Automatic learning of gait signatures for people identification

This work targets people identification in video based on the way they walk (i.e. gait). While classical methods typically derive gait signatures from sequences of binary silhouettes, in this work we explore the use of convolutional neural networks (CNN) for learning high-level descriptors from low-level motion features (i.e. optical flow components). We carry out a thorough experimental evaluation of the proposed CNN architecture on the challenging TUM-GAID dataset. The experimental results indicate that using spatio-temporal cuboids of optical flow as input data for CNN allows to obtain state-of-the-art results on the gait task with an image resolution eight times lower than the previously reported results (i.e. 80x60 pixels).Comment: Proof of concept paper. Technical report on the use of ConvNets (CNN) for gait recognition. Data and code: http://www.uco.es/~in1majim/research/cnngaitof.htm

Applying the Minimal Detectable Change of a Static and Dynamic Balance Test Using a Portable Stabilometric Platform to Individually Assess Patients with Balance Disorders

Balance disorders have a high prevalence among elderly people in developed countries, and falls resulting from balance disorders involve high healthcare costs. Therefore, tools and indicators are necessary to assess the response to treatments. Therefore, the aim of this study is to detect relevant changes through minimal detectable change (MDC) values in patients with balance disorders, specifically with vertigo. A test-retest of a static and dynamic balance test was conducted on 34 healthy young volunteer subjects using a portable stabilometric platform. Afterwards, in order to show the MDC applicability, eight patients diagnosed with balance disorders characterized by vertigo of vestibular origin performed the balance test before and after a treatment, contrasting the results with the assessment by a specialist physician. The balance test consisted of four tasks from the Romberg test for static balance control, assessing dynamic postural balance through the limits of stability (LOS). The results obtained in the test-retest show the reproducibility of the system as being similar to or better than those found in the literature. Regarding the static balance variables with the lowest MDC value, we highlight the average velocity of the center of pressure (COP) in all tasks and the root mean square (RMS), the area, and the mediolateral displacement in soft surface, with eyes closed. In LOS, all COP limits and the average speed of the COP and RMS were highlighted. Of the eight patients assessed, an agreement between the specialist physician and the balance test results exists in six of them, and for two of the patients, the specialist physician reported no progression, whereas the balance test showed worsening. Patients showed changes that exceeded the MDC values, and these changes were correlated with the results reported by the specialist physician. We conclude that (at least for these eight patients) certain variables were sufficiently sensitive to detect changes linked to balance progression. This is intended to improve decision making and individualized patient monitoring

Applying machine learning for healthcare: A case study on cervical pain assessment with motion capture

Given the exponential availability of data in health centers and the massive sensorization that is expected, there is an increasing need to manage and analyze these data in an effective way. For this purpose, data mining (DM) and machine learning (ML) techniques would be helpful. However, due to the specific characteristics of the field of healthcare, a suitable DM and ML methodology adapted to these particularities is required. The applied methodology must structure the different stages needed for data-driven healthcare, from the acquisition of raw data to decision-making by clinicians, considering the specific requirements of this field. In this paper, we focus on a case study of cervical assessment, where the goal is to predict the potential presence of cervical pain in patients affected with whiplash diseases, which is important for example in insurance-related investigations. By analyzing in detail this case study in a real scenario, we show how taking care of those particularities enables the generation of reliable predictive models in the field of healthcare. Using a database of 302 samples, we have generated several predictive models, including logistic regression, support vector machines, k-nearest neighbors, gradient boosting, decision trees, random forest, and neural network algorithms. The results show that it is possible to reliably predict the presence of cervical pain (accuracy, precision, and recall above 90%). We expect that the procedure proposed to apply ML techniques in the field of healthcare will help technologists, researchers, and clinicians to create more objective systems that provide support to objectify the diagnosis, improve test treatment efficacy, and save resources

