米之间的两种方法确定HJCD。步态结果与两种计算方程的比较显示出显著差异(SPM)。在大多数情况下，两种方法之间的差异可以忽略不计，但在一些患者(腿部)，它们高于MDC值。平均而言，与x线片的HJ距离和步态分析数据符合得很好，但并非每个患者(高达40 mm)。根据SPM分析，步态曲线有明显差异。在大多数情况下，差异低于MDC，但在个别患者中，结果可能存在临床相关差异。因此，如果盆腔成像可用，我们建议使用它来计算HJ中心。
{"title":"Does using the hip joint distance (x-ray) as an input change the kinematic, kinetic output and is this clinically relevant?","authors":"Andreas Kranzl, Groblschegg Leonore, Attwenger Bernhard, Durstberger Sebastian, Koppenwallner Laurin Xaver, Unglaube Fabian","doi":"10.1016/j.gaitpost.2023.07.130","DOIUrl":"https://doi.org/10.1016/j.gaitpost.2023.07.130","url":null,"abstract":"There are a number of methods for determining the centre of the hip joint (HJ). The most common are regression equations or functional methods. In individual cases, however, we do not know how well the HJ centre is actually determined. Several papers present Harrington's regression formula as the best choice (Harrington et al., 2007; Kainz et al., 2015; Peters et al., 2012). If an image of the pelvis is available, the HJCD can be determined from it, and this can be used to optimise the determination of the joint centre in the regression formula. Does using the hip joint distance (x-ray) as an input change the joint parameters? A retrospective analysis of the gait laboratory database identified patients who had a calibrated radiograph and a 3D gait analysis. The calculated HJCD from the gait data was compared with that from the radiograph. In addition, the ASIS distance was calculated using the hip joint distance from the radiograph, and again the HJ position was determined using the newly obtained ASIS distance in the Harrington formula. The gait data were statistically compared using SPM analysis and the maximum distance between the two methods was determined over all curves. This was compared with the minimal detectable changes (MDC) (Wilken et al., 2012). Data from 349 patients (legs n=698, age: 4-22 years) with anterior knee malalignment without neuromuscular disease were analysed. HJCD correlations between radiographs and 3DGA values were 0.662 (p<0.001) using the Harrington method. The Bland-Altman plots for HJCD showed minimal differences using the Harrington regression formula. However, there were differences of up to 40 mm between the two methods of determining the HJCD. A comparison of the gait results with the two calculated equations shows significant differences (SPM). In most cases the differences between the two methods were negligible, but in some patients (legs) they were above the MDC value.Download : Download high-res image (85KB)Download : Download full-size image On average, the HJ distance from the radiograph and the gait analysis data were in good agreement, but not in every patient (up to 40 mm). The gait curves show significantly different results according to SPM analysis. In most cases the differences are below the MDC, but in individual patients there may well be clinically relevant differences in the results. Therefore, if pelvic imaging is available, we recommend using it to calculate the HJ centre.","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":"135298028","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.2023.07.238
Heidi Stölzer-Hutsch, Dirk Schriefer, Katrin Trentzsch, Tjalf Ziemssen
Common symptoms in people with multiple sclerosis (pwMS) are walking limitations that can reduce the quality of life and lead to an increased risk of falling and fear of falling [1,2]. Instrumented gait analysis on a walkway with integrated pressure sensors can be used for assessment of both forward and backward walking. Walking backwards has been established as a more sensitive parameter to detect fallers, compared to walking forwards [3]. It is unknown whether fear of falling can be already detected by walking backwards. For possible interventions, it is important to identify patients with falls resp. fear of falling as early as possible. Is there an association between forward and backward walking and falls resp. fear of falling in pwMS? 705 pwMS (71.6% female, 82.1% with relapsing remitting MS) completed three test conditions on an eight-meter pressor sensor walking way (GAITRite® System) without shoes: (i) walking forwards at a self-selected normal speed, (ii) walking forwards at fast speed and (iii) walking backwards at the highest possible speed. In addition, fall history and fear of falling in the previous month were assessed. Velocity, step length and stance phase of gait cycle were determined in all test conditions. In walking backwards condition, time for 3-meter backward walking test (3MBWT) was additionally included in the analysis. Multiple logistic regressions adjusted for age, gender, body mass index (BMI) and Expanded Disability Status Scale (EDSS) were applied. Of 705 pwMS, 10.6% were fallers (n=75; age: 46.52 ±10.79; BMI: 26.05 ±5.66; EDSS median: 3.5), while 31.9% presented with fear of falling (n=225; age: 47.58 ±11,29; BMI: 25.73 ±5.01; EDSS median: 3.5). Step length during fast walking (odds ratio (OR) 0.982; CI 0.966-0.998) and velocity during walking backwards proved to be significant indicators of falls with an OR of 0.982 (CI 0.970-0.995). All parameters of walking backwards (velocity, step length, stance of cycle and 3MBWT) and stance of cycle in normal walking could be proven as an indicator of fear of falling (see Fig. 1). In addition to identifying patients at risk of falling [3], the results suggest that walking backwards also can identify pwMS presenting with fear of falling. Longitudinal analyses will be performed to validate the clinical utility of walking backwards. Fig. 1.Download : Download high-res image (111KB)Download : Download full-size image
{"title":"Backward and forward walking and its association with falls and fear of falling in people with multiple sclerosis","authors":"Heidi Stölzer-Hutsch, Dirk Schriefer, Katrin Trentzsch, Tjalf Ziemssen","doi":"10.1016/j.gaitpost.2023.07.238","DOIUrl":"https://doi.org/10.1016/j.gaitpost.2023.07.238","url":null,"abstract":"Common symptoms in people with multiple sclerosis (pwMS) are walking limitations that can reduce the quality of life and lead to an increased risk of falling and fear of falling [1,2]. Instrumented gait analysis on a walkway with integrated pressure sensors can be used for assessment of both forward and backward walking. Walking backwards has been established as a more sensitive parameter to detect fallers, compared to walking forwards [3]. It is unknown whether fear of falling can be already detected by walking backwards. For possible interventions, it is important to identify patients with falls resp. fear of falling as early as possible. Is there an association between forward and backward walking and falls resp. fear of falling in pwMS? 705 pwMS (71.6% female, 82.1% with relapsing remitting MS) completed three test conditions on an eight-meter pressor sensor walking way (GAITRite® System) without shoes: (i) walking forwards at a self-selected normal speed, (ii) walking forwards at fast speed and (iii) walking backwards at the highest possible speed. In addition, fall history and fear of falling in the previous month were