Characteristic Motion Patterns Research Articles

Kinematic analysis of movement patterns during a reach-and-grasp task in stroke patients.

This study aimed to evaluate the kinematic movement patterns during a reach-and-grasp task in post-stroke patients according to the upper extremity impairment severity. Subacute stroke patients (n = 46) and healthy controls (n = 20) were enrolled in this study. Spatiotemporal and kinematic data were obtained through 3D motion analysis during the reach-and-grasp task. Stroke patients were grouped using the Fugl-Meyer Assessment (FMA) scale, and a comparison of the groups was performed. The severe group showed a significantly longer movement time, lower peak velocity, and higher number of movement units than the mild group during the reach-and-grasp task (p < 0.05). Characteristic compensatory movement patterns, such as shoulder abduction, thoracic posterior tilting, and upward and external rotation were significantly greater during the forward transporting phase in the severe group than in the mild group (p < 0.05). The FMA score was significantly associated with the movement time during the forward transporting phase, number of movement units during the reaching phase, range of shoulder abduction-adduction and wrist flexion-extension movements during the reaching phase, and range of thoracic internal-external rotation during the backward transporting phase (p < 0.05). Post-stroke patients have unique spatiotemporal and kinematic movement patterns during a reach-and grasp-task according to the impairment severity.

Effects of translocation on American crocodile movements and habitat use in South Florida

AbstractThe range of the threatened American crocodile (Crocodylus acutus) in the United States is limited to the southernmost parts of Florida. As this species has recovered concurrently with an increasing human population, human–crocodile conflicts have also increased. Resolving conflicts can involve translocating crocodiles; however, they often return to the site from which they were removed. We examined the effects of translocation on crocodile movements, habitat use, body condition, and survival in Florida, USA, in 2018–2019 to refine recommendations for managers considering translocation to resolve human–crocodile conflict. We captured and attached global positioning system (GPS) units to 17 crocodiles, 10 of which served as a reference group (free‐ranging crocodiles released at their capture site) and 7 served as a treatment group (crocodiles that were translocated 14–158 km from their capture site). We collected location data from individual crocodiles for 34–661 days ( ~ 250 days for each group). Body condition was similar for both groups. Corticosterone levels measured periodically during handling indicated that crocodiles experienced increasing stress levels during handling. Three crocodiles translocated ≤45 km from their original capture site returned to that location within 13 days. Three crocodiles translocated ≥110 km did not return. One female translocated 152 km was recaptured 0.42 km from its original capture site 965 days after its release. We identified 2 states of characteristic movement patterns: state 1 indicated individuals moving slowly and somewhat randomly, and state 2 indicated individuals exhibiting fast, active directional movement. Translocated individuals were more likely than reference individuals to switch to, and stay in, state 2. Because of concerns regarding return rates and heightened stress as a result of capture and translocation, we suggest crocodile translocations have limited conservation value and may only be worth considering once all other reasonable options are exhausted.

Investigation of Characteristic Motion Patterns of the Knee Joint During a Weightbearing Flexion.

This study aimed to develop and validate a novel flexion axis concept by calculating the points on femoral condyles that could maintain constant heights during knee flexion. Twenty-two knees of 22 healthy subjects were investigated when performing a weightbearing single leg lunge. The knee positions were captured using a validated dual fluoroscopic image system. The points on sagittal planes of the femoral condyles that had minimal changes in heights from the tibial plane along the flexion path were calculated. It was found that the points do formulate a medial-lateral flexion axis that was defined as the iso-height axis (IHA). The six degrees of freedom (6DOF) kinematics data calculated using the IHA were compared with those calculated using the conventional transepicondylar axis and geometrical center axis. The IHA measured minimal changes in proximal-distal translations and varus-valgus rotations along the flexion path, indicating that the IHA may have interesting clinical implications. Therefore, identifying the IHA could provide an alternative physiological reference for improvement of contemporary knee surgeries, such as ligament reconstruction and knee replacement surgeries that are aimed to reproduce normal knee kinematics and medial/lateral soft tissue tensions during knee flexion.

