High reliability Android application for multidevice multimodal mobile data acquisition and annotation

We have completed the collection of one of the richest accurately annotated mobile dataset of modes of transportation and locomotion. To do this, we developed a highly reliable Android application called DataLogger capable of recording multisensor data from multiple synchronized smartphones simultaneously. The application allows real-time data annotation. We explain how we designed the app to achieve high reliability and ease of use. We also present an evaluation of the application in a big-data collection (750 hours, 950 GB of data, 17 different sensor modalities), analysing the data loss (less than 0.4‰) and battery consumption (≈6% on average per hour). The application is available as open source

The University of Sussex-Huawei locomotion and transportation dataset for multimodal analytics with mobile devices

Scientific advances build on reproducible research which need publicly available benchmark datasets. The computer vision and speech recognition communities have led the way in establishing benchmark datasets. There are much less datasets available in mobile computing, especially for rich locomotion and transportation analytics. This paper presents a highly versatile and precisely annotated large-scale dataset of smartphone sensor data for multimodal locomotion and transportation analytics of mobile users. The dataset comprises 7 months of measurements, collected from all sensors of 4 smartphones carried at typical body locations, including the images of a body-worn camera, while 3 participants used 8 different modes of transportation in the southeast of the United Kingdom, including in London. In total 28 context labels were annotated, including transportation mode, participant’s posture, inside/outside location, road conditions, traffic conditions, presence in tunnels, social interactions, and having meals. The total amount of collected data exceed 950 GB of sensor data, which corresponds to 2812 hours of labelled data and 17562 km of traveled distance. We present how we set up the data collection, including the equipment used and the experimental protocol. We discuss the dataset, including the data curation process, the analysis of the annotations and of the sensor data. We discuss the challenges encountered and present the lessons learned and some of the best practices we developed to ensure high quality data collection and annotation. We discuss the potential applications which can be developed using this large-scale dataset. In particular, we present how a machine-learning system can use this dataset to automatically recognize modes of transportations. Many other research questions related to transportation analytics, activity recognition, radio signal propagation and mobility modelling can be adressed through this dataset. The full dataset is being made available to the community, and a thorough preview is already publishe

Knowledge and Practice of Health Professionals in the Management of Dysphagia

Background: Dysphagia is associated with poor outcome in stroke patients. Studies investigating the association of dysphagia and early dysphagia screening (EDS) with outcomes in patients with acute ischemic stroke (AIS) are rare. The aims of our study are to investigate the association of dysphagia and EDS within 24 h with stroke-related pneumonia and outcomes. Methods: Over a 4.5-year period (starting November 2007), all consecutive AIS patients from 15 hospitals in Schleswig-Holstein, Germany, were prospectively evaluated. The primary outcomes were stroke-related pneumonia during hospitalization, mortality, and disability measured on the modified Rankin Scale >= 2-5, in which 2 indicates an independence/slight disability to 5 severe disability. Results: Of 12,276 patients (mean age 73 +/- 13; 49% women), 9,164 patients (74%) underwent dysphagia screening; of these patients, 55, 39, 4.7, and 1.5% of patients had been screened for dysphagia within 3, 3 to 72 h following admission. Patients who underwent dysphagia screening were likely to be older, more affected on the National Institutes of Health Stroke Scale score, and to have higher rates of neurological symptoms and risk factors than patients who were not screened. A total of 3,083 patients (25.1%; 95% CI 24.4-25.8) had dysphagia. The frequency of dysphagia was higher in patients who had undergone dysphagia screening than in those who had not (30 vs. 11.1%; p < 0.001). During hospitalization (mean 9 days), 1,271 patients (10.2%; 95% CI 9.7-10.8) suffered from stroke-related pneumonia. Patients with dysphagia had a higher rate of pneumonia than those without dysphagia (29.7 vs. 3.7%; p < 0.001). Logistic regression revealed that dysphagia was associated with increased risk of stroke-related pneumonia (OR 3.4; 95% CI 2.8-4.2; p < 0.001), case fatality during hospitalization (OR 2.8; 95% CI 2.1-3.7; p < 0.001) and disability at discharge (OR 2.0; 95% CI 1.6-2.3; p < 0.001). EDS within 24 h of admission appeared to be associated with decreased risk of stroke-related pneumonia (OR 0.68; 95% CI 0.52-0.89; p = 0.006) and disability at discharge (OR 0.60; 95% CI 0.46-0.77; p < 0.001). Furthermore, dysphagia was independently correlated with an increase in mortality (OR 3.2; 95% CI 2.4-4.2; p < 0.001) and disability (OR 2.3; 95% CI 1.8-3.0; p < 0.001) at 3 months after stroke. The rate of 3-month disability was lower in patients who had received EDS (52 vs. 40.7%; p = 0.003), albeit an association in the logistic regression was not found (OR 0.78; 95% CI 0.51-1.2; p = 0.2). Conclusions: Dysphagia exposes stroke patients to a higher risk of pneumonia, disability, and death, whereas an EDS seems to be associated with reduced risk of stroke-related pneumonia and disability. (C) 2016 S. Karger AG, Base

