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Publicações

2017

Beat-ID: Towards a computationally low-cost single heartbeat biometric identity check system based on electrocardiogram wave morphology

Autores
Paiva, JS; Dias, D; Cunha, JPS;

Publicação
PLOS ONE

Abstract
In recent years, safer and more reliable biometric methods have been developed. Apart from the need for enhanced security, the media and entertainment sectors have also been applying biometrics in the emerging market of user-adaptable objects/systems to make these systems more user-friendly. However, the complexity of some state-of-the-art biometric systems (e.g., iris recognition) or their high false rejection rate (e.g., fingerprint recognition) is neither compatible with the simple hardware architecture required by reduced-size devices nor the new trend of implementing smart objects within the dynamic market of the Internet of Things (IoT). It was recently shown that an individual can be recognized by extracting features from their electrocardiogram (ECG). However, most current ECG-based biometric algorithms are computationally demanding and/or rely on relatively large (several seconds) ECG samples, which are incompatible with the aforementioned application fields. Here, we present a computationally low-cost method (patent pending), including simple mathematical operations, for identifying a person using only three ECG morphology-based characteristics from a single heartbeat. The algorithm was trained/tested using ECG signals of different duration from the Physionet database on more than 60 different training/test datasets. The proposed method achieved maximal averaged accuracy of 97.450% in distinguishing each subject from a ten-subject set and false acceptance and rejection rates (FAR and FRR) of 5.710 +/- 1.900% and 3.440 +/- 1.980%, respectively, placing Beat-ID in a very competitive position in terms of the FRR/FAR among state-of-the-art methods. Furthermore, the proposed method can identify a person using an average of 1.020 heartbeats. It therefore has FRR/FAR behavior similar to obtaining a fingerprint, yet it is simpler and requires less expensive hardware. This method targets low-computational/energy-cost scenarios, such as tiny wearable devices (e.g., a smart object that automatically adapts its configuration to the user). A hardware proof-of concept implementation is presented as an annex to this paper.

2017

A diffusion-based connectivity map of the GPi for optimised stereotactic targeting in DBS

Autores
da Silva, NM; Ahmadi, SA; Tafula, SN; Silva Cunha, JPS; Botzel, K; Vollmar, C; Rozanski, VE;

Publicação
NEUROIMAGE

Abstract
Background: The GPi (globus pallidus internus) is an important target nucleus for Deep Brain Stimulation (DBS) in medically refractory movement disorders, in particular dystonia and Parkinson's disease. Beneficial clinical outcome critically depends on precise electrode localization. Recent evidence indicates that not only neurons, but also axonal fibre tracts contribute to promoting the clinical effect. Thus, stereotactic planning should, in the future, also take the individual course of fibre tracts into account. Objective: The aim of this project is to explore the GPi connectivity profile and provide a connectivity based parcellation of the GPi. Methods: Diffusion MRI sequences were performed in sixteen healthy, right-handed subjects. Connectivity-based parcellation of the GPi was performed applying two independent methods: 1) a hypothesis-driven, seed-to-target approach based on anatomic priors set as connectivity targets and 2) a purely data-driven approach based on k-means clustering of the GPi. Results: Applying the hypothesis-driven approach, we obtained five major parcellation clusters, displaying connectivity to the prefrontal cortex, the brainstem, the GPe (globus pallidus externus), the putamen and the thalamus. Parcellation clusters obtained by both methods were similar in their connectivity profile. With the data-driven approach, we obtained three major parcellation clusters. Inter individual variability was comparable with results obtained in thalamic parcellation. Conclusion: The three parcellation clusters obtained by the purely data-driven method might reflect GPi subdivision into a sensorimotor, associative and limbic portion. Clinical and physiological studies indicate greatest clinical DBS benefit for electrodes placed in the postero-ventro-lateral GPi, the region displaying connectivity to the thalamus in our study and generally attributed to the sensorimotor system. Clinical studies relating DBS electrode positions to our GPi connectivity map would be needed to complement our findings.

2017

The Role of the Pallidothalamic Fibre Tracts in Deep Brain Stimulation for Dystonia: A Diffusion MRI Tractography Study

Autores
Rozanski, VE; da Silva, NM; Ahmadi, SA; Mehrkens, J; Cunha, JD; Houde, JC; Vollmar, C; Botzel, K; Descoteaux, M;