Island hopping of active colloids.

Individual self-propelled colloidal particles, like active Brownian particles (ABP) or run-and-tumble (RT) swimmers, exhibit characteristic and well-known motion patterns. However, their interaction with obstacles remains an open and important problem. We here investigate the two-dimensional motion of silica-gold Janus particles (JP) suspended in a bath of smaller silica passive particles. Actuated by AC electric fields, the JP cruise through passive colloids organized in 'islands' due to attractive electrohydrodynamic (EHD) flows. A typical island contains dozens of particles. The JP travels straight in obstacle-free regions and reorients abruptly upon collision with an island. As an underlying mechanism, we propose that the scattering events are caused by the interplay of EHD flows, self-propulsion and local torques. The combination of directed motion and sudden reorientations leads to active trajectories resembling the RT behavior of biological microswimmers.

The effects of curve registration on linear models of jump performance and classification based on vertical ground reaction forces

Functional principal components define modes of variation in time series, which represent characteristic movement patterns in biomechanical data. Their usefulness however depends on the prior choices made in data processing. Recent research showed that better curve alignment achieved with registration (dynamic time warping) reduces errors in linear models predicting jump height. However, the efficacy of registration in different preprocessing combinations, including time normalisation, padding and feature extraction, is largely unknown. A more comprehensive analysis is needed, given the potential value of registration to machine learning in biomechanics. We evaluated popular preprocessing methods combined with registration, creating 512 models based on ground reaction force data from 385 countermovement jumps. The models either predicted jump height or classified jumps into those performed with or without arm swing. Our results show that the classification models benefited from registration in various forms, particularly when landmarks were placed at critical points. The best classifier achieved a 5.5 percentage point improvement over the equivalent unregistered model. However, registration was detrimental to the jump height models, although this performance variable may be a special case given its direct relationship with impulse. Our meta-models revealed the relative contributions made by various preprocessing operations, highlighting that registration does not generalise so well to new data. Nonetheless, our analysis shows the potential for registration in further biomechanical applications, particularly in classification, when combined with the other appropriate preprocessing operations.

ISB clinical biomechanics award winner 2021: Tibio-femoral kinematics of natural versus replaced knees – A comparison using dynamic videofluoroscopy

BackgroundA comparison of natural versus replaced tibio-femoral kinematics in vivo during challenging activities of daily living can help provide a detailed understanding of the mechanisms leading to unsatisfactory results and lay the foundations for personalised implant selection and surgical implantation, but also enhance further development of implant designs towards restoring physiological knee function. The aim of this study was to directly compare in vivo tibio-femoral kinematics in natural versus replaced knees throughout complete cycles of different gait activities using dynamic videofluoroscopy. MethodsTwenty-seven healthy and 30 total knee replacement subjects (GMK Sphere, GMK PS, GMK UC) were assessed during multiple complete gait cycles of level walking, downhill walking, and stair descent using dynamic videofluoroscopy. Following 2D/3D registration, tibio-femoral rotations, condylar antero-posterior translations, and the location of the centre of rotation were compared. FindingsThe total knee replacement groups predominantly experienced reduced tibial internal/external rotation and altered medial and lateral condylar antero-posterior translations compared to natural knees. An average medial centre of rotation was found for the natural and GMK sphere groups in all three activities, whereas the GMK PS and UC groups experienced a more central to lateral centre of rotation. InterpretationEach total knee replacement design exhibited characteristic motion patterns, with the GMK Sphere most closely replicating the medial centre of rotation found for natural knees. Despite substantial similarities between the subject groups, none of the implant geometries was able to replicate all aspects of natural tibio-femoral kinematics, indicating that different implant geometries might best address individual functional needs.