Efficient Transport Protocol for Networked Haptics Applications

The performance of haptic application is highly sensitive to communication delays and losses of data. It implies several constraints in developing networked haptic applications. This paper describes a new internet protocol called Efficient Transport Protocol (ETP), which aims at developing distributed interactive applications. TCP and UDP are transport protocols commonly used in any kind of networked communication, but they are not focused on real time application. This new protocol is focused on reducing roundtrip time (RTT) and inter packet gap (IPG). ETP is, therefore, optimized for interactive applications which are based on processes that are continuously exchanging data.ETP protocol is based on a state machine that decides the best strategies for optimizing RTT and IPG. Experiments have been carried out in order to compare this new protocol and UDP

Is my patient improving? Individualized gait analysis in rehabilitation

In the rehabilitation field, clinicians are continually struggling to assess improvements in patients following interventions. In this paper, we propose an approach to use gait analysis based on inertial motion capture (MoCap) to monitor individuals during rehabilitation. Gait is a cyclical movement that generates a sufficiently large data sample in each capture session to statistically compare two different sessions from a single patient. Using this crucial idea, 21 heterogeneous patients with hemiplegic spasticity were assessed using gait analysis before and after receiving treatment with botulinum toxin injections. Afterwards, the two sessions for each patient were compared using the magnitude-based decision statistical method. Due to the challenge of classifying changes in gait variables such as improvements or impairments, assessing each patient’s progress required an interpretative process. After completing this process, we determined that 10 patients showed overall improvement, five patients showed overall impairment, and six patients did not show any overall change. Finally, the interpretation process was summarized by developing guidelines to aid in future assessments. In this manner, our approach provides graphical information about the patients’ progress to assess improvement following intervention and to support decision-making. This research contributes to integrating MoCap-based gait analysis into rehabilitation

Association between Caries, Obesity and Insulin Resistance in Mexican Adolescents

Aim: To determine the association among dental caries, obesity and insulin resistance in Mexican adolescents. Methods: Body Mass Index, obesity (OB) blood pressure, insulin level, insulin resistance (IR), triglycerides level, serum HDL-cholesterol (cHDL), DMFT index and salivary flow were measured. Results: Anthropometric measures showed a significant statistical difference (p \u3c 0.05). Insulin level was 8.98 for healthy subjects, whereas for OB-IR group was 25.35, there was a statistical significant difference (p \u3c 0.05). Triglycerides level was 88.50 for healthy subjects and 169.40 mg/dL for OB-IR; cHDL was 52.88 for healthy and 41.82 mg/dL for OB-IR group, both showed a statistically significant difference (p \u3c 0.05). Salivary flow was 4.30 for healthy and for OB-IR group was 5.48 ml/min showed a significant statistical difference (p \u3c 0.05). DMFT index was 3.02 for healthy and for OB-IR adolescents was 4.78, showed a significant statistical difference (p \u3c 0.05). The caries component of DMFT index was 1.84 for healthy and was 3.52 for OB-IR adolescents, showed a significant statistical difference (p \u3c 0.05). According to the multivariate analysis, DMFT (OR=3.10; IC95%=0.20-1.02, p=0.042) and decay (OR=3.30; IC95%=0.19-1.0, p=0.011) were associated with subjects with OB-IR. Conclusion: OB-IR Mexican adolescents showed a positive association with DMFT

Three-dimensional hydrodynamic and sediment transport modeling to test the sediment focusing hypothesis in upland lakes

