32 research outputs found
RECESSION OF KAFFIØYRA REGION GLACIERS, OSCAR II LAND, SVALBARD
The main aim of this research was to describe the course of the glacier retreat in the Kaffiøyra Region, starting from the maximum advance of the glaciers to the year 2009. From maps and archival data as well as the results of the field measurements and GPS measurements carried out in the years 1977–2009, the authors present the retreat histories for six glaciers. The smallest retreat was recorded for Waldemarbreen (8 m a-1), while Elisebreen retreated at the fastest rate of 18 m a-1. Since 1909 the area of Kaffiøyra glaciers has decreased by 37% on average. The smallest change was recorded in the case of Irenebreen and Waldemarbreen, while the largest was in the case of Oliverbreen and Einvindbreen. As the analysis of the glacier extension in the valley areas of the Kaffiøyra Region indicates, all of them have been in the same recession stage since 1909.
Toward the autism motor signature : gesture patterns during smart tablet gameplay identify children with autism
Autism is a developmental disorder evident from infancy. Yet, its clinical identification requires expert diagnostic training. New evidence indicates disruption to motor timing and integration may underpin the disorder, providing a potential new computational marker for its early identification. In this study, we employed smart tablet computers with touch-sensitive screens and embedded inertial movement sensors to record the movement kinematics and gesture forces made by 37 children 3-6 years old with autism and 45 age- and gender-matched children developing typically. Machine learning analysis of the children’s motor patterns identified autism with up to 93% accuracy. Analysis revealed these patterns consisted of greater forces at contact and with a different distribution of forces within a gesture, and gesture kinematics were faster and larger, with more distal use of space. These data support the notion disruption to movement is core feature of autism, and demonstrate autism can be computationally assessed by fun, smart device gameplay
Tablet-based gameplay identifies movement patterns related to autism spectrum disorder
Background: It has been proposed that one of the early markers of autism spectrum disorder (ASD) are abnormalities in the development of intentional movements, which can be observed from early childhood. New evidence suggests that disruption of motor timing and integration may underpin the disorder, providing a new potential marker for its identification. Objectives: In this study, we used widely available tablet devices (iPads) to identify differences in kinematics between children diagnosed with ASD and their typically developing (TD) peers. We also compared movement patterns of children diagnosed with neurodevelopmental disorders other than autism (OND) with movement patterns exhibited by ASD and TD children. We utilised tablet devices’ inertial sensors (accelerometer, gyroscope, and touchscreen to record the movements children make while playing two educational games on a tablet. Methods: Ninety-six children (aged 3-6) diagnosed with ASD, 37 diagnosed with OND, and 387 TD children took part in the study. The children were asked to play two educational games on a tablet. Each game consisted of two parts: two-minute long training and five-minute long test session. During the gameplay, we collected data from tablet’s sensors and screen. After the experimental session, 262 variables obtained by simple calculation of the raw sensor data (e.g. acceleration of the movements) were extracted and analysed using machine learning algorithms. To increase generalisation properties of the models, we reduced dimensionality to 49 most significant variables. Results: To compare movement patterns of children with ASD, OND, and TD children, we used machine learning algorithms. Each algorithm differentiated individuals within the ASD group from the other groups using 49 variables derived from the touch screen and inertial sensors. ASD - TD comparison: The algorithms classified children diagnosed with ASD from TD children with up to 93% accuracy. OND - TD comparison: The algorithms classified children diagnosed with OND from TD children with up to 95% accuracy. The results suggest that movement patterns of typically developing children are different than patterns exhibited by children diagnosed with neurodevelopmental disorders other than autism. ASD - OND comparison The algorithms classified children diagnosed with ASD from OND children with up to 93% accuracy. This result suggests that ASD is characterised by movement patterns that can be differentiated from patterns related to other neurodevelopment disorders. Conclusions: These findings support the view that children with ASD can be differentiated from TD children by movement patterns analysis. We also provide evidence suggesting that patterns characteristic of ASD children are different from patterns exhibited by children with OND. However, the latter result is not particularly strong due to the small sample of OND group. Further research is needed to provide better evidence