assessed. Velocity, step length and stance phase of gait cycle were determined in all test conditions. In walking backwards condition, time for 3-meter backward walking test (3MBWT) was additionally included in the analysis. Multiple logistic regressions adjusted for age, gender, body mass index (BMI) and Expanded Disability Status Scale (EDSS) were applied. Of 705 pwMS, 10.6% were fallers (n=75; age: 46.52 ±10.79; BMI: 26.05 ±5.66; EDSS median: 3.5), while 31.9% presented with fear of falling (n=225; age: 47.58 ±11,29; BMI: 25.73 ±5.01; EDSS median: 3.5). Step length during fast walking (odds ratio (OR) 0.982; CI 0.966-0.998) and velocity during walking backwards proved to be significant indicators of falls with an OR of 0.982 (CI 0.970-0.995). All parameters of walking backwards (velocity, step length, stance of cycle and 3MBWT) and stance of cycle in normal walking could be proven as an indicator of fear of falling (see Fig. 1). In addition to identifying patients at risk of falling [3], the results suggest that walking backwards also can identify pwMS presenting with fear of falling. Longitudinal analyses will be performed to validate the clinical utility of walking backwards. Fig. 1.Download : Download high-res image (111KB)Download : Download full-size image","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":"135298038","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.2023.07.223
Halit Selçuk, Hilal Keklicek
Previous studies have shown that obesity impairs body biomechanics (1-3). However, no study has been found examining the gait of individuals who are not obese but have an above-normal BMI and were considered pre-obese. Does pre-obesity affect the symmetry of the angular values of the lower extremity during walking? Thirteen individuals with normal body mass index (BMI) (21.53±2.05 kg/m) and eight individuals with pre-obesity (28.52±2.21 kg/m) were recruited for the study. Participants walked at their self-paced speed for 4-5 minutes (4) on a motorized treadmill and the data of lower limb angles were collected with inertial measurement units (Xsens Technologies B.V.). Minimum, maximum, and average values of stance and swing phase of the participants for the whole series of the ankle, knee, and hip angles, as well as; the series at heel strike and foot release phase were recorded. Differences between right and left joints were calculated to examine gait symmetry. Symmetry in ankle angles was similar between groups (p>0.05). In the pre-obese group; minimum(p=0.011) and maximum (p=0.007) knee angles were more asymmetrical in the stance phase than in the normal-weight group. Also, the minimum knee angle in the swing phase was more asymmetrical (p=0.043) in the pre-obese group. In addition, it was determined that the pre-obese group exhibited more asymmetrical knee angles at heel strike (p=0.032) and foot release (p=0.017). The maximum hip angle of the pre-obese group was more asymmetrical in the stance phase (p=0.003) and swing phase (p= 0.006). Also, in the heel strike, the hip angle (p=0.009) was found to be more asymmetrical than the normal-weight group. No difference was observed between the groups for all other measurements (p>0.05). The results of the study showed that individuals with pre-obesity level BMI exhibited a more asymmetrical gait pattern in the proximal joints during walking. It was observed that the increase in BMI negatively affected gait even if below the level of obesity.
{"title":"Individuals with pre-obesity exhibit a more asymmetrical gait pattern","authors":"Halit Selçuk, Hilal Keklicek","doi":"10.1016/j.gaitpost.2023.07.223","DOIUrl":"https://doi.org/10.1016/j.gaitpost.2023.07.223","url":null,"abstract":"Previous studies have shown that obesity impairs body biomechanics (1-3). However, no study has been found examining the gait of individuals who are not obese but have an above-normal BMI and were considered pre-obese. Does pre-obesity affect the symmetry of the angular values of the lower extremity during walking? Thirteen individuals with normal body mass index (BMI) (21.53±2.05 kg/m) and eight individuals with pre-obesity (28.52±2.21 kg/m) were recruited for the study. Participants walked at their self-paced speed for 4-5 minutes (4) on a motorized treadmill and the data of lower limb angles were collected with inertial measurement units (Xsens Technologies B.V.). Minimum, maximum, and average values of stance and swing phase of the participants for the whole series of the ankle, knee, and hip angles, as well as; the series at heel strike and foot release phase were recorded. Differences between right and left joints were calculated to examine gait symmetry. Symmetry in ankle angles was similar between groups (p>0.05). In the pre-obese group; minimum(p=0.011) and maximum (p=0.007) knee angles were more asymmetrical in the stance phase than in the normal-weight group. Also, the minimum knee angle in the swing phase was more asymmetrical (p=0.043) in the pre-obese group. In addition, it was determined that the pre-obese group exhibited more asymmetrical knee angles at heel strike (p=0.032) and foot release (p=0.017). The maximum hip angle of the pre-obese group was more asymmetrical in the stance phase (p=0.003) and swing phase (p= 0.006). Also, in the heel strike, the hip angle (p=0.009) was found to be more asymmetrical than the normal-weight group. No difference was observed between the groups for all other measurements (p>0.05). The results of the study showed that individuals with pre-obesity level BMI exhibited a more asymmetrical gait pattern in the proximal joints during walking. It was observed that the increase in BMI negatively affected gait even if below the level of obesity.","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":"135298042","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.2023.07.197
Fraser Philp, Erik Meilak, Tracey Willis, Naomi Winn, Anand Pandyan
Facioscapulohumeral dystrophy (FSHD) can affect upper-limb function through muscle degeneration, fatty infiltration and oedema. Muscle echogenicity, measured using ultrasound, could be used as a biomarker for muscular changes and disease progression [1–3]. Histogram-matching may be instrumental in overcoming existing shortcomings that prevent us from using such images to extract clinically useful information [4,5]. Can histogram-matching of muscle ultrasound images be used to extract clinically relevant measures to quantify the muscle morphological changes in people with FSHD (pwFSHD)? Participants attended a single motion analysis session for upper-limb 2D-ultrasound imaging and 3D-movement analysis. Stratified sampling by arm function was used for pwFSHD. Controls were age and sex matched. Middle trapezius measurement was taken at the midpoint of a line between C7 and ACJ. Six total measurements were taken (3-longitudinal and 3-transverse views) using an Esoate MyLab-Gamma device and linear probe (3-13 MHz). Muscle thickness measurements were carried using ImageJ 1.53t. Histogram-matching was carried out as described by Bottenus et al. [4]. All images were matched to a single reference image from a control group participant. Manual