1,720,989 research outputs found
Gait partitioning methods: a systematic review
Full text linkIn the last years, gait phase partitioning has come to be a challenging research topic due to its impact on several applications related to gait technologies. A variety of sensors can be used to feed algorithms for gait phase partitioning, mainly classifiable as wearable or non-wearable. Among wearable sensors, footswitches or foot pressure insoles are generally considered as the gold standard; however, to overcome some inherent limitations of the former, inertial measurement units have become popular in recent decades. Valuable results have been achieved also though electromyography, electroneurography, and ultrasonic sensors. Non-wearable sensors, such as opto-electronic systems along with force platforms, remain the most accurate system to perform gait analysis in an indoor environment. In the present paper we identify, select, and categorize the available methodologies for gait phase detection, analyzing advantages and disadvantages of each solution. Finally, we comparatively examine the obtainable gait phase granularities, the usable computational methodologies and the optimal sensor placements on the targeted body segments
A HMM distributed classifier to control robotic knee module of an active orthosis
No full textThe aim of this work is the evaluation of Distributed Classifier for the detection of gait phases that can be implemented in an active knee orthosis for the recovery of locomotion of pediatric subjects with neurological diseases, such as Cerebral Palsy (CP). The classifier is based on a Hierarchical Weighted Decision applied to the outputs of two or more scalar Hidden Markov Models (HMMs) trained by linear accelerations and angular velocities measured at shank and thigh. The kinematics of the dominant lower limb of ten healthy subjects were acquired by means of linear accelerometers and gyroscopes embedded in two inertial sensors. The actual sequence of gait phases was captured by means of foot switches. The experimental procedure consisted in one walking task, repeated for three times, on a treadmill at the preferred velocity of each subject. We compared the performance, in terms of sensitivity and specificity, of both Scalar Classifiers (SCs) and Distributed Classifiers (DCs) based on all the combinations of sagittal acceleration and sagittal angular velocity of the two body segments. The DC based on the angular velocities showed the highest values of sensitivity and specificity. The SC based on the angular velocity of shank was the better among others SCs, but the values of sensitivity and specificity are lower than 0.95. When we use only one sensor, placed on shank or thigh, the DC based on kinematic variables of shank showed better results, but not higher than 0.95. Consequently, the additional information provided by linear acceleration did not improve the performance and then, the gait-phase detection algorithm, which can be implemented in an active knee orthosis, has to be based on the output of two gyroscopes placed on shank and thigh. © 2015 IEEE
Realization and validation of a piezoresistive textile-based insole for gait-related measurements
No full textThe measurement of gait-related parameters is required in several application fields, such as experimental biomechanics and robotics. To enhance the wearability, smart textile-based sensors are always more widespread. In this context, we proposed an innovative insoles sensorized with piezoresistive textile able to gather information related to gait phase duration and center of pressure. An experimental protocol involved five healthy people was carried out to validate the gait-related measurements by using two force platforms as reference system. A total of 80 strides has been used for the validation procedure. The on/ off status of the piezoresistive sensors placed on toe and heel has been analyzed by applying a threshold-based procedure in order to compute the duration of the stride, as well the stance and swing phase. As for the center of pressure (CoP), the sensor outputs were post-processed to carry put the displacement of the CoP during the stride. The absolute error (AE) and the median absolute error (MAE) have been computed to evaluate the accuracy of the insole to measure the gait events and the gait phase duration in comparison of force platform outputs. Moreover, the correlation between the CoP displacements computed through the two sensor systems was computed, as well the root mean square error (RMSE). The gait phase duration was associated with a MAE lower than 0.05 s both considering the stance and the swing; vice versa a MAE up to 0.16 s was found for the identification of the events. Considering the CoP, the average correlation coefficient was found equal to 0.92; with a RMSE up to 3.2 cm. These findings allow us to assess the ability of the realized insole in the measurement of the gait phases duration; whereas the CoP measurement should be considered viable only if it is sufficient to know the trend of the displacement rather than the accurate value. Considering the achievement, such insole could be used for robotic application when seeking to develop control system for lower limb exoskeleton
Validation of inter-subject training for hidden markov models applied to gait phase detection in children with Cerebral Palsy