Age and Training-Related Changes on Body Composition and Fitness in Male Amateur Cyclists

Master athletes are considered as a model of healthy aging because they can limit the age-related decline of physiological abilities compared to sedentary individuals. The main objective of this study is to analyze age-related changes and annual training on body composition (BC) and cardiorespiratory fitness (CRF) parameters. The participants in this retrospective cross-sectional study were 176 male cyclists, aged 40–60 years. BC was evaluated through anthropometric measurements and CRF was determined by an incremental cycle ergometer test to exhaustion. A comparative study between age groups was carried out through a one-way ANOVA test and the associations between the variables were assessed by Spearman’s correlation coefficients and multiple regression analysis to estimate the performance. Training was generally associated with a decrease in both body weight and body fat (p 0.05). In the performance prediction model, the included variables explained 52% of the variance. In summary, the changes induced by age were minimal in BC and negligible in CRF, whereas HR decreased with age. Training load was generally associated with a decrease in body weight, BMI and body fat percentage that was particularly notable in the abdominal skin folds. A decrease in HRrest was observed as a vagal effect due to kilometers cycled per year, and age did not seem to have a significant effect. The annual cycling kilometers were associated with to high PPO that is greater in the M40 group and a non-significant upward trend in VO2max

Deep convolutional feature transfer across mobile activity recognition domains, sensor modalities and locations

Deep convolutional neural networks are powerful image and signal classifiers. One hypothesis is that kernels in the convolutional layers act as feature extractors, progressively highlighting more domain-specific features in upper layers of the network. Thus lower-level features might be suitable for transfer. We analyse this in wearable activity recognition by reusing kernels learned on a source domain on another target domain. We consider transfer between users, application domains, sensor modalities and sensor locations. We characterise the trade-offs of transferring various convolutional layers along model size, learning speed, recognition performance and training data. Through a novel kernel visualisation technique and comparative evaluations we identify what learned kernels are predominantly sensitive to, amongst sensor characteristics, motion dynamics and on-body placement. We demonstrate a ~17% decrease in training time at equal performance thanks to kernel transfer and we derive recommendations on when transfer is most suitable

Exploring human activity annotation using a privacy preserving 3D model

Annotating activity recognition datasets is a very time consuming process. Using lay annotators (e.g. using crowdsourcing) has been suggested to speed this up. However, this requires to preserve privacy of users and may preclude relying on video for annotation. We investigate to which extent using a 3D human model animated from the data of inertial sensors placed on the limbs allows for annotation of human activities. The animated model is shown to 6 people in a suite of tests in order to understand the accuracy of the labelling. We present the model and the dataset, then we present the experiments including the number of activities. We present 3 experiments where we investigate the use of a 3D model for i) activity segmentation, ii) for "openended" annotation where users freely describe the activity they see on screen, and iii) traditional annotation, where users pick one activity among a pre-defined list of activities. In the latter case, results show that users recognise with 56% accuracy when picking from 11 possible activities

Wearable beach volleyball serve type recognition

We present results on beach volleyball serve recognition and classification from a wrist-worn gyroscope deployed with semi-professional beach volleyball players. We trained a template-based recognition system based on a Warping Longest Common Subsequence algorithm to spot serves, and potentially distinguish among 4 common serve types. This shows the potential of wearable technologies in beach volleyball, which could offer precise sport analytics

Valor pronóstico de la bioimpedancia eléctrica medida con el dispositivo IVOL en la insuficiencia cardiaca aguda