Disruption to motor intentions in children with autism : kinematic evidence for brainstem timing errors
Human movements are prospective (Delafield-Butt et al., 2018). They must anticipate ahead of time their lawful consequences (Delafield-Butt & Gangopadhyay, 2013; Trevarthen & Delafield-Butt, 2017a, 2017b). In children with autism, evidence indicates a common disruption to prospective movement may underpin its early pathogenesis (Trevarthen & Delafield-Butt, 2013) and may be a cardinal feature of autism (Fournier et al., 2006). Yet, more work is required to better characterize this possible ‘autism motor signature’ and to probe its neurodevelopmental origins. In this study, we employed smart tablet computers with touch-sensitive screens and embedded inertial movement sensors to ecologically record the subsecond motor kinematics of purposive, prospective movements made by children developing with and without autism
A prospective perception-action strategy in children with autism during smart-tablet gameplay
Background: Motor differences between children with autism spectrum disorders (ASD) and those with typical development (TD) have been identified in various activities such as pointing (Torres et al., 2013) and placing (Crippa et al., 2014). Kinematic differences have also been observed in goal-oriented swipe kinematics during smart-tablet gameplay (Lu et al., 2019, 2020). General Tau Theory has been used to describe goal-oriented perception-action strategies (Lee, 2009), which proposes an intrinsic action guide generated by the nervous system coupled to the motor command to guide the physical movement. The coupling constant between the two is assumed to be set by the brain to coordinate the kinematic profile of the goal-oriented action. Here, an exploration to surface a potential difference in the tau-coupling during smart-tablet gameplay in children with ASD is presented. Objectives: To test whether or not the perception-action strategy employed by children with and without ASD differ during goal-oriented swipes in smart-tablet gameplay. Methods: Goal-oriented swipe data were extracted from a study of smart-tablet gameplay for young children (Anzulewicz et al., 2016). Only those swipes that proceeded directly from start to finish without overshooting the target were included. A total of 500 swipes were obtained from 32 children with ASD (aged 33-79 months), and 1426 swipes were obtained from 44 children with TD (aged 36-74 months). The percentage of tau-coupling in each swipe, its duration and distance, and the tau-coupling constant were determined utilising the time and x- and y-coordinates data. Results: Children with ASD demonstrated 97.90 ± 10.49 (mean ± SD) % while children with TD demonstrated 98.98 ± 7.54 % of tau-coupling movement, indicating a significantly weakening (t-test, p = 0.01) and more variable (F-test, p < 0.01) tau-coupling pattern in children with ASD. The coupling constant was 0.40 ± 0.93 for the ASD group and 0.41 ± 0.15 for the TD group. Children with ASD demonstrated a significantly wider range of the coupling constant than children with TD (F-test, p < 0.01) while the mean values were similar. Conclusions: The findings indicate that, in comparison to children with TD, children with ASD demonstrated significantly less tau-coupling with higher variability during swipes whilst engaging in smart-tablet gameplay. It should be noted that the coupling constant in ASD was significantly more variable, however, the mean value was similar to what was observed in TD. The results of the coupling constant imply that, for the overall movement, children with ASD and TD used similar strategies to perform the goal-oriented swipes while greater fluctuations were observed in ASD. These findings are consistent with previous reports indicating that individuals with ASD have difficulties in controlling goal-oriented movement efficiently with increased subsecond motor variability during the travel of the movement (Torres et al., 2013). Increased acceleration and jerk amplitudes noted in adults with ASD (Cook et al., 2013) suggests sensorimotor and timing are disrupted at the level of the brainstem integration (Delafield-Butt & Trevarthen, 2017). Therefore, disruption to efficient perception-action regulation by tau-coupling might be a critical motor disruption in ASD
Kinematics of prospective motor control in autism spectrum disorder : an exploratory multilevel modelling analysis of goal-directed finger movements during smart-tablet gameplay