Analysis of Vortex Development over Eastern Indian Ocean using Potential Vorticity

A vortex phenomenon may have a significant influence, especially on wind circulation patterns and extreme weather in Indonesia. The formation of the vortex, initially located over the eastern part of the Indian Ocean has drawn attention due to the highest frequency of its occurrence and as the source of the vortex over the Indonesian region. Vortices generated in this region is also suspected as one of contributing factor for flooding events at Jakarta in 2002 and 2007, studying both formation and development mechanism of these vortices is essential. The evolution of vortex development is investigated to characterize the vortex motion and development pattern in the Eastern Indian Ocean region. The study was conducted for 17 years starting from 1998 to 2016 on every December-January-February (DJF) period using ECMWF (European Center for Medium-Range Weather Forecast) ERA-Interim Reanalysis data. The analysis of vortex evolution was conducted for each event using a composite evolution of potential vorticity anomalies in the isentropic layer. The result shows 84 vortex systems identified with three characteristic patterns of vortex movement that occurred during 295 days of the observation period. Composite analysis of potential vorticity anomalies shows that the initial formation of vortices in the Eastern Indian Ocean is related to the emergence of negative potential vorticity anomalies from the west, which subsequently forming the vortices.

Perception of yips among professional Japanese golfers: perspectives from a network modelled approach

‘Yips’ in golf is a complex spectrum of anxiety and movement-disorder that affects competitive sporting performance. With unclear etiology and high prevalence documented in western literature, the perception and management of this psycho-neuromuscular problem among Japanese elite golfers is unknown. The objective of this study was to explore factors associated with yips, investigate the performance deficits and the strategies implemented to prevent yips. We surveyed approx. 1300 professional golfers on their golfing habits, anxiety and musculoskeletal problems, kinematic deficits, changes in training and their outcomes. Statistical procedures included multiple logistic regression and network analysis. 35% of the respondents had experienced yips in their career, their odds increasing proportionally to their golfing experience. Regardless of musculoskeletal symptoms, about 57% of all yips-golfers attributed their symptoms to psychological causes. Network analysis highlighted characteristic movement patterns, i.e. slowing, forceful or freezing of movement for putting, approach and teeing shots respectively. Golfers’ self-administered strategies to relieve yips were mostly inconsequential. Within the limits of our self-reported survey, most golfers perceived yips as a psychological phenomenon despite evidence pointing to a movement-disorder. While self-administered interventions were satisfactory at best, it may be imperative to sensitize golfers from a movement-disorder standpoint for early management of the problem.

Preference for locomotion-compatible curved paths and forward direction of self-motion in somatomotor and visual areas

During locomotion, leg movements define the direction of walking (forward or backward) and the path one is taking (straight or curved). These aspects of locomotion produce characteristic visual motion patterns during movement. Here, we tested whether cortical regions responding to either egomotion-compatible visual motion, or leg movements, or both, are sensitive to these locomotion-relevant aspects of visual motion. We compared a curved path (typically the visual feedback of a changing direction of movement in the environment) to a linear path for simulated forward and backward motion in an event-related fMRI experiment. We used an individual surface-based approach and two functional localizers to define (1) six egomotion-related areas (V6+, V3A, intraparietal motion area [IPSmot], cingulate sulcus visual area [CSv], posterior cingulate area [pCi], posterior insular cortex [PIC]) using the flow field stimulus and (2) three leg-related cortical regions (human PEc [hPEc], human PE [hPE] and primary somatosensory cortex [S–I]) using a somatomotor task. Then, we extracted the response from all these regions with respect to the main event-related fMRI experiment, consisting of passive viewing of an optic flow stimulus, simulating a forward or backward direction of self-motion in either linear or curved path. Results showed that some regions have a significant preference for the curved path motion (hPEc, hPE, S–I, IPSmot) or a preference for the forward motion (V3A), while other regions have both a significant preference for the curved path motion and for the forward compared to backward motion (V6+, CSv, pCi). We did not find any significant effects of the present stimuli in PIC. Since controlling locomotion mainly means controlling changes of walking direction in the environment during forward self-motion, such a differential functional profile among these cortical regions suggests that they play a differentiated role in the visual guidance of locomotion.