segmentation of the subcutaneous fat layer was carried out and used as the region-of-interest for histogram-matching across all images. Using full histogram-matching, the monotonic transformation was applied across the entire image. The trapezius muscle was segmented to determine mean grayscale values (echogenicity). The student t-test was used for evaluating between group differences and the relationship between echogenicity values and muscle thickness was investigated. Data was collected for 14 participants (7 pwFSHD (2 F:5 M) and 7 sex- and age-matched controls (2 F:5 M). PwFSHD had mean (SD) age, height and weight values of 41.9-years (17.1), 176 cm (8.8) and 90.6 kg (24.8) respectively. The control group had age, height and weight values of 41.4-years (15.5), 176.4 cm (5.7) and 77.1 kg (11.2) respectively. Group echogenicity values are presented in Fig. 1. Download : Download high-res image (106KB)Download : Download full-size image Mean (SD) echogenicity values for pwFSHD were higher than the control group (96.5 (30.3) vs 32.2 (11.2) respectively) with statistically significant differences (p<0.001). Mean (SD) trapezius muscle thickness was higher in the control group 1.48 cm (0.27) vs 0.74 cm (0.45) respectively. Mean echogenicity scores accounted for 82% of the variance in mean muscle thickness values (R2=0.824). PwFSHD demonstrated higher echogenicity values and smaller muscle thicknesses indicative of degenerative muscle structure changes associated with the disease. Preliminary results suggest that post capture processing of ultrasound images using histogram matching can provide quantifiable differences in people with and without FSHD. This could facilitate clinically feasible bedside methods for assessing
{"title":"Quantifying morphological changes in middle trapezius with ultrasound scanning and a novel histogram matching algorithm","authors":"Fraser Philp, Erik Meilak, Tracey Willis, Naomi Winn, Anand Pandyan","doi":"10.1016/j.gaitpost.2023.07.197","DOIUrl":"https://doi.org/10.1016/j.gaitpost.2023.07.197","url":null,"abstract":"Facioscapulohumeral dystrophy (FSHD) can affect upper-limb function through muscle degeneration, fatty infiltration and oedema. Muscle echogenicity, measured using ultrasound, could be used as a biomarker for muscular changes and disease progression [1–3]. Histogram-matching may be instrumental in overcoming existing shortcomings that prevent us from using such images to extract clinically useful information [4,5]. Can histogram-matching of muscle ultrasound images be used to extract clinically relevant measures to quantify the muscle morphological changes in people with FSHD (pwFSHD)? Participants attended a single motion analysis session for upper-limb 2D-ultrasound imaging and 3D-movement analysis. Stratified sampling by arm function was used for pwFSHD. Controls were age and sex matched. Middle trapezius measurement was taken at the midpoint of a line between C7 and ACJ. Six total measurements were taken (3-longitudinal and 3-transverse views) using an Esoate MyLab-Gamma device and linear probe (3-13 MHz). Muscle thickness measurements were carried using ImageJ 1.53t. Histogram-matching was carried out as described by Bottenus et al. [4]. All images were matched to a single reference image from a control group participant. Manual segmentation of the subcutaneous fat layer was carried out and used as the region-of-interest for histogram-matching across all images. Using full histogram-matching, the monotonic transformation was applied across the entire image. The trapezius muscle was segmented to determine mean grayscale values (echogenicity). The student t-test was used for evaluating between group differences and the relationship between echogenicity values and muscle thickness was investigated. Data was collected for 14 participants (7 pwFSHD (2 F:5 M) and 7 sex- and age-matched controls (2 F:5 M). PwFSHD had mean (SD) age, height and weight values of 41.9-years (17.1), 176 cm (8.8) and 90.6 kg (24.8) respectively. The control group had age, height and weight values of 41.4-years (15.5), 176.4 cm (5.7) and 77.1 kg (11.2) respectively. Group echogenicity values are presented in Fig. 1. Download : Download high-res image (106KB)Download : Download full-size image Mean (SD) echogenicity values for pwFSHD were higher than the control group (96.5 (30.3) vs 32.2 (11.2) respectively) with statistically significant differences (p<0.001). Mean (SD) trapezius muscle thickness was higher in the control group 1.48 cm (0.27) vs 0.74 cm (0.45) respectively. Mean echogenicity scores accounted for 82% of the variance in mean muscle thickness values (R2=0.824). PwFSHD demonstrated higher echogenicity values and smaller muscle thicknesses indicative of degenerative muscle structure changes associated with the disease. Preliminary results suggest that post capture processing of ultrasound images using histogram matching can provide quantifiable differences in people with and without FSHD. This could facilitate clinically feasible bedside methods for assessing","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":"135298058","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.2023.07.202
Barbara Postolka, Bryce A. Killen, Hannelore Boey, Jos Vander Sloten, Ilse Jonkers
Increased joint contact stress can lead to cartilage degeneration and thus the development of osteoarthritis. While articular knee joint loading is well studied [1], less is known about other joints despite them being at risk of the disease as well. In particular, structural deformities of the foot-ankle complex such as flat feet are known to increase the risk for developing osteoarthritis at the hind- and midfoot joints [2]. The aim of this project was to combine state of the art in vivo kinematics with dynamic musculoskeletal simulations using an extended foot-ankle model including contact modelling to estimate ankle articular joint loading in healthy subjects during different gait activities. 6 healthy subjects (4 female, 2 male; 23.8±3.0 years; BMI 23.2±2.4 kg/m²) with no history of foot-ankle injuries participated in this study. Whole body kinematics were measured for each subject during three gait cycles of walking and running using a full body and extended foot skin marker system [3]. Cartilage contact between the tibia and talus were added to a foot-ankle model [4] to allow estimation of articular joint mechanics using an elastic foundation model based on cartilage stiffness and mesh penetration [1]. Generic models were scaled for each individual and kinematics calculated for every trial. Based on subject-specific kinematics, articular joint mechanics were estimated using the OpenSim joint and articular mechanics (JAM) tool [1]. To investigate articular joint loading, contact area as well as mean and peak pressure at the ankle joint were analysed during the stance phase. Mean and peak cartilage contact pressure were comparable at heel strike and toe off, but substantially differed throughout the stance phases of walking and running (Fig. 1A). During walking, cartilage contact pressure showed a double peak with the higher peak around contralateral heel