Human Movement Recognition Based on the Stochastic Characterisation of Acceleration Data

Human activity recognition algorithms based on information obtained from wearable sensors are successfully applied in detecting many basic activities. Identified activities with time-stationary features are characterised inside a predefined temporal window by using different machine learning algorithms on extracted features from the measured data. Better accuracy, precision and recall levels could be achieved by combining the information from different sensors. However, detecting short and sporadic human movements, gestures and actions is still a challenging task. In this paper, a novel algorithm to detect human basic movements from wearable measured data is proposed and evaluated. The proposed algorithm is designed to minimise computational requirements while achieving acceptable accuracy levels based on characterising some particular points in the temporal series obtained from a single sensor. The underlying idea is that this algorithm would be implemented in the sensor device in order to pre-process the sensed data stream before sending the information to a central point combining the information from different sensors to improve accuracy levels. Intra- and inter-person validation is used for two particular cases: single step detection and fall detection and classification using a single tri-axial accelerometer. Relevant results for the above cases and pertinent conclusions are also presented

Sensor optimization in smart insoles for post-stroke gait asymmetries using total variation and L1 distances

By deploying pressure sensors on insoles, the forces exerted by the different parts of the foot when performing tasks standing up can be captured. The number and location of sensors to use are important factors in order to enhance the accuracy of parameters used in assessment while minimizing the cost of the device by reducing the number of deployed sensors. Selecting the best locations and the required number of sensors depends on the application and the features that we want to assess. In this paper, we present a computational process to select the optimal set of sensors to characterize gait asymmetries and plantar pressure patterns for stroke survivors based upon the total variation and L1 distances. The proposed mechanism is ecologically validated in a real environment with 14 stroke survivors and 14 control users. The number of sensors is reduced to 4, minimizing the cost of the device both for commercial users and companies and enhancing the cost to benefit ratio for its uptake from a national healthcare system. The results show that the sensors that better represent the gait asymmetries for healthy controls are the sensors under the big toe and midfoot and the sensors in the forefoot and midfoot for stroke survivors. The results also show that all four regions of the foot (toes, forefoot, midfoot, and heel) play an important role for plantar pressure pattern reconstruction for stroke survivors, while the heel and forefoot region are more prominent for healthy controls

Description of the vitis vinifera L. Phenotypic variability in eno-carpological traits by a Euro-Asiatic collaborative network among ampelographic collections

The grapevine intra-specific variability captured an increasing interest during the last decades, as demonstrated by the number of recently funded European projects focused on the grapevine biodiversity preservation. However, nowadays, crop plants are mainly characterized by genotyping methods. The present work summarizes the phenotype data collected among 20 ampelographic collections spread over 15 countries, covering most of the viticultural areas in the Euro-Asiatic region: from Portugal to Armenia and from Cyprus to Luxembourg. Together with agro-climatic characterization of the experimental site, over two years about 2,400 accessions were described. A common experimental protocol mainly focused on the carpological and oe-nological traits was followed, obtaining a general overview of the distribution of the considered phenotypic traits in the cultivated Vitis vinifera species. The most replicated cultivars were selected and, for the subset of these reference cultivars, their behavior in the different environmental conditions over sites and years was described by ANOVA methods

Grape varieties (Vitis vinifera L.) from the Balearic Islands: genetic characterization and relationship with Iberian Peninsula and Mediterranean Basin

International audienceAmpelographic descriptions, a set of 20 nuclear microsatellite loci (nuSSR), five chloroplast microsatellites (cSSR), as well as historical references have been used to identify 66 accessions of Vitis vinifera L. The plant material included major and minor varieties under risk of extinction, collected in the Balearic Islands, and now conserved in two germplasm repositories site in Spain. The 66 samples analyzed corresponded to 32 different genotypes, several unique genotypes were found, three of them remaining unknown. Some synonyms and homonyms were found in the Mediterranean basin, highlighting that the dispersal of some varieties are related with historical human movements and migrations occurred in three several periods, (1) around seventh century related to Islam expansion, (2) around thirteen to fifteenth centuries and (3) in the nineteenth century related to phylloxera crisis. Some parentages were identified, being the cultivar Callet Cas Concos a key variety in several crosses, confirming the high value of unknown varieties for parentage analysis. Several grouping methods confirm the existence of two gene pools

Do optional activities matter in virtual learning environments?

Virtual Learning Environments (VLEs) provide studentts with activities to improve their learning (e.g., reading texts, watching videos or solving exercises). But VLEs usually also provide optional activities (e.g., changing an avatar profile or setting goals). Some of these have a connection with the learning process, but are not directly devoted to learning concepts (e.g., setting goals). Few works have dealt with the use of optional activities and the relationships between these activities and other metrics in VLEs. This paper analyzes the use of optional activities at different levels in a specific case study with 291 students from three courses (physics, chemistry and mathematics) using the Khan Academy platform. The level of use of the different types of optional activities is analyzed and compared to that of learning activities. In addition, the relationship between the usage of optional activities and different student behaviors and learning metrics is presented