209 research outputs found

    System (for) Tracking Equilibrium and Determining Incline (STEADI)

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    The goal of this project was to design and implement a smartphone-based wearable system to detect fall events in real time. It has the acronym STEADI. Rather than have expensive customised hardware STEADI was implemented in a cost effective manner using a generic mobile computing device. In order to detect the fall event, we propose a fall detector that uses the accelerometer available in a mobile phone. As for detecting a fall we mainly divide the system in two sections, the signal processing and classification. For the processing both a median filter and a high pass filter are used. A Median filter is used to amplify/enhance the signal by removing impulsive noise while preserving the signal shape while the High pass filter is used to emphasise transitions in the signal. Then, in order to recognize a fall event, our STEADI system implements two methods that are a simple threshold analysis to determine whether or not a fall has occurred (threshold-based) and a more sophisticated NaĂŻve-Bayes classification method to differentiate falling from other mobile activities. Our experimental results show that by applying the signal processing and NaĂŻve-Bayes classification together increases the accuracy by more than 20% compared with using the threshold-based method alone. The NaĂŻve-Bayes achieved a detection accuracy of 95% in overall. Furthermore, an external sensor is introduced in order to enhance its accuracy. In addition to the fall detection, the systems can also provide location information using Google Maps as to the whereabouts of the fall event using the available GPS on the smartphone and sends the message to the caretaker via an SMS

    System (for) Tracking Equilibrium and Determining Incline (STEADI)

    Get PDF
    The goal of this project was to design and implement a smartphone-based wearable system to detect fall events in real time. It has the acronym STEADI. Rather than have expensive customised hardware STEADI was implemented in a cost effective manner using a generic mobile computing device. In order to detect the fall event, we propose a fall detector that uses the accelerometer available in a mobile phone. As for detecting a fall we mainly divide the system in two sections, the signal processing and classification. For the processing both a median filter and a high pass filter are used. A Median filter is used to amplify/enhance the signal by removing impulsive noise while preserving the signal shape while the High pass filter is used to emphasise transitions in the signal. Then, in order to recognize a fall event, our STEADI system implements two methods that are a simple threshold analysis to determine whether or not a fall has occurred (threshold-based) and a more sophisticated NaĂŻve-Bayes classification method to differentiate falling from other mobile activities. Our experimental results show that by applying the signal processing and NaĂŻve-Bayes classification together increases the accuracy by more than 20% compared with using the threshold-based method alone. The NaĂŻve-Bayes achieved a detection accuracy of 95% in overall. Furthermore, an external sensor is introduced in order to enhance its accuracy. In addition to the fall detection, the systems can also provide location information using Google Maps as to the whereabouts of the fall event using the available GPS on the smartphone and sends the message to the caretaker via an SMS

    Analyzing human gait and posture by combining feature selection and kernel methods

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    This paper evaluates a set of computational algorithms for the automatic estimation of human postures and gait properties from signals provided by an inertial body sensor. The use of a single sensor device imposes limitations for the automatic estimation of relevant properties, like step length and gait velocity, as well as for the detection of standard postures like sitting or standing. Moreover, the exact location and orientation of the sensor is also a common restriction that is relaxed in this study. Based on accelerations provided by a sensor, known as the `9 2', three approaches are presented extracting kinematic information from the user motion and posture. Firstly, a two-phases procedure implementing feature extraction and Support Vector Machine based classi cation for daily living activity monitoring is presented. Secondly, Support Vector Regression is applied on heuristically extracted features for the automatic computation of spatiotemporal properties during gait. Finally, sensor information is interpreted as an observation of a particular trajectory of the human gait dynamical system, from which a reconstruction space is obtained, and then transformed using standard principal components analysis, nally Support Vector Regression is used for prediction. Daily living Activities are detected and spatiotemporal parameters of human gait are estimated using methods sharing a common structure based on feature extraction and kernel methods. The approaches presented are susceptible to be used for medical purposes.Peer ReviewedPreprin

    DESIGN OF A GAIT ACQUISITION AND ANALYSIS SYSTEM FOR ASSESSING THE RECOVERY OF MICE POST-SPINAL CORD INJURY

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    Current methods of determining spinal cord recovery in mice, post-directed injury, are qualitative measures. This is due to the small size and quickness of mice. This thesis presents a design for a gait acquisition and analysis system able to capture the footfalls of a mouse, extract position and timing data, and report quantitative gait metrics to the operator. These metrics can then be used to evaluate the recovery of the mouse. This work presents the design evolution of the system, from initial sensor design concepts through prototyping and testing to the final implementation. The system utilizes a machine vision camera, a well-designed walkway enclosure, and image processing techniques to capture and analyze paw strikes. Quantitative results gained from live animal experiments are presented, and it is shown how the measurements can be used to determine healthy, injured, and recovered gait