strike (peak pressure: 5.96±1.66 MPa) whereas during running cartilage contact pressure showed a single peak during mid-stance (peak pressure: 9.61±2.41 MPa) (Fig. 1A&B). Although similar cartilage contact locations were found for walking and running, contact area was considerably larger during running (1.39±0.15 cm²) then walking (0.96±0.19 cm²) (Fig. 1B).Download : Download high-res image (119KB)Download : Download full-size image This study showed a first analysis of ankle mechanics during multiple gait cycles of walking and running. Using a detailed musculoskeletal foot-ankle model combined with recently developed methods to estimate cartilage contact mechanics, this study allowed novel insights on the location and magnitude of articular joint loading. While this study provided important findings on the ankle joint, further developments are needed to also estimate cartilage contact mechanics at the subtalar joint. In addition, analysis of pathological cohorts such as subjects with chronic ankle instability or flat feet, will help to understand changes in articular mechanics and how they
{"title":"Articular ankle joint loading during dynamic activities","authors":"Barbara Postolka, Bryce A. Killen, Hannelore Boey, Jos Vander Sloten, Ilse Jonkers","doi":"10.1016/j.gaitpost.2023.07.202","DOIUrl":"https://doi.org/10.1016/j.gaitpost.2023.07.202","url":null,"abstract":"Increased joint contact stress can lead to cartilage degeneration and thus the development of osteoarthritis. While articular knee joint loading is well studied [1], less is known about other joints despite them being at risk of the disease as well. In particular, structural deformities of the foot-ankle complex such as flat feet are known to increase the risk for developing osteoarthritis at the hind- and midfoot joints [2]. The aim of this project was to combine state of the art in vivo kinematics with dynamic musculoskeletal simulations using an extended foot-ankle model including contact modelling to estimate ankle articular joint loading in healthy subjects during different gait activities. 6 healthy subjects (4 female, 2 male; 23.8±3.0 years; BMI 23.2±2.4 kg/m²) with no history of foot-ankle injuries participated in this study. Whole body kinematics were measured for each subject during three gait cycles of walking and running using a full body and extended foot skin marker system [3]. Cartilage contact between the tibia and talus were added to a foot-ankle model [4] to allow estimation of articular joint mechanics using an elastic foundation model based on cartilage stiffness and mesh penetration [1]. Generic models were scaled for each individual and kinematics calculated for every trial. Based on subject-specific kinematics, articular joint mechanics were estimated using the OpenSim joint and articular mechanics (JAM) tool [1]. To investigate articular joint loading, contact area as well as mean and peak pressure at the ankle joint were analysed during the stance phase. Mean and peak cartilage contact pressure were comparable at heel strike and toe off, but substantially differed throughout the stance phases of walking and running (Fig. 1A). During walking, cartilage contact pressure showed a double peak with the higher peak around contralateral heel strike (peak pressure: 5.96±1.66 MPa) whereas during running cartilage contact pressure showed a single peak during mid-stance (peak pressure: 9.61±2.41 MPa) (Fig. 1A&B). Although similar cartilage contact locations were found for walking and running, contact area was considerably larger during running (1.39±0.15 cm²) then walking (0.96±0.19 cm²) (Fig. 1B).Download : Download high-res image (119KB)Download : Download full-size image This study showed a first analysis of ankle mechanics during multiple gait cycles of walking and running. Using a detailed musculoskeletal foot-ankle model combined with recently developed methods to estimate cartilage contact mechanics, this study allowed novel insights on the location and magnitude of articular joint loading. While this study provided important findings on the ankle joint, further developments are needed to also estimate cartilage contact mechanics at the subtalar joint. In addition, analysis of pathological cohorts such as subjects with chronic ankle instability or flat feet, will help to understand changes in articular mechanics and how they ","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":"135298059","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.2023.07.121
Merve Keskin, Derya Ozer Kaya
Dentists are at risk due to adverse conditions they are exposed to, such as improper working posture, repetitive movements, long-term static positions, excessive effort with frequent use of small muscles, tight grip of materials, using vibrating instruments, and holding their arms high for long periods of time (1). Does the scapular asymmetry distance increase as the working posture of dentists worsens? In the study, 122 volunteers (52 males, 70 females, age: 25.94±3.40 years) from dentists who have been active in the clinic for at least 6 months were included. The Lateral Scapular Slide Test was used to measure scapular asymmetry. Measurement was performed in 4 positions: in a neutral position of the glenohumeral joint with arms at both sides in a free-standing position, shoulders at 45° abduction and 90° abduction (2), and the arms were in 90° abduction holding 2.3 kg (5 lb) for those with a body weight of 68.1 kg and above, and 1.4 kg (3 lb) for those with a body weight of less than 68.1 kg. The distance between the inferior end of the scapula and the spinous process of the nearest thoracic vertebra was measured in all four positions. Working posture was evaluated during the study by observation with the REBA whole-body assessment method. The risk levels of the scoring results were made according to the REBA method; 1 point was classified as “negligible, 2-3 points as “low”, 4-7 points as “moderate”, 8-10 as “high” and 11-15 as “very high” (3,4). According to the REBA score risk classification, 36.1% of the participants were included between 4-7 “medium risk”, 56.6% 8-10 “high risk”, and 7.4% 11-15 “very high risk” group. The mean REBA score was found to be 6.48±0.73 in the intermediate-risk group, 8.72±0.73 in the high-risk group, and 11.00±0.00 in the very high-risk group. A positive correlation was found between the REBA score and dominant side lateral scapular slide test with neutral, 45°, 90° and weights (r=0.325, p<0.001; r=0.268, p=0.003; r=0.267, p=0.003; r=0.265, p=0.003). In the results, it was seen that the working posture of the dentists was risky and there was no participant in the risk-free group. The scapular asymmetry distance increased as the risk in the working posture of the dentists increased. In a previous study, interns and 1-year dentists were compared for the lateral scapular slide test, and, scapular asymmetry distance was found to be higher in 1-year dentists. (5). It has been observed that the exposure may increase as the exposure to the working posture increases. Risky postures may be related to scapular asymmetry those may further develop dysfunctions.