Comparison of the spine kinematics by defining lumbar as single and multi-segmental in completing critical daily task

The change of the spinal curvature in completing a variety of daily tasks is essential to independent living. There is still a lack of studies highlighting the lumbar segmental contribution during sit-to-stand (STS) and stand-to-flexion (STF) using non-invasive study. The purpose of this study is to compare the spine kinematics by defining lumbar as a single and multi-segmental during continuous daily motion in healthy Asian adults using a non-invasive approach. During STS, most subjects implemented kyphotic lumbar curve during the early stage of motion which revealed poor posture implementation and significant differences in the lumbar kinematics which were only noticeable at specific phases between both approaches. A significant difference in multi-segmental behaviour was observed only at the end of the motion. All three segments displayed different time responses during the transition from kyphotic to lordotic curve. Passive/delayed behavior within the lower lumbar segment was observed between 0-50% of motion completion. During STF, statistically significant differences were found between assuming lumbar as a single and multi-segment in all phases. This in vitro study identified characteristic motion patterns in the lumbar spine during daily motions. The results provided a clear description of the healthy spinal condition of adults and may serve to identify specific multi-segmental contribution.

Investigation of the pedaling forces in a cycling field test using the non-linear measure ML1

The study of biomechanical and physiological variables allows human movement scientists to investigate the characteristics of movement patterns in cyclists. While straightforward and well-investigated, linear measures may not adequately capture the underlying complexity of movements during cycling. Therefore, a non-linear phase-space measure (ML1) was applied to forces and heart rates of nine cyclists in a field test. The test was repeated two times with different instructions on how to alter the bike’s gearing while cycling a 12.5 km long level track. Pedaling forces and heart rates were measured. Future aim of the underlying study is the investigation of innovative control algorithms for e-bike propulsions. Force-time curves were sequenced into single cycles, linearly interpolated in the time domain, and z-score normalized. ML1 was calculated in a flowing window algorithm of 50 cycles. With fixed gearing, a contrast analysis showed that changes in terrain inclination were strongly associated with changes in the non-linear measure ML1. The calculation of Spearman’s cross correlation showed high coefficients of correlation between ML1 and delayed heart rate. The results indicate systematic changes of the pedaling movement as an adaptive response to changes in terrain inclination. Future research may utilize the findings from this study to investigate possible relationships between subjective measures of exhaustion, comfort, and discomfort with biomechanical characteristics of the pedaling movement.

Open-Source 3D Printable GPS Tracker to Characterize the Role of Human Population Movement on Malaria Epidemiology in River Networks: A Proof-of-Concept Study in the Peruvian Amazon.

Human movement affects malaria epidemiology at multiple geographical levels; however, few studies measure the role of human movement in the Amazon Region due to the challenging conditions and cost of movement tracking technologies. We developed an open-source low-cost 3D printable GPS-tracker and used this technology in a cohort study to characterize the role of human population movement in malaria epidemiology in a rural riverine village in the Peruvian Amazon. In this pilot study of 20 participants (mean age = 40 years old), 45,980 GPS coordinates were recorded over 1 month. Characteristic movement patterns were observed relative to the infection status and occupation of the participants. Applying two analytical animal movement ecology methods, utilization distributions (UDs) and integrated step selection functions (iSSF), we showed contrasting environmental selection and space use patterns according to infection status. These data suggested an important role of human movement in the epidemiology of malaria in the Peruvian Amazon due to high connectivity between villages of the same riverine network, suggesting limitations of current community-based control strategies. We additionally demonstrate the utility of this low-cost technology with movement ecology analysis to characterize human movement in resource-poor environments.