Background: Disturbance in movement is widely observed in autism and differences have been measured at the level of movement kinematics. Anzulewicz et al (2016) showed that gesture patterns from smart-tablet gameplay can distinguish between children with autism (ASD) and typically developing children (TD) with high accuracy using a machine learning algorithm, but a limitation of the data-driven approach used is that distinguishing features included in the algorithm may not be grounded in theory. It has been suggested that prospective control of movement is disrupted in autism, and this may result from impairments in using sensory feedback as the movement unfolds, despite intact control of internally generated movements. Furthermore, movement kinematics variables which are influenced by task difficulty and change with motor development have been identified to indicate prospective motor control.Objectives: The objective of the analysis is to explore differences between ASD and TD children in the kinematics of prospective motor control during goal-directed finger movements to different target distances, using data collected by Anzulewicz et al (2016).Methods: Touch-screen position coordinates of 4775 goal-directed swipes made during a smart-tablet gameplay by 82 children, aged 3-5 years old, were analysed. Target distance was calculated as the length between start and end position of each swipe and five kinematic variables related to prospective motor control were calculated from time differentials of position, namely: (1) peak velocity of the full movement, (2) peak velocity of the first movement unit (1MU), (3) number of movement units (velocity peaks), (4) % time in deceleration and (5) % time to peak velocity. Multilevel modelling was used to analyse the fixed effects and interaction effect of target distance and ASD diagnosis on each kinematic outcome, including a random effect to control for correlation in the kinematic outcome for swipes by the same individual.Results: Increase in 1cm target distance led to an increase in peak velocity of the full movement, and ASD children showed a greater increase than TD (Interaction: 3%, CI: 1% to 4%, p<0.001). TD children showed a 3% reduction in peak velocity (1MU) (CI: -5% to 0%, p=0.05) and decelerate 0.41% longer (CI: 0.20% - 0.63%, p<0.001) for more distant targets, but children with ASD showed the opposite relationship (Peak velocity (1MU) - Interaction: 9%, CI: 3% to 14%, p<0.001; Deceleration - interaction: -0.54%, CI: -0.93% to -0.14%, p=0.008). ASD children reached a peak in velocity later for more distant targets (Interaction: 1.28%, CI: 0.39% to 2.16%, p=0.005), but no relationship is seen for TD children. Overall, ASD children have 31% more movement units than TD (CI: 1% to 70%, p=0.04), but a 3% smaller increase in movement units for more distant targets (CI: -5% to -1%, p=0.007).Conclusions: The kinematics of prospective control is different for children with ASD and TD, and may help to identify children with autism. These findings are consistent with the idea that individuals with ASD may differ in the use of feedback control, and internal feedforward control may be influenced differently by external constraints such as target distance
A diagnostic evaluation of tablet serious games for the assessment of autism spectrum disorder in young children
Recent evidence suggests an underlying movement disruption may be a core component of Autism Spectrum Disorder (ASD) and a new, accessible early biomarker. Mobile smart technologies such as iPads contain inertial movement and touch-screen sensors capable of recording sub second movement patterns during gameplay. A previous pilot study employed machine learning analysis of motor patterns recorded from children 3-5 years old. It identified those with ASD from age- and gender-matched controls with 93% accuracy, presenting an attractive assessment method suitable for use in the home, clinic or classroom. This is a Phase III prospective, diagnostic classification study designed according to the Standards for Reporting Diagnostic Accuracy Studies (STARD) guidelines. Three cohorts are investigated: children developing typically (TD); children with a clinical diagnosis of ASD; and children with a diagnosis of another neurodevelopmental disorder (OND) that is not ASD. The study will be completed in Glasgow, U.K., and Gothenburg, Sweden. The recruitment target is 760 children (280 TD, 280 ASD and 200 OND). Children play two games on the iPad then a third party data acquisition and analysis algorithm (Play.Care, Harimata sp. z o.o., Poland) will classify the data as positively or negatively associated with ASD. The results are blind until data collection is complete, when the algorithm’s classification will be compared against medical diagnosis. Furthermore, parents of participants will complete three questionnaires: Strengths and Difficulties Questionnaire; ESSENCE Questionnaire; and the Adaptive Behavioural Assessment System. The primary outcome measure is sensitivity and specificity of Play.Care to detect ASD. Secondary outcomes include the ability of Play.Care to differentiate ASD from OND