    Investigating the Effectiveness of a Haptic Feedback System to Improve the Gait Speed of Older Adults in Overground Walking

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    While the use of tactile feedback for modifying gait has recently shown promising results in a number of research studies, there has been little attention given to its ability to effect change in the gait of older adults nor has the effect of the frequency of this feedback been examined. Given the important associations of walking speed with the health of older adults, the goal of this study was to determine if a recently developed haptic feedback system could increase the walking speed of older adults and whether the frequency at which this feedback was provided would have an impact on the results. In order to achieve a faster walking speed, peak thigh extension was selected as a biomechanical surrogate for stride length with vibrotactile haptic feedback being provided to the thighs to increase that parameter and, consequently, increase speed. Further, the influence of the frequency of the feedback on several other gait parameters was also investigated. Ten healthy older adults (68.4 ± 4.1 years) were recruited for this study, in which their peak thigh extension, cadence, normalized stride length, and normalized stride velocity, as well as their coefficients of variation (COV), were compared among six different experimental conditions. The study’s findings demonstrated that when compared to their pretest values, older people using the haptic feedback device had considerably longer peak thigh extensions during both post-tests and feedback walking conditions. The longer stride length made possible by this more extended thigh angle allowed for a corresponding rise in walking velocity. Surprisingly, none of the gait metrics examined were substantially impacted by the feedback’s frequency. In other words, regardless of how frequently the input was given, the haptic feedback device was successful in improving elderly people’s walking abilities. These results indicate the haptic feedback device has the potential to enhance gait speed, stride length, and stride velocity, which are essential elements involved with keeping independence and mobility in older people

    Recommendations for determining the validity of consumer wearable and smartphone step count: expert statement and checklist of the INTERLIVE network

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    PBJ is supported by the Portuguese Foundation for Science and Technology (SFRH/BPD/115977/2016). WJ is partly funded by Science Foundation Ireland (12/RC/2289_P2). PMG and FBO are supported by grants from the MINECO/FEDER (DEP2016-79512-R) and from the University of Granada, Plan Propio de Investigacion 2016, Excellence actions: Units of Excellence; Scientific Excellence Unit on Exercise and Health (UCEES); Junta de Andalucia, Consejeria de Conocimiento, Investigacion y Universidades and European Regional Development Funds (ref. SOMM17/6107/UGR). JMM is partly funded by Private Stiftung Ewald Marquardt fur Wissenschaft und Technik, Kunst und Kultur. UE and JS are partly funded by the Research Council of Norway (249932/F20). AG is supported a European Research Council Grant (grant number 716657). ELS is supported by TrygFonden (grant number 310081). This research was partly funded by Huawei Technologies, Finland.Consumer wearable and smartphone devices provide an accessible means to objectively measure physical activity (PA) through step counts. With the increasing proliferation of this technology, consumers, practitioners and researchers are interested in leveraging these devices as a means to track and facilitate PA behavioural change. However, while the acceptance of these devices is increasing, the validity of many consumer devices have not been rigorously and transparently evaluated. The Towards Intelligent Health and Well-Being Network of Physical Activity Assessment (INTERLIVE) is a joint European initiative of six universities and one industrial partner. The consortium was founded in 2019 and strives to develop best-practice recommendations for evaluating the validity of consumer wearables and smartphones. This expert statement presents a best-practice consumer wearable and smartphone step counter validation protocol. A two-step process was used to aggregate data and form a scientific foundation for the development of an optimal and feasible validation protocol: (1) a systematic literature review and (2) additional searches of the wider literature pertaining to factors that may introduce bias during the validation of these devices. The systematic literature review process identified 2897 potential articles, with 85 articles deemed eligible for the final dataset. From the synthesised data, we identified a set of six key domains to be considered during design and reporting of validation studies: target population, criterion measure, index measure, validation conditions, data processing and statistical analysis. Based on these six domains, a set of key variables of interest were identified and a 'basic' and 'advanced' multistage protocol for the validation of consumer wearable and smartphone step counters was developed. The INTERLIVE consortium recommends that the proposed protocol is used when considering the validation of any consumer wearable or smartphone step counter. Checklists have been provided to guide validation protocol development and reporting. The network also provide guidance for future research activities, highlighting the imminent need for the development of feasible alternative 'gold-standard' criterion measures for free-living validation. Adherence to these validation and reporting standards will help ensure methodological and reporting consistency, facilitating comparison between consumer devices. Ultimately, this will ensure that as these devices are integrated into standard medical care, consumers, practitioners, industry and researchers can use this technology safely and to its full potential.Portuguese Foundation for Science and Technology SFRH/BPD/115977/2016Science Foundation IrelandEuropean Commission 12/RC/2289_P2MINECO/FEDER DEP2016-79512-RUniversity of Granada, Plan Propio de Investigacion 2016, Excellence actions: Units of ExcellenceScientific Excellence Unit on Exercise and Health (UCEES)European Commission SOMM17/6107/UGRPrivate Stiftung Ewald Marquardt fur Wissenschaft und Technik, Kunst und KulturResearch Council of Norway 249932/F20European Research Council (ERC) European Commission 716657TrygFonden 310081Huawei TechnologiesJunta de Andaluci