Simultaneous identification of human body model parameters and gait trajectory from 3D motion capture data

The analysis of human movements rests on a realistic human body model. Deducing model parameters from anthropomorphic data is challenging since these are inherently imprecise. An approach to improve model accuracy is the parameter adaptation based on motion data. 3D motion capture data are already being used for generating the trajectories of a human body model, so combining motion tracking and parameter identification seems most natural. This paper introduces a holistic approach to simultaneously identify the geometric parameters of a kinematic human lower limb model and the parameters defining a (cyclic) gait trajectory, based on 3D marker positions. The result is a time-continuous description of a physiologically compatible lower extremity movement along with optimal model parameters so to best reproduce the captured motion. The method takes into account restrictions such as the range of motion of human body joints and is robust against missing data due to marker occlusions or failures of the measurement system. Considering multiple gait cycles of a movement trial, we derive the characteristic motion pattern (CMP) of a specific subject walking at a specific speed. Our method further allows for motion analysis and assessment, but also for motion synthesis with arbitrary time span and time resolution and can thus be used for simulations and trajectory planning of rehabilitation and movement assistance systems, such as exoskeletons.

Computational Analysis of Movement Patterns of Dogs with ADHD-Like Behavior.

Simple SummaryADHD-like (attention deficit hyperactivity disorder) behavior in dogs may be expressed as impulsivity, inattentiveness, or aggression, compromising both dog and owner quality of life. Its treatment in a clinical setting requires behavioral modification and sometimes a medical treatment is added. There is a lack of objective tools for assessment and diagnosis of the problem, and behavioral experts mostly rely on owner reports. To address this gap, in this paper we use a self-developed computational tool which automatically analyzes movement of a dog from video footage collected during behavioral consultation. Based on a computational analysis of behavioral consultations of 12 dogs medically treated due to ADHD-like behavior and of a control group of 12 dogs with no reported behavioral problems, we identify three dimensions of characteristic movement patterns of dogs with ADHD-like behaviors, which are detectable during consultation. These include (i) high speed of movement, (ii) large coverage of room space, and (iii) frequent re-orientation in room space. These patterns can form the basis for computational methods for objective assessment of dogs with ADHD-like behavior that could help for diagnosis and clinical treatment of the disorder.Computational approaches were called for to address the challenges of more objective behavior assessment which would be less reliant on owner reports. This study aims to use computational analysis for investigating a hypothesis that dogs with ADHD-like (attention deficit hyperactivity disorder) behavior exhibit characteristic movement patterns directly observable during veterinary consultation. Behavioral consultations of 12 dogs medically treated due to ADHD-like behavior were recorded, as well as of a control group of 12 dogs with no reported behavioral problems. Computational analysis with a self-developed tool based on computer vision and machine learning was performed, analyzing 12 movement parameters that can be extracted from automatic dog tracking data. Significant differences in seven movement parameters were found, which led to the identification of three dimensions of movement patterns which may be instrumental for more objective assessment of ADHD-like behavior by clinicians, while being directly observable during consultation. These include (i) high speed, (ii) large coverage of space, and (iii) constant re-orientation in space. Computational tools used on video data collected during consultation have the potential to support quantifiable assessment of ADHD-like behavior informed by the identified dimensions.

Use of Accelerometry for Long Term Monitoring of Stroke Patients.

Stroke patients are monitored hourly by physicians and nurses in an attempt to better understand their physical state. To quantify the patients’ level of mobility, hourly movement (i.e. motor) assessment scores are performed, which can be taxing and time-consuming for nurses and physicians. In this paper, we attempt to find a correlation between patient motor scores and continuous accelerometer data recorded in subjects who are unilaterally impaired due to stroke. The accelerometers were placed on both upper and lower extremities of four severely unilaterally impaired patients and their movements were recorded continuously for 7 to 14 days. Features that incorporate movement smoothness, strength, and characteristic movement patterns were extracted from the accelerometers using time-frequency analysis. Support vector classifiers were trained with the extracted features to test the ability of the long term accelerometer recordings in predicting dependent and antigravity sides, and significantly above baseline performance was obtained in most instances (n}{}P < 0.05n). Finally, a leave-one-subject-out approach was carried out to assess the generalizability of the proposed methodology, and above baseline performance was obtained in two out of the three tested subjects. The methodology presented in this paper provides a simple, yet effective approach to perform long term motor assessment in neurocritical care patients.