Phase 3 diagnostic evaluation of a smart tablet serious game to identify autism in 760 children 3–5 years old in Sweden and the United Kingdom
Acknowledgments We are grateful to the children, their parents, teachers and clinicians who have worked so hard to make this study possible, both in its design and in its implementation. Funding This work was subcontracted to the University of Strathclyde by Harimata sp. z o.o. as an integral part of a Horizon 2020 SME Instrument, grant number 756079. Prepublication history for this paper is available online. To view these files, please visit the journal online (http://dx.doi.org/10.1136/bmjopen-2018-026226).Peer reviewedPublisher PD
State-of-the-art of transcatheter treatment of aortic valve stenosis and the overview of the InFlow project aiming at developing the first Polish TAVI system
Initial experience of transcatheter aortic valve implantation (TAVI) or replacement (TAVR) has ap-peared as a promising minimally invasive technology for patients disqualified from surgical treatment (SAVR). Safety and efficacy of TAVI has been analyzed and assessed through numerous registries and trials. Furthermore, results obtained from comparative TAVI vs. SAVR trials proved that both treat¬ments can be considered equal in terms of post-procedural mortality and morbidity in high-risk, as well as lower risk patients. However, there are still some issues that have to be addressed, such as higher chance of paravalvular leakage, vascular injuries, conduction disturbances, malpositioning and the yet unmet problem of insufficient biological valves durability. Recent technological developments along with the learning curve of operators prove a great potential for improvement of TAVI and a chance of surpassing SAVR in various groups of patients in the near future. In pursuit of finding new solutions, the CardValve Consortium consisting of leading scientific and research institutions in Poland has been created. Under the name of InFlow and financial support from the National Center for Research and Development, they have started a project with the aim to design, create and implement into clinical practice the first, Polish, low-profile TAVI valve system, utilizing not only biological but also artificial, polymeric-based prosthesis. This review focuses on current developments in TAVI technologies including the InFlow project
Long-term bio-functional performance of a novel, self-positioning balloon expandable transcatheter biological aortic valve system in the ovine aortic banding model
Background: The aim of the study was to evaluate bio-functionality of a novel, proprietary balloon-expandable biological transcatheter aortic valve implantation (TAVI) system (InFlow, CardValve Consortium, Poland) in an ovine model of aortic banding.
Methods: Surgical ascending aorta banding was created in 21 sheep. Two weeks later, 18 biological valves were implanted within the model using 15–16 F InFlow TAVI systems and carotid cut-down approach. Follow-up transthoracic echocardiography was performed at 30, 90, and 180-day. At designated time, animals were euthanized and valves harvested for analysis.
Results: All sheep survived the banding procedure. There were 4 (22%) procedure related deaths within a 7-day period. During the observation an additional 2 sheep died. In one, the valve dislocated after the procedure — the animal was excluded. Two animals completed 30-day follow up, five 90-day follow-up and four terminal follow-up of 180 days. Valves examined via transesophageal echocardiography showed proper hemodynamic parameters without evidence of structural valve deterioration. The maximum and average flow gradients at 180 days were 31.4 (23.3–37.7) and 17.5 (13.1–20.2) mmHg, respectively. There was one case of moderate insufficiency and no case of perivalvular leaks. By histopathology, there were no inflammation, thrombosis, nor calcifications in any tested valves at long-term follow-up. Neointimal coverage of stent struts increased with time from basal part in “early” groups to nearly 3/4 of stent length in the 180-day group. The pannus tissue showed maturation that increased with time with no stenotic “collar” visible in orthotopically implanted valves.
Conclusions: The study showed good hemodynamic performance, durability and biocompatibility of the novel biological THV