由于牙医所处的不利环境，例如不适当的工作姿势、重复的动作、长期静止的姿势、频繁使用小肌肉的过度用力、紧握材料、使用振动仪器、长时间高举手臂等，牙医会面临风险(1)。随着牙医工作姿势的恶化，肩胛骨不对称距离是否会增加?本研究纳入了122名志愿者，其中男性52名，女性70名，年龄25.94±3.40岁，均为在临床活动至少6个月的牙医。肩胛骨外侧滑动试验用于测量肩胛骨不对称。测量采用4种体位:肩关节中立位，两侧手臂独立站立，肩膀45°外展和90°外展(2)，手臂90°外展，体重在68.1 kg及以上的人保持2.3 kg (5 lb)，体重在68.1 kg以下的人保持1.4 kg (3 lb)。在所有四个位置测量肩胛骨下端与最近的胸椎棘突之间的距离。采用REBA全身评估法观察研究期间的工作姿势。采用REBA法对评分结果进行风险等级评定;1分为“可忽略”，2-3分为“低”，4-7分为“中等”，8-10分为“高”，11-15分为“非常高”(3,4)。根据REBA评分风险分类，36.1%的参与者处于4-7“中等风险”组，56.6%的参与者处于8-10“高风险”组，7.4%的参与者处于11-15“非常高风险”组。中危组REBA平均评分为6.48±0.73，高危组为8.72±0.73，极高危组为11.00±0.00。REBA评分与优势侧肩胛骨外侧滑动试验中性、45°、90°和体重呈正相关(r=0.325, p<0.001;r = 0.268, p = 0.003;r = 0.267, p = 0.003;r = 0.265, p = 0.003)。结果显示，牙医的工作姿势是有风险的，无风险组没有参与者。肩胛骨不对称距离随着牙医工作姿势风险的增加而增加。在之前的研究中，我们比较了实习生和1年牙医肩胛骨外侧滑动试验，发现1年牙医肩胛骨不对称距离更高。(5).据观察，暴露量可能随着工作姿势暴露量的增加而增加。危险的姿势可能与肩胛骨不对称有关，这些不对称可能进一步发展为功能障碍。
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Pub Date : 2023-09-01DOI: 10.1016/j.gaitpost.2023.07.116
Ioanna Katsaveli, Anthi Kellari, Zacharias Dimitriadis, Ioannis Poulis, Asimakis Kanellopoulos
Proprioception plays a crucial role to coordinated movement, which is fundamental for daily activities, exercise, and sports. The proprioceptive perception of joint angular velocity sense has received little attention in terms of research, unlike joint position sense, which has been thoroughly studied (1). The present research was conducted in order to investigate the behavior of the proprioceptive ability to comprehend and reproduce low-to-medium angular velocities in the knee joint in a healthy population. The investigation of the proprioceptive behavior regarding the accuracy of the knee joint angular velocity replication, in different joint angular velocities. 43 young healthy individuals (23 men and 20 women, mean age 20.84 yrs) participated in the present research, and were measured in 5 angular joint velocities, 30o/s, 45o/s, 60o/s, 75o/s and 90o/s, and in a randomized order, by using the “Biodex System 3 pro” isokinetic dynamometer. Five passive demonstration trials were followed by five active replications. The subjects were blindfolded during the whole procedure and they were blinded to the results, as were the examiners. Only the last 3 replication attempts were used to calculate the average velocity achieved, since the first two were considered as familiarization trials. The subjects appear to have reproduced the angular velocity of 30o/s more accurately. There is a statistically significant error in the replication of the rest of the velocities, incrementally increasing as the joint angular velocity increased. The lowest angular velocity of 30o/s showed the less significant replication error, both in absolute value (6.0o/s) and as a percentage (20.0%) of the targeted velocity, while 90o/s had the biggest one (34.9o/s and 38.8%, respectively). Something noteworthy was that the majority of the volunteers tend to undershoot the target velocities. Specifically, the number of subjects that undershoot (in comparison to the sample size) were 28/43, 38/43, 40/43, 41/43 and 43/43 for 30o/s, 45o/s, 60o/s, 75o/s and 90o/s respectively. The present study showed that as the joint angular velocity increases, and the brain cannot be informed on time about the joint motion state and is forced to predict it, the replication error increases. Regarding the unknown in the literature undershooting phenomenon observed in the present study, it seems that as the joint velocity increases and cannot be predicted with accuracy, the brain, from the spectrum of the possible predicted ones, always choses to replicate it with one of those with the lower values. This phenomenon may be an interesting conservative behavior of the brain, as the high joint angular velocities seem to be related with injuries.
