2020
Autores
Paiva, JS; Jorge, PAS; Ribeiro, RSR; Balmaña, M; Campos, D; Mereiter, S; Jin, CS; Karlsson, NG; Sampaio, P; Reis, CA; Cunha, JPS;
Publicação
SCIENTIFIC REPORTS
Abstract
An amendment to this paper has been published and can be accessed via a link at the top of the paper. © 2020, The Author(s).
2020
Autores
Rocha, JN; Barnes, CM; Rees, P; Clark, CT; Stratton, G; Summers, HD;
Publicação
MEDICINE AND SCIENCE IN SPORTS AND EXERCISE
Abstract
Purpose (i) To develop an automated measurement technique for the assessment of both the form and intensity of physical activity undertaken by children during play. (ii) To profile the varying activity across a cohort of children using a multivariate analysis of their movement patterns. Methods Ankle-worn accelerometers were used to record 40 min of activity during a school recess, for 24 children over five consecutive days. Activity events of 1.1 s duration were identified within the acceleration time trace and compared with a reference motif, consisting of a single walking stride acceleration trace, obtained on a treadmill operating at a speed of 4 km h(-1). Dynamic time warping of motif and activity events provided metrics of comparative movement duration and intensity, which formed the data set for multivariate mapping of the cohort activity using a principal component analysis (PCA). Results The two-dimensional PCA plot provided clear differentiation of children displaying diverse activity profiles and clustering of those with similar movement patterns. The first component of the PCA correlated to the integrated intensity of movement over the 40-min period, whereas the second component informed on the temporal phasing of activity. Conclusions By defining movement events and then quantifying them by reference to a motion-standard, meaningful assessment of highly varied activity within free play can be obtained. This allows detailed profiling of individual children's activity and provides an insight on social aspects of play through identification of matched activity time profiles for children participating in conjoined play.
2020
Autores
Vilas Boas, MD; Rocha, AP; Cardoso, MN; Fernandes, JM; Coelho, T; Cunha, JPS;
Publicação
FRONTIERS IN NEUROLOGY
Abstract
Hereditary amyloidosis associated with transthyretin V30M (ATTRv V30M) is a rare and inherited multisystemic disease, with a variable presentation and a challenging diagnosis, follow-up and treatment. This condition entails a definitive and progressive motor impairment that compromises walking ability from near onset. The detection of the latter is key for the disease's diagnosis. The aim of this work is to perform quantitative 3-D gait analysis in ATTRv V30M patients, at different disease stages, and explore the potential of the obtained gait information for supporting early diagnosis and/or stage distinction during follow-up. Sixty-six subjects (25 healthy controls, 14 asymptomatic ATTRv V30M carriers, and 27 symptomatic patients) were included in this case-control study. All subjects were asked to walk back and forth for 2 min, in front of a Kinect v2 camera prepared for body motion tracking. We then used our own software to extract gait-related parameters from the camera's 3-D body data. For each parameter, the main subject groups and symptomatic patient subgroups were statistically compared. Most of the explored gait parameters can potentially be used to distinguish between the considered group pairs. Despite of statistically significant differences being found, most of them were undetected to the naked eye. Our Kinect camera-based system is easy to use in clinical settings and provides quantitative gait information that can be useful for supporting clinical assessment during ATTRv V30M onset detection and follow-up, as well as developing more objective and fine-grained rating scales to further support the clinical decisions.
2020
Autores
Leite, A; Silva, ME; Rocha, AP;
Publicação
2020 11TH CONFERENCE OF THE EUROPEAN STUDY GROUP ON CARDIOVASCULAR OSCILLATIONS (ESGCO): COMPUTATION AND MODELLING IN PHYSIOLOGY NEW CHALLENGES AND OPPORTUNITIES
Abstract
This work focus on detection of diseases from Heart Rate Variability (HRV) series using Long Short-Term Memory (LSTM) networks. First, non-linear models are used to extract sequences of features that characterize the HRV series. These time sequences are then used as input for the LSTM. HRV recordings from the Noltisalis database are used for training and testing this approach. The results indicate that the procedure provides accuracy scores in the range of 86.7% to 90.0% on the test set.
2020
Autores
Miyandoab, FD; Ferreira, JC; Tavares, VMG; da Silva, JM; Velez, FJ;
Publicação
IEEE-ACM TRANSACTIONS ON NETWORKING
Abstract
A multifunctional router IC to be included in the nodes of a wearable body sensor network is described and evaluated. The router targets different application scenarios, especially those including tens of sensors, embedded into textile materials and with high data-rate communication demands. The router IC supports two different functionality sets, one for sensor nodes and another for the base node, both based on the same circuit module. The nodes are connected to each other by means of woven thick conductive yarns forming a mesh topology with the base node at the center. From the standpoint of the network, each sensor node is a four port router capable of handling packets from destination nodes to the base node, with sufficient redundant paths. The adopted hybrid circuit and packet switching scheme significantly improve network performance in terms of end-to-end delay, throughput and power consumption. The IC also implements a highly precise, sub-microsecond one-way time synchronization protocol which is used for time stamping the acquired data. The communication module was implemented in a 4-metal, 0.35 mu m CMOS technology. The maximum data rate of the system is 35 Mbps while supporting up to 250 sensors, which exceeds current BAN applications scenarios.
2020
Autores
Galdi, C; Boyle, J; Chen, LL; Chiesa, V; Debiasi, L; Dugelay, JL; Ferryman, J; Grudzien, A; Kauba, C; Kirchgasser, S; Kowalski, M; Linortner, M; Maik, P; Michon, K; Patino, L; Prommegger, B; Sequeira, AF; Szklarski, L; Uhl, A;
Publicação
IET BIOMETRICS
Abstract
Pervasive and useR fOcused biomeTrics bordEr projeCT (PROTECT) is an EU project funded by the Horizon 2020 research and Innovation Programme. The main aim of PROTECT was to build an advanced biometric-based person identification system that works robustly across a range of border crossing types and that has strong user-centric features. This work presents the case study of the multibiometric verification system developed within PROTECT. The system has been developed to be suitable for different borders such as air, sea, and land borders. The system covers two use cases: the walk-through scenario, in which the traveller is on foot; the drive-through scenario, in which the traveller is in a vehicle. Each deployment includes a different set of biometric traits and this study illustrates how to evaluate such multibiometric system in accordance with international standards and, in particular, how to overcome practical problems that may be encountered when dealing with multibiometric evaluation, such as different score distributions and missing scores.
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