Full text linkGait-phase recognition is a necessary functionality to drive robotic rehabilitation devices for lower limbs. Hidden Markov Models (HMMs) represent a viable solution, but they need subject-specific training, making data processing very time-consuming. Here, we validated an inter-subject procedure to avoid the intra-subject one in two, four and six gait-phase models in pediatric subjects. The inter-subject procedure consists in the identification of a standardized parameter set to adapt the model to measurements. We tested the inter-subject procedure both on scalar and distributed classifiers. Ten healthy children and ten hemiplegic children, each equipped with two Inertial Measurement Units placed on shank and foot, were recruited. The sagittal component of angular velocity was recorded by gyroscopes while subjects performed four walking trials on a treadmill. The goodness of classifiers was evaluated with the Receiver Operating Characteristic. The results provided a goodness from good to optimum for all examined classifiers (0 < G < 0.6), with the best performance for the distributed classifier in two-phase recognition (G = 0.02). Differences were found among gait partitioning models, while no differences were found between training procedures with the exception of the shank classifier. Our results raise the possibility of avoiding subject-specific training in HMM for gait-phase recognition and its implementation to control exoskeletons for the pediatric population
Sensor-Based Indices for the Prediction and Monitoring of Anterior Cruciate Ligament Injury. Reliability Analysis and a Case Study in Basketball
Full text linkThe possibility of measuring predictive factors to discriminate athletes at higher risk of anterior cruciate ligament (ACL) injury still represents an open research question. We performed an observational study with thirteen female basketball players who performed monopodalic jumps and single-leg squat tests. One of them suffered from an ACL injury after the first test session. Data gathered from twelve participants, who did not suffer from ACL injury, were used for a reliability analysis. Parameters related to leg stability, load absorption capability and leg mobility showed good-to-excellent reliability. Path length, root mean square of the acceleration and leg angle with respect to the vertical axis revealed themselves as possible predictive factors to identify athletes at higher risk. Results confirm that six months after reconstruction represents the correct time for these athletes to return to playing. Furthermore, the training of leg mobility and load absorption capability could allow athletes to reduce the probability of new injuries
Investigating issues and needs of dyslexic students at university: proof of concept of an artificial intelligence and virtual reality-based supporting platform and preliminary results
No full textSpecific learning disorders affect a significant portion of the population. A total of 80% of its instances are dyslexia, which causes significant difficulties in learning skills related to reading, memorizing and the exposition of concepts. Whereas great efforts have been made to diagnose dyslexia and to mitigate its effects at primary and secondary school, little has been done at the university level. This has resulted in a sensibly high rate of abandonment or even of failures to enroll. The VRAIlexia project was created to face this problem by creating and popularizing an innovative method of teaching that is inclusive for dyslexic students. The core of the project is BESPECIAL, a software platform based on artificial intelligence and virtual reality that is capable of understanding the main issues experienced by dyslexic students and to provide them with ad hoc digital support methodologies in order to ease the difficulties they face in their academic studies. The aim of this paper is to present the conceptual design of BESPECIAL, highlighting the role of each module that composes it and the potential of the whole platform to fulfil the aims of VRAIlexia. Preliminary results obtained from a sample of about 700 dyslexic students are also reported, which clearly show the main issues and needs that dyslexic students experience and these will be used as guidelines for the final implementation of BESPECIAL
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Feasibility of Muscle Synergy Outcomes in Clinics, Robotics, and Sports: A Systematic Review
Full text linkIn the last years, several studies have been focused on understanding how the central nervous system controls muscles to perform a specific motor task. Although it still remains an open question, muscle synergies have come to be an appealing theory to explain the modular organization of the central nervous system. Even though the neural encoding of muscle synergies remains controversial, a large number of papers demonstrated that muscle synergies are robust across different tested conditions, which are within a day, between days, within a single subject, and between subjects that have similar demographic characteristics. Thus, muscle synergy theory has been largely used in several research fields, such as clinics, robotics, and sports. The present systematical review aims at providing an overview on the applications of muscle synergy theory in clinics, robotics, and sports; in particular, the review is focused on the papers that provide tangible information for (i) diagnosis or pathology assessment in clinics, (ii) robot-control design in robotics, and (iii) athletes’ performance assessment or training guidelines in sports
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
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