{"title":"Investigation of the knee angular velocity proprioceptive behavior as the joint velocity increases","authors":"Ioanna Katsaveli, Anthi Kellari, Zacharias Dimitriadis, Ioannis Poulis, Asimakis Kanellopoulos","doi":"10.1016/j.gaitpost.2023.07.116","DOIUrl":"https://doi.org/10.1016/j.gaitpost.2023.07.116","url":null,"abstract":"Proprioception plays a crucial role to coordinated movement, which is fundamental for daily activities, exercise, and sports. The proprioceptive perception of joint angular velocity sense has received little attention in terms of research, unlike joint position sense, which has been thoroughly studied (1). The present research was conducted in order to investigate the behavior of the proprioceptive ability to comprehend and reproduce low-to-medium angular velocities in the knee joint in a healthy population. The investigation of the proprioceptive behavior regarding the accuracy of the knee joint angular velocity replication, in different joint angular velocities. 43 young healthy individuals (23 men and 20 women, mean age 20.84 yrs) participated in the present research, and were measured in 5 angular joint velocities, 30o/s, 45o/s, 60o/s, 75o/s and 90o/s, and in a randomized order, by using the “Biodex System 3 pro” isokinetic dynamometer. Five passive demonstration trials were followed by five active replications. The subjects were blindfolded during the whole procedure and they were blinded to the results, as were the examiners. Only the last 3 replication attempts were used to calculate the average velocity achieved, since the first two were considered as familiarization trials. The subjects appear to have reproduced the angular velocity of 30o/s more accurately. There is a statistically significant error in the replication of the rest of the velocities, incrementally increasing as the joint angular velocity increased. The lowest angular velocity of 30o/s showed the less significant replication error, both in absolute value (6.0o/s) and as a percentage (20.0%) of the targeted velocity, while 90o/s had the biggest one (34.9o/s and 38.8%, respectively). Something noteworthy was that the majority of the volunteers tend to undershoot the target velocities. Specifically, the number of subjects that undershoot (in comparison to the sample size) were 28/43, 38/43, 40/43, 41/43 and 43/43 for 30o/s, 45o/s, 60o/s, 75o/s and 90o/s respectively. The present study showed that as the joint angular velocity increases, and the brain cannot be informed on time about the joint motion state and is forced to predict it, the replication error increases. Regarding the unknown in the literature undershooting phenomenon observed in the present study, it seems that as the joint velocity increases and cannot be predicted with accuracy, the brain, from the spectrum of the possible predicted ones, always choses to replicate it with one of those with the lower values. This phenomenon may be an interesting conservative behavior of the brain, as the high joint angular velocities seem to be related with injuries.","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":"135298354","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.2023.07.263
Rebecca Louise Walker, Thomas D O'Brien, Gabor J Barton, Bernie Carter, David M Wright, Richard J Foster
Children with cerebral palsy (CwCP) experience regular falls [1] but their lived experiences of how falls occur in the real-world are unknown. Understanding real-world causes of falls by listening to perspectives of children and parents is vital, since typical walking analyses are carried out over level-ground and therefore overlooks everyday challenges to balance [2]. Walk-along interviews can generate rich insights into children’s everyday life by discussing experiences while walking [3]. This abstract presents findings from ‘The Walk-Along Project’, a novel qualitative investigation using walk-along interviews to explore lived experiences of CwCP. The Walk-Along Project aimed to determine the challenging walking environments (e.g. uneven surfaces) that increase fall-risk. What types of challenging environments affect fall-risk in CwCP, based on their lived experiences? Twelve CwCP (GMFCS I to III, 6 diplegia, 6 hemiplegia, 12±3 years old) and their parents participated in an outdoor walk-along interview lasting approximately 25 minutes. During each walk-along interview participants discussed previous fall experiences and everyday ‘challenging’ environments (likely to cause a fall) that they commonly encounter. Chest-mounted cameras (Kaiser Baas X450) and clip on microphones (RODE GO II) captured walking environments and conversations. Data from microphones were matched to video footage, manually transcribed and analysed in NVivo using interpretive description[4]. Environments that could or have previously caused a fall were identified by CwCP and photographed during walk-along interviews (Fig. 1). Any uneven surface that could cause a trip or balance disturbance was suggested as challenging, such as tactile paving: “I’d probably trip over it because it is bumpy” (child, aged 13) Unseen grass potholes were reported to cause most falls based on past experiences. Falls were also more likely when combined with sensory distractions (e.g. seeing/hearing nearby people/friends): “So like if I am walking in this direction and am looking at [people playing nearby] football I could go like that…[demonstrates trailing foot tripping on a raised grid]” (child, aged 16) Download : Download high-res image (167KB)Download : Download full-size image Children described things they do to reduce fall-risk, including being careful, avoiding places or walking slower: “I would just go slow on a grass surface and hope that I don’t fall” (Child, aged 8) Younger children evidenced receiving more parental intervention when walking in challenging environments (e.g. “watch your step”). In comparison, older children reported having better awareness of what could cause a fall compared to when they were younger. The Walk-Along Project provides novel insight beyond what is currently known about the types of challenging environments that increase fall-risk in CwCP. Both environmental (uneven surfaces) and sensory (everyday distractions) challenges contribute heavily to daily fa
脑瘫儿童(CwCP)经常跌倒[1]，但他们在现实世界中如何跌倒的生活经验尚不清楚。通过倾听儿童和家长的观点来了解跌倒的现实原因是至关重要的，因为典型的步行分析是在平地上进行的，因此忽略了日常的平衡挑战[2]。行走访谈可以通过边走边讨论经验，对儿童的日常生活产生丰富的见解[3]。这篇摘要介绍了“漫步项目”的发现，这是一项新颖的定性调查，使用漫步访谈来探索CwCP的生活经历。Walk-Along项目旨在确定具有挑战性的步行环境(例如不平整的表面)会增加跌倒的风险。根据他们的生活经历，哪些类型的具有挑战性的环境会影响CwCP的跌倒风险?12名CwCP (GMFCS I至III, 6名双瘫患者，6名偏瘫患者，12±3岁)及其父母参加了持续约25分钟的户外行走访谈。在每次步行访谈中，参与者讨论了他们以前的跌倒经历以及他们经常遇到的日常“具有挑战性”的环境(可能导致跌倒)。胸装摄像头(Kaiser Baas X450)和夹式麦克风(RODE GO II)捕捉行走环境和对话。来自麦克风的数据与视频片段相匹配，在NVivo中使用解释性描述进行人工转录和分析[4]。CwCP确定了可能或之前导致跌倒的环境，并在行走采访中拍摄了照片(图1)。任何可能导致跌倒或平衡障碍的不平坦表面都被认为是具有挑战性的，例如触觉铺路:“我可能会被它绊倒，因为它是颠簸的”(13岁的孩子)根据过去的经验，据报道，看不见的草坑是导致大多数跌倒的原因。当有感官干扰时(例如，看到/听到附近的人/朋友)，摔倒的可能性也更大:“所以，如果我朝这个方向走，看着[附近的人]踢足球，我可能会那样……[演示在一个升高的网格上拖着脚绊倒]”(16岁的孩子)下载:下载高分辨率图片(167KB)下载:下载完整尺寸图片孩子们描述了他们为减少跌倒风险所做的事情，包括小心，避开地方或走得慢一些:“我只会在草地上慢慢走，希望我不会摔倒”(8岁的孩子)年幼的孩子在具有挑战性的环境中行走时，父母会更多地干预(例如“注意脚下”)。相比之下，年龄较大的儿童报告说，与年轻时相比，他们对可能导致跌倒的原因有更好的认识。Walk-Along项目提供了新的见解，超越了目前已知的增加CwCP摔倒风险的挑战性环境类型。环境(不平坦的表面)和感官(日常分心)挑战都是导致日常跌倒发生的重要原因，但在现有的CwCP评估中并未考虑到这一点[2]。未来的工作应考虑这些相互作用的因素，当试图确定在高跌倒风险的CwCP和设计跌倒预防规划。