Palaeolimnological studies rely on assumptions regarding the distribution and completeness of lake deposits that are not always fully supported by observations. In particular, the assumption that “focusing” of suspended sediments leads to preferential deposition in the deepest part of a lake is not always justified, especially in upland lakes subject to energetic wind forcing. Few studies have investigated the hydrodynamic controls on lake sediment focusing, especially the importance of wind-driven currents in deep water. We combine a three-dimensional numerical hydrodynamic and suspended sediment model (FVCOM) with a semi-empirical wind wave model to investigate the potential mobility of bottom sediments in a small oligotrophic upland lake (Llyn Conwy, north Wales, UK). Exploratory simulations of wave- and current-generated bottom stress and suspended sediment dynamics confirm the expected importance of wave-generated bottom stresses in shallower waters (< 3 m depth) around the shore. Field survey shows that lake sediments are largely absent from this zone. This is consistent with peripheral wave action as a sediment focusing mechanism. In deeper water, wind-driven currents become the dominant contributor to bottom stress. Strong wind forcing events drive an energetic circulation with peak bottom stresses that intermittently exceed any realistic erosion threshold over a large proportion of the lake at depths far below those at which waves can be effective. The spatial distribution of lake sediments, and the completeness of the sediment record, is thus determined by a complex interaction between wind-driven circulation and bathymetry, rather than by bathymetry alone. Although our sediment dynamics simulations are purely exploratory, the results are consisted with survey results that show a patchy distribution of deep-water accumulation. Some implications of these results for the selection of sediment coring locations and the interpretation of sediment records are considered

A Decentralized Multi-Agent Coordination Method for Dynamic and Constrained Production Planning

[EN] In the capacitated production planning problem, quantities of products need to be determined at consecutive periods within a given time horizon when product demands, costs, and production capacities vary through time. We focus on a general formulation of this problem where each product is produced in one step and setup cost is paid at each period of production. Additionally, products can be anticipated or backordered in respect to the demand period. We propose a computationally efficient decentralized approach based on the spillover effect relating to the accumulation of production costs of each product demand through time. The performance of the spillover algorithm is compared against the state-of-the-art mixed integer programming branch-and-bound solver CPLEX 12.8 considering optimality gap and computational time.This work is supported by: the Spanish MINECO projects RTI2018-095390-B-C33 (MCIU/AEI/FEDER, UE) and TIN2017- 88476-C2-1-R, the French ADEME project E-Logistics, and an STSM Grant funded by the European ICT COST Action IC1406, cHiPSet.Lujak, M.; Fernandez, A.; Onaindia De La Rivaherrera, E. (2020). A Decentralized Multi-Agent Coordination Method for Dynamic and Constrained Production Planning. International Foundation for Autonomous Agents and Multiagent Systems. 1913-1915. http://hdl.handle.net/10251/179784S1913191

Acute-Stress Biomarkers in Three Octopodidae Species After Bottom Trawling

Several Octopodidae species have a great potential for the diversification of worldwide aquaculture. Unfortunately, the lack of stress-related biomarkers in this taxon results an obstacle for its maintenance in conditions where animal welfare is of paramount relevance. In this study, we made a first approach to uncover physiological responses related to fishing capture in Eledone moschata, Eledone cirrhosa, and Octopus vulgaris. Captured octopus from all three species were individually maintained in an aquaculture system onboard of oceanographic vessel in south-western waters of Europe. Haemolymph plasma and muscle were collected in animals at the moment of capture, and recovery was evaluated along a time-course of 48 h in Eledone spp., and 24 h for O. vulgaris. Survival rates of these species captured in spring and autumn were evaluated. Physiological parameters such as plasma pH, total CO2, peroxidase activity, lysozyme, hemocyanin, proteases, pro-phenoloxidase, anti-proteases, free amino acids, lactate and glucose levels, as well as muscle water percentage, free amino acids, lactate, glycogen and glucose values were analyzed. The immune system appears to be compromised in these species due to capture processes, while energy metabolites were mobilized to face the acute-stress situation, but recovery of all described parameters occurs within the first 24 h after capture. Moreover, this situation exerts hydric balance changes, as observed in the muscle water, being these responses depending on the species assessed. In conclusion, three Octopodidae species from south-western waters of Europe have been evaluated for stress-related biomarkers resulting in differentiated mechanisms between species. This study may pave the way to further study the physiology of stress in adult octopuses and develop new methodologies for their growth in aquaculture conditions