Automatic Extraction and Detection of Characteristic Movement Patterns in Children with ADHD Based on a Convolutional Neural Network (CNN) and Acceleration Images.

Attention deficit and hyperactivity disorder (ADHD) is a neurodevelopmental disorder, which is characterized by inattention, hyperactivity and impulsive behaviors. In particular, children have difficulty keeping still exhibiting increased fine and gross motor activity. This paper focuses on analyzing the data obtained from two tri-axial accelerometers (one on the wrist of the dominant arm and the other on the ankle of the dominant leg) worn during school hours by a group of 22 children (11 children with ADHD and 11 paired controls). Five of the 11 ADHD diagnosed children were not on medication during the study. The children were not explicitly instructed to perform any particular activity but followed a normal session at school alternating classes of little or moderate physical activity with intermediate breaks of more prominent physical activity. The tri-axial acceleration signals were converted into 2D acceleration images and a Convolutional Neural Network (CNN) was trained to recognize the differences between non-medicated ADHD children and their paired controls. The results show that there were statistically significant differences in the way the two groups moved for the wrist accelerometer (t-test p-value <0.05). For the ankle accelerometer statistical significance was only achieved between data from the non-medicated children in the experimental group and the control group. Using a Convolutional Neural Network (CNN) to automatically extract embedded acceleration patterns and provide an objective measure to help in the diagnosis of ADHD, an accuracy of 0.875 for the wrist sensor and an accuracy of 0.9375 for the ankle sensor was achieved.

„Wär’ schön, wenn sie’s schaffen würde!“

AbstractThis article is based on the KMP (Kestenberg Movement Profile) for assessment of child development and movement behavior. I investigate characteristic movement patterns in a videotaped child psychoanalytic session. How do therapist and child move together? Since the KMP is commonly applied in dance therapy to evaluate movement skills and give support to development process, I will propose some suggestions for alternative modes of moving and encourage the building up of a new dialogue through action modification.

Early-onset of symptoms and clinical course of Pompe disease associated with the c.-32–13 T > G variant

BackgroundIndividuals with late-onset Pompe disease (LOPD) and the common c.-32–13 T > G variant are widely thought to have milder, adult-onset disease. This belief, and the consequent low suspicion of clinical involvement in children, has led to delays in diagnosis and treatment initiation in patients with early onset of symptoms. Previous reports of LOPD in children do not include description of the early-onset phenotype. This description of signs and symptoms, some of which are subtle and less known, is important to facilitate prompt identification and appropriate treatment in symptomatic children. MethodsRetrospective chart review of a cohort of 84 LOPD patients with the c.-32–13 T > G variant was conducted to identify patients diagnosed clinically (as opposed to through newborn screening) who had clinically documented symptom-onset within the first two years of life. ResultsFour patients had early onset of symptoms, with age at onset ranging from 10 days to 20 months. Initial symptoms included delay in achievement of gross motor milestones, signs of proximal muscle weakness, swallow and feeding difficulties, and sleep apnea. Early and characteristic alterations in posture and movement were identified in all patients. Age at diagnosis ranged from 10 months to 26 months. Median age at enzyme replacement therapy (ERT) initiation was 23.5 months. Despite ERT, progression of musculoskeletal involvement and residual muscle weakness was evident in all patients, as evidenced by ptosis, myopathic facies, scoliosis, lumbar lordosis, scapular winging, and trunk and lower extremity weakness. Standardized functional assessments showed gross motor function below age level as measured by the Alberta Infant Motor Scales, the Peabody Developmental Motor Scales-2, the Bruininks-Oseretsky Test of Motor Proficiency, Second Edition, and the six-minute walk test. ConclusionsOnset of symptoms including delay in achievement of gross motor milestones, signs of proximal muscle weakness, swallow and feeding difficulties, and sleep apnea in the first two years of life is not uncommon in individuals with LOPD and the c.-32–13 T > G variant. Patients with early-onset disease appear to have a more, rapid and severe progression of disease with persistent residual muscle deficits which partially improve with higher doses of ERT. Careful evaluation for specific and characteristic patterns of posture and movement in patients with this variant is necessary to identify those who have early onset of disease. Increased awareness of the early-onset signs and symptoms may also enable early identification of disease onset in children who are diagnosed through newborn screening.