{"title":"“I’d go slow and hope I don’t fall” Exploring lived experiences of children with cerebral palsy walking in challenging environments","authors":"Rebecca Louise Walker, Thomas D O'Brien, Gabor J Barton, Bernie Carter, David M Wright, Richard J Foster","doi":"10.1016/j.gaitpost.2023.07.263","DOIUrl":"https://doi.org/10.1016/j.gaitpost.2023.07.263","url":null,"abstract":"Children with cerebral palsy (CwCP) experience regular falls [1] but their lived experiences of how falls occur in the real-world are unknown. Understanding real-world causes of falls by listening to perspectives of children and parents is vital, since typical walking analyses are carried out over level-ground and therefore overlooks everyday challenges to balance [2]. Walk-along interviews can generate rich insights into children’s everyday life by discussing experiences while walking [3]. This abstract presents findings from ‘The Walk-Along Project’, a novel qualitative investigation using walk-along interviews to explore lived experiences of CwCP. The Walk-Along Project aimed to determine the challenging walking environments (e.g. uneven surfaces) that increase fall-risk. What types of challenging environments affect fall-risk in CwCP, based on their lived experiences? Twelve CwCP (GMFCS I to III, 6 diplegia, 6 hemiplegia, 12±3 years old) and their parents participated in an outdoor walk-along interview lasting approximately 25 minutes. During each walk-along interview participants discussed previous fall experiences and everyday ‘challenging’ environments (likely to cause a fall) that they commonly encounter. Chest-mounted cameras (Kaiser Baas X450) and clip on microphones (RODE GO II) captured walking environments and conversations. Data from microphones were matched to video footage, manually transcribed and analysed in NVivo using interpretive description[4]. Environments that could or have previously caused a fall were identified by CwCP and photographed during walk-along interviews (Fig. 1). Any uneven surface that could cause a trip or balance disturbance was suggested as challenging, such as tactile paving: “I’d probably trip over it because it is bumpy” (child, aged 13) Unseen grass potholes were reported to cause most falls based on past experiences. Falls were also more likely when combined with sensory distractions (e.g. seeing/hearing nearby people/friends): “So like if I am walking in this direction and am looking at [people playing nearby] football I could go like that…[demonstrates trailing foot tripping on a raised grid]” (child, aged 16) Download : Download high-res image (167KB)Download : Download full-size image Children described things they do to reduce fall-risk, including being careful, avoiding places or walking slower: “I would just go slow on a grass surface and hope that I don’t fall” (Child, aged 8) Younger children evidenced receiving more parental intervention when walking in challenging environments (e.g. “watch your step”). In comparison, older children reported having better awareness of what could cause a fall compared to when they were younger. The Walk-Along Project provides novel insight beyond what is currently known about the types of challenging environments that increase fall-risk in CwCP. Both environmental (uneven surfaces) and sensory (everyday distractions) challenges contribute heavily to daily fa","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":"135298535","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.2023.07.254
Maud Van Den Bogaart, Maaike M. Eken, Rachel H.J. Senden, Rik G.J. Marcellis, Kenneth Meijer, Pieter Meyns, Hans M.N. Essers
Gait analysis is imperative for tailoring evidence-based interventions in individuals with and without a physical disability.1 The gold standard for gait analysis is optoelectronic three-dimensional motion analysis, which requires expertise, is laboratory based, and requires expensive equipment, which is not available in all settings, particularly in low to middle-income countries. New techniques based on deep learning to track body landmarks in simple video recordings allow recordings in a natural environment.2,3 Deeplabcut is a free and open-source toolbox to track user-defined features in videofiles.4,5 What is the minimal number of additional labelled frames needed for good tracking accuracy of markerless pose estimation (DeepLabCut) during treadmill walking? An increasing number of videos (1, 2, 5, 10, 15 and 20 videos) from typically developed adults (mean age = 50.7±17.3 years) were included in the analysis. Participants walked at comfortable walking speed on a dual-belt instrumented treadmill (Computer Assisted Rehabilitation Environment (CAREN), Motekforce Link, Amsterdam, The Netherlands). 2D video recordings were conducted in the sagittal plane with a gray-scale camera (50 Hz, Basler scA640-74gm, Basler, Germany). Using the pre-trained MPII human model (ResNet101; pcut-off = 0.8) in DeepLabCut, the following joints and anatomical landmarks were tracked unilaterally (left side): Ankle, knee, hip, shoulder, elbow and wrist (chin and forehead were excluded). An increasing number of frames was labeled per video (1 and 5 frames per video) and added to the pre-trained MPII human model, which was then retrained till 500.000 iterations. 95% of the labelled frames were used for training, 5% for testing. For each scenario with an increasing number of videos and manually labelled frames, the train and test error was calculated. Good tracking accuracy was defined as an error smaller then the diameter of a retroreflective marker (= 1.4 cm). The results of the train and test pixel errors are presented in Fig. 1 for 11 different scenarios. When the number of videos increased to 5 videos with 1 or 5 labelled frames, the train pixel error reduced to 1.11 and 1.16 pixels, respectively (corresponding to an error of < 1 cm). From labelling at least 20 frames, the test pixel error was less then 5 pixels (corresponding to an error of < 3 cm).Download : Download high-res image (91KB)Download : Download full-size image A good tracking accuracy (error < 1 cm) in the training set was achieved from 5 additionally labeled videos. The tracking accuracy for the test dataset remained constant (≈ 2-3 cm) from labelling 20 frames or more. Further research is needed and ongoing to determine the optimal number of training iterations and additional labelled videos and frames for good test and train tracking accuracy (< 1.4 cm). This optimal setup will then be used to validate DeepLabCut to measure joint centres and angles during walking with respect to the gold standard.