    Toward Flexibility in Sensor Placement for Motion Capture Systems: A Signal Processing Approach

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    Cannot archive published version. Post-Print only. http://www.sherpa.ac.uk/romeo/issn/1530-437X/ Author contacted 21/02/14

    Towards understanding the functionality of foot orthosis based on foot structure and function

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    The raw data related to the second study of this thesis (Chapter 3) is available online in the section of supporting information at https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0232677. These files present the following data: S1 File. The pattern of foot orthosis depression/reformation for healthy subjects during walking with sport versus regular foot orthosis. S2 File. Raw data for the training session of sport foot orthosis. This Excel file consists three sheets in which the position of triad markers, the orientation of triad markers and the position of markers on plantar surface of foot orthosis are provided respectively. S3 File. Raw data for walking with sport foot orthosis. This Excel file consists two sheets in which the position of triad markers and the orientation of triad markers are provided respectively for subject 1. S4 File. The results of each participant during walking with sport foot orthosis. This .mat file includes “DispEachPoint” and “DispEachPointMean” which shows the displacement of each predicted marker on foot orthosis plantar surface during stance phase of walking relative to its corresponding position in static non weight-bearing for each trial and the average of trials respectively. In addition, “loc_stance” and “loc_meanstance” show the location of each predicted marker during stance phase of walking. “peaks” and “peaksMean” represent the minimum (depression) and maximum (reformation) value of displacement during walking S5 File. The results of each participant during walking with regular foot orthosis. This .mat file includes “DispEachPoint” and “DispEachPointMean” which shows the displacement of each predicted marker on foot orthosis plantar surface during stance phase of walking relative to its corresponding position in static non weight-bearing for each trial and the average of trials respectively. In addition, “loc_stance” and “loc_meanstance” show the location of each predicted marker during stance phase of walking. “peaks” and “peaksMean” represent the minimum (depression) and maximum (reformation) value of displacement during walkingLes orthèses plantaires (OP) sont des dispositifs médicaux fréquemment utilisés pour réduire les douleurs et blessures de surutilisation, notamment chez les personnes ayant les pieds plats. Le port d'OP permettrait de corriger les altérations biomécaniques attribuées à la déformation du pied plat, que sont la perte de l’arche longitudinale médiale et la pronation excessive du pied. Cependant, le manque de compréhension de la fonction des OP entraine une grande variabilité des OP prescrites en milieu clinique. L'objectif de cette thèse est d'approfondir les connaissances sur l’effet des OP sur la biomécanique, de quantifier les déformations des OP à la marche et de mettre en relation ces déformations avec la biomécanique du pied. La première étude a évalué la manière dont les différentes conceptions d'OP imposent des modifications dans le mouvement et le chargement appliqué sur le pied. Cet objectif a été atteint grâce à une revue systématique traitant des effets des OP sur la cinématique et la cinétique du membre inférieur pendant la marche chez des personnes ayant des pieds normaux. Les critères d'inclusion ont réduit les études à celles qui ont fait état des résultats pour les géométries les plus fréquentes des OP, à savoir les biseaux, les supports d’arche et les stabilisateurs de talon. La revue a mis en évidence que les orthèses avec un biseau médial peuvent réduire le moment d'éversion de la cheville. Aucune évidence significative n'a été trouvée dans notre méta-analyse sur l'efficacité des orthèses incluant des supports d’arche ou des stabilisateurs de talon. Les différents procédés et matériaux utilisés dans la conception des OP ainsi que les caractéristiques des pieds des participants pourraient expliquer la variabilité retrouvée au regard des effets des OP sur la biomécanique. La deuxième étude a apporté des informations précieuses et inédites sur le comportement dynamique des OP à la marche. La cinématique du contour des OP a été utilisée pour prédire la déformation de leur surface plantaire pendant la marche chez 13 individus ayant des pieds normaux en utilisant un réseau de