Holistic segmentation of the lung in cine MRI.

Duchenne muscular dystrophy (DMD) is a childhood-onset neuromuscular disease that results in the degeneration of muscle, starting in the extremities, before progressing to more vital areas, such as the lungs. Respiratory failure and pneumonia due to respiratory muscle weakness lead to hospitalization and early mortality. However, tracking the disease in this region can be difficult, as current methods are based on breathing tests and are incapable of distinguishing between muscle involvements. Cine MRI scans give insight into respiratory muscle movements, but the images suffer due to low spatial resolution and poor signal-to-noise ratio. Thus, a robust lung segmentation method is required for accurate analysis of the lung and respiratory muscle movement. We deployed a deep learning approach that utilizes sequence-specific prior information to assist the segmentation of lung in cine MRI. More specifically, we adopt a holistically nested network to conduct image-to-image holistic training and prediction. One frame of the cine MRI is used in the training and applied to the remainder of the sequence ([Formula: see text] frames). We applied this method to cine MRIs of the lung in the axial, sagittal, and coronal planes. Characteristic lung motion patterns during the breathing cycle were then derived from the segmentations and used for diagnosis. Our data set consisted of 31 young boys, age [Formula: see text] years, 15 of whom suffered from DMD. The remaining 16 subjects were age-matched healthy volunteers. For validation, slices from inspiratory and expiratory cycles were manually segmented and compared with results obtained from our method. The Dice similarity coefficient for the deep learning-based method was [Formula: see text] for the sagittal view, [Formula: see text] for the axial view, and [Formula: see text] for the coronal view. The holistic neural network approach was compared with an approach using Demon's registration and showed superior performance. These results suggest that the deep learning-based method reliably and accurately segments the lung across the breathing cycle.

Are there characteristic motion patterns in the lumbar spine during flexion?

Flexion is the main motion of the lumbar spine. While in vitro tests with pure moments suggest larger intra-segmental rotations for the more caudal segments, in vivo results show diverging motion distributions. The present study analysed the motion distribution in vivo of 320 asymptomatic subjects.The change of the back curvature between standing and upper body flexion was determined using a non-invasive measurement device. Linear, bilinear, trilinear, quadratic, and cubic regression models were fitted to the segmental motion distribution over the lengths of the lordosis to categorise characteristic motion patterns. Simplicity and approximation quality were used to assign the motion distributions to the regression models.Seventy-seven percent of the motion distributions could be explained by a bilinear model. A further 12% and 11% could be represented by a trilinear and linear model, respectively. Less than 1% of the distributions could not satisfactorily be represented by the models. All of the bilinear models displayed maximum flexion in approximately the middle of lordosis. All linear models showed a decreasing rotation from caudal to cranial. Most of the trilinear models displayed a distribution similar to the bilinear. Age, sex, body height, and weight did not significantly affect these distributions.This in vivo study identified characteristic motion patterns in the lumbar spine during flexion. The quantitative results provide a clear description of the healthy condition and may serve to identify spinal motion abnormalities.