Introducción y objetivos: La evaluación actual de la insuficiencia cardiaca (IC) aguda no permite predecir adecuadamente su evolución. La bioimpedancia eléctrica (BI) permite conocer el estado de volemia, hasta ahora solo con equipos fijos. Hemos desarrollado y validado un dispositivo portátil e inalámbrico para medir la BI en el tobillo (IVOL). El objetivo del estudio es conocer el valor pronóstico a largo plazo de la medición puntual de la BI con IVOL en pacientes con IC aguda. Métodos: Estudio de cohorte prospectivo de pacientes no seleccionados ingresados por IC aguda en un hospital de tercer nivel. Se analizó la asociación entre la BI y diferentes variables (clínicas, analíticas y ecocardiográficos) al ingreso y evolución clínica. Resultados: Se incluyeron 76 pacientes (edad media 66,1 anos, ˜ 71,1% varones, 68,4% hipertensos, 34,2% diabéticos, NT-ProBNP medio: 7.103 pg/ml). De ellos, el 52,6% con fracción de eyección del ventrículo izquierdo (FEVI) no preservada (< 50%) y el 56,6% con disfunción del ventrículo derecho (VD). El 26,3% fallecieron durante un seguimiento medio de 35,8 meses. La supervivencia en pacientes con BI ≤ 21,8 fue menor, globalmente, y en los subgrupos de pacientes sin FEVI preservada y con disfunción del VD; p < 0,008). En el análisis multivariante una BI ≥ 21,8 fue un factor independiente de supervivencia (HR: 0,242; IC 95%: 0,86-0,681; p = 0,007). Conclusiones: Los valores de la BI medidos con IVOL pueden ser un predictor independiente de mortalidad a largo plazo en pacientes hospitalizados por IC aguda. Este valor pronóstico se mantiene en pacientes con FEVI no preservada y con disfunción ventricular derecha

Age and Training-Related Changes on Body Composition and Fitness in Male Amateur Cyclists

Master athletes are considered as a model of healthy aging because they can limit the age-related decline of physiological abilities compared to sedentary individuals. The main objective of this study is to analyze age-related changes and annual training on body composition (BC) and cardiorespiratory fitness (CRF) parameters. The participants in this retrospective cross-sectional study were 176 male cyclists, aged 40-60 years. BC was evaluated through anthropometric measurements and CRF was determined by an incremental cycle ergometer test to exhaustion. A comparative study between age groups was carried out through a one-way ANOVA test and the associations between the variables were assessed by Spearman’s correlation coefficients and multiple regression analysis to estimate the performance. Training was generally associated with a decrease in both body weight and body fat (p &lt; 0.05). A decrease in resting heart rate was observed as a vagal effect of kilometers cycled per year (p &lt; 0.05). Kilometers cycled per year were associated with an increase in peak power output, which was larger in the master 40 group (p &lt; 0.05) with a non-significant upward in VO2max (p &gt; 0.05). In the performance prediction model, the included variables explained 52% of the variance. In summary, the changes induced by age were minimal in BC and negligible in CRF, whereas HR decreased with age. Training load was generally associated with a decrease in body weight, BMI and body fat percentage that was particularly notable in the abdominal skin folds. A decrease in HRrest was observed as a vagal effect due to kilometers cycled per year, and age did not seem to have a significant effect. The annual cycling kilometers were associated with to high PPO that is greater in the M40 group and a non-significant upward trend in VO2max

A Systematic Review on Spinal Asymmetries in Case Studies of Unilateral Nephroptosis from a Viscerosomatic Point of View

The assessment of posture and asymmetries is common in musculoskeletal clinical practice, and correction is a frequent goal. In this setting, posture and asymmetries are usually interpreted in terms of musculoskeletal issues. This study aimed to evaluate spinal asymmetries in case studies of unilateral nephroptosis. A systematic review was performed using PubMed, CINAHL, Scopus and Web of Science. We included case reports and case series of nephroptotic patients which showed diagnostic imaging that allowed us to assess the presence of spinal asymmetries in the frontal plane. The methodological quality of the selected studies was assessed by using Case Report (CARE) checklist. Nineteen studies were included, with a total number of 78 reported patients (69 women) ranging 22 to 44 years old (mean: 29). Only one patient presented with medial nephroptosis, while the rest presented with caudal migration. Ninety-one percent of the cases affected to the right kidney. All cases but two showed homolateral flank closure (lower rib descent, iliac crest raise and/or homolateral side-bending). The correction of nephroptosis, either by supine position or surgical treatment, removed asymmetries in some cases while other cases improved only partly. Manual therapists must consider visceral implications while assessing body posture. Further, since the most common symptom of nephroptosis is loin pain, and it has been claimed that loin pain is underdiagnosed, manual therapists should consider its potential presence during clinical practice. Finally, being that nephroptosis shares several features with idiopathic lumbar scoliosis (type of patient, postural adaptation), more research is needed regarding any possible relation between them