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Pub Date : 2023-09-01DOI: 10.1016/j.gaitpost.2023.07.208
Robert Reisig, Mehrdad Davoudi, Marco Götze, Firooz Salami, Sebastian Wolf
Cerebral Palsy (CP) is a neurodevelopmental disorder that affects motor function and coordination. While there is no curative treatment, various methods, surgical and conservative, can be used to optimize patients' physical performance. [1] Treatment planning involves physical examination, imaging, and gait analysis. [2] Despite being the only method apart from physical examination to assess muscle weakness and spasticity, the role of EMG data in decision-making is little understood. [3] However, it can be efficient to perform and could substantially improve treatment decision trees. [4] This Delphi Process complements a data driven approach with identical research goals so that findings of both can be integrated. How can EMG enhance diagnostic and therapeutic methods for patients with CP? Our objectives include identifying key EMG data features that advance decision-making processes and determining the most appropriate and impactful descriptors for data evaluation. Additionally, present-day utilization is being investigated. A Delphi Process is being employed, engaging an initial panel of 53 experts in gait analysis. Of these, 44 have agreed to continue their participation in the project. These experts were selected based on their affiliation with ESMAC and referrals from other participants. In the first round, panelists were asked about their current or past use of EMG in gait analysis for patients with CP. Questions covered the topics effectiveness, reliability, assessed muscles, data processing, decision-making processes involving EMG data, use of normative data, and descriptors being used to evaluate EMG. Participants will receive the evaluated results from the previous rounds and may base their decisions on this information. The second round is scheduled to begin by the end of April 2023. The third round is planned for completion and evaluation before ESMAC in September 2023. The Delphi Process is currently underway, and the first round has been completed. 90% of participants found EMG information in the context of CP to be at least somewhat helpful, and 79% considered it at least somewhat reliable. While at least 32% of participants rely solely on raw data, more than 21% solely use enveloped data. The muscles predominantly used for decision processes are rectus femoris and tibialis anterior. Statistic assessed musclesDownload : Download high-res image (86KB)Download : Download full-size image The most widespread descriptors used include 'delayed,' 'prolonged,' 'premature,' 'cocontraction,' 'out of phase,' 'absent,' 'early' and 'continuous. Current results show predominant consensus about helpfulness and reliability of EMG data in the context of CP. Simultaneously, there seem to be two major approaches in data evaluation – one using raw data and the other using envelopes. In future rounds of the process we aim to collect treatment decision trees from experts which are based on EMG data – may they be driven by experience or evidence – and tr
{"title":"A Delphi Process is being applied to objectify the systematic use of EMG in therapy of Cerebral Palsy","authors":"Robert Reisig, Mehrdad Davoudi, Marco Götze, Firooz Salami, Sebastian Wolf","doi":"10.1016/j.gaitpost.2023.07.208","DOIUrl":"https://doi.org/10.1016/j.gaitpost.2023.07.208","url":null,"abstract":"Cerebral Palsy (CP) is a neurodevelopmental disorder that affects motor function and coordination. While there is no curative treatment, various methods, surgical and conservative, can be used to optimize patients' physical performance. [1] Treatment planning involves physical examination, imaging, and gait analysis. [2] Despite being the only method apart from physical examination to assess muscle weakness and spasticity, the role of EMG data in decision-making is little understood. [3] However, it can be efficient to perform and could substantially improve treatment decision trees. [4] This Delphi Process complements a data driven approach with identical research goals so that findings of both can be integrated. How can EMG enhance diagnostic and therapeutic methods for patients with CP? Our objectives include identifying key EMG data features that advance decision-making processes and determining the most appropriate and impactful descriptors for data evaluation. Additionally, present-day utilization is being investigated. A Delphi Process is being employed, engaging an initial panel of 53 experts in gait analysis. Of these, 44 have agreed to continue their participation in the project. These experts were selected based on their affiliation with ESMAC and referrals from other participants. In the first round, panelists were asked about their current or past use of EMG in gait analysis for patients with CP. Questions covered the topics effectiveness, reliability, assessed muscles, data processing, decision-making processes involving EMG data, use of normative data, and descriptors being used to evaluate EMG. Participants will receive the evaluated results from the previous rounds and may base their decisions on this information. The second round is scheduled to begin by the end of April 2023. The third round is planned for completion and evaluation before ESMAC in September 2023. The Delphi Process is currently underway, and the first round has been completed. 90% of participants found EMG information in the context of CP to be at least somewhat helpful, and 79% considered it at least somewhat reliable. While at least 32% of participants rely solely on raw data, more than 21% solely use enveloped data. The muscles predominantly used for decision processes are rectus femoris and tibialis anterior. Statistic assessed musclesDownload : Download high-res image (86KB)Download : Download full-size image The most widespread descriptors used include 'delayed,' 'prolonged,' 'premature,' 'cocontraction,' 'out of phase,' 'absent,' 'early' and 'continuous. Current results show predominant consensus about helpfulness and reliability of EMG data in the context of CP. Simultaneously, there seem to be two major approaches in data evaluation – one using raw data and the other using envelopes. In future rounds of the process we aim to collect treatment decision trees from experts which are based on EMG data – may they be driven by experience or evidence – and tr","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":"135298541","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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