neurones artificiels. Une erreur moyenne inférieure à 0,6 mm a été obtenue pour nos prédictions. En plus de la précision des prédictions, le modèle a été capable de différencier le patron de déformations pour deux OP de rigidités différentes et entre les participants inclus dans l’étude. Enfin, dans une troisième étude, nous avons identifié la relation entre la déformation des OP personnalisées et la biomécanique du pied à la marche chez 17 personnes avec des pieds plats. L'utilisation de modèles linéaires mixtes a permis d’exprimer les variations de la déformation des OP dans différentes régions en fonction des variables cinématiques du pied et de pressions plantaires. Cette étude a montré que l'interaction pied-OP varie selon les différentes régions de l’OP et les différentes phases du cycle de marche. Ainsi, des lignes directrices préliminaires ont été fournies afin de standardiser et optimiser la conception des OP. Dans l'ensemble, les résultats de cette thèse justifient l'importance d’'intégrer des caractéristiques dynamiques du pied de chaque individu dans la conception d'OP personnalisées. Des études futures pourraient étendre les modèles de prédiction de l'interaction pied-OP en incluant d'autres paramètres biomécaniques tels que les moments articulaires, les activations musculaires et la morphologie du pied. De tels modèles pourraient être utilisés pour développer des fonctions coût pour l'optimisation de la conception des OP par une approche itérative utilisant la simulation par les éléments finis.Foot orthoses (FOs) are frequently used medical devices to manage overuse injuries and pain in flatfoot individuals. Wearing FOs can result in improving the biomechanical alterations attributed to flatfoot deformity such as the loss of medial longitudinal arch and excessive foot pronation. However, a lack of a clear understanding of the function of FOs contributes to the highly variable FOs prescribed in clinical practice. The objective of this thesis was to deepen the knowledge about the biomechanical outcomes of FOs and to formulate the dynamic behaviour of FOs as a function of foot biomechanics during gait. The primary study investigated how different designs of FOs impose alterations in foot motion and loading. This objective was achieved through a systematic review of all literature reporting the kinematics and kinetics of the lower body during walking with FOs in healthy individuals. The inclusion criteria narrowed the studies to the ones which reported the outcomes for common designs of FOs, namely posting, arch support, and heel support. The review identified some evidence that FOs with medial posting can decrease ankle eversion moment. No significant evidence was found in our meta-analysis for the efficiency of arch supported and heel supported FOs. The findings of this study revealed that differences in FO design and material as well as foot characteristics of participants could explain the variations in biomechanical outcomes of FOs. The second study provided valuable information on the dynamic behaviour of customized FOs. The kinematics of FO contour was used to predict the deformation of FO plantar surface in 13 healthy individuals during walking using an artificial intelligence approach. An average error below 0.6 mm was achieved for our predictions. In addition to the prediction accuracy, the model was capable to differentiate between different rigidities of FOs and between included participants in terms of range and pattern of deformation. Finally, the third study identified the relationship between the deformation of customized FOs and foot biomechanics in 17 flatfoot individuals during walking. The use of linear mixed models made it possible to identify the variables of foot kinematics and region-dependent plantar pressure that could explain the variations in FO deformation. This study showed that the foot-FO interaction changes over different regions of FO and different phases of gait cycle. In addition, some preliminary guidelines were provided to standardize and optimize the design of FOs. Overall, the results of this thesis justify the importance of incorporating the dynamic characteristics of each individual’s foot into the design of customized FOs. Future studies can extend the predictive models for foot-FO interactions by including other determinants of foot biomechanics such as joint moments, muscle activation, and foot morphology. Based on such extended models, the cost functions could be devised for optimizing the designs of customized 3D printed FOs through an iterative approach using finite element modeling
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