Publicação
HUMAN BRAIN MAPPING

Abstract
Background: Deep Brain Stimulation (DBS) of the Globus pallidus internus (GPi) is gold standard treatment in medically refractory dystonia. Recent evidence indicates that stimulation effects are also due to axonal modulation and affection of a fibre network. For the GPi, the pallidothalamic tracts are known to be the major motor efferent pathways. The aim of this study is to explore the anatomic vicinity of these tracts and DBS electrodes in dystonia applying diffusion tractography. Methods: Diffusion MRI was acquired in ten patients presenting for DBS for dystonia. We applied both a conventionally used probabilistic tractography algorithm (FSL) as well as a probabilistic streamline tracking approach, based on constrained spherical deconvolution and particle filtering with anatomic priors, to the datasets. DBS electrodes were coregistered to the diffusion datasets. Results: We were able to delineate the pallidothalamic tracts in all patients. Using the streamline approach, we were able to distinguish between the two sub-components of the tracts, the ansa lenticularis and the fasciculus lenticularis. Clinically efficient DBS electrodes displayed a close anatomic vicinity pathway of the pallidothalamic tracts, and their course was consistent with previous tracer labelling studies. Although we present only anatomic data, we interpret these findings as evidence of the possible involvement of fibre tracts to the clinical effect in DBS. Electro-physiological intraoperative recordings would be needed to complement our findings. In the future, a clear and individual delineation of the pallidothalamic tracts could optimize the stereotactic process of optimal electrode localization. (C) 2016 Wiley Periodicals, Inc.

2017

Heart rate variability metrics for fine-grained stress level assessment

Autores
Pereira, T; Almeida, PR; Cunha, JPS; Aguiar, A;

Publicação
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE

Abstract
Background and Objectives: In spite of the existence of a multitude of techniques that allow the estimation of stress from physiological indexes, its fine-grained assessment is still a challenge for biomedical engineering. The short-term assessment of stress condition overcomes the limits to stress characterization with long blocks of time and allows to evaluate the behaviour change in real-world settings and also the stress level dynamics. The aim of the present study was to evaluate time and frequency domain and nonlinear heart rate variability (HRV) metrics for stress level assessment using a short-time window. Methods: The electrocardiogram (ECG) signal from 14 volunteers was monitored using the Vital Jacketml while they performed the Trier Social Stress Test (TSST) which is a standardized stress-inducing protocol. Window lengths from 220 s to 50 s for HRV analysis were tested in order to evaluate which metrics could be used to monitor stress levels in an almost continuous way. Results: A sub-set of HRV metrics (AVNN, rMSSD, SDNN and pNN20) showed consistent differences between stress and non-stress phases, and showed to be reliable parameters for the assessment of stress levels in short-term analysis. Conclusions: The AVNN metric, using 50 s of window length analysis, showed that it is the most reliable metric to recognize stress level across the four phases of TSST and allows a fine-grained analysis of stress effect as an index of psychological stress and provides an insight into the reaction of the autonomic nervous system to stress.

2016

NeuroKinect: A Novel Low-Cost 3Dvideo-EEG System for Epileptic Seizure Motion Quantification

Autores
Cunha, JPS; Choupina, HMP; Rocha, AP; Fernandes, JM; Achilles, F; Loesch, AM; Vollmar, C; Hartl, E; Noachtar, S;

Publicação
PLOS ONE

Abstract
Epilepsy is a common neurological disorder which affects 0.5-1% of the world population. Its diagnosis relies both on Electroencephalogram (EEG) findings and characteristic seizure -induced body movements - called seizure semiology. Thus, synchronous EEG and (2D) video recording systems (known as Video-EEG) are the most accurate tools for epilepsy diagnosis. Despite the establishment of several quantitative methods for EEG analysis, seizure semiology is still analyzed by visual inspection, based on epileptologists' subjective interpretation of the movements of interest (MOIs) that occur during recorded seizures. In this contribution, we present NeuroKinect, a low-cost, easy to setup and operate solution for a novel 3Dvideo-EEG system. It is based on a RGB-D sensor (Microsoft Kinect camera) and performs 24/7 monitoring of an Epilepsy Monitoring Unit (EMU) bed. It does not require the attachment of any reflectors or sensors to the patient's body and has a very low maintenance load. To evaluate its performance and usability, we mounted a state-of-the-art 6-camera motion-capture system and our low-cost solution over the same EMU bed. A comparative study of seizure-simulated MOIs showed an average correlation of the resulting 3D motion trajectories of 84.2%. Then, we used our system on the routine of an EMU and collected 9 different seizures where we could perform 3D kinematic analysis of 42 MOIs arising from the temporal (TLE) (n = 19) and extratemporal (ETE) brain regions (n = 23). The obtained results showed that movement displacement and movement extent discriminated both seizure MOI groups with statistically significant levels (mean = 0.15 m vs. 0.44 m, p<0.001; mean = 0.068 m(3) vs. 0.14 m(3), p< 0.05, respectively). Furthermore, TLE MOIs were significantly shorter than ETE (mean = 23 seconds vs 35 seconds, p< 0.01) and presented higher jerking levels (mean = 345 ms(-3) vs 172 ms(-3), p< 0.05). Our newly implemented 3D approach is faster by 87.5% in extracting body motion trajectories when compared to a 2D frame by frame tracking procedure. We conclude that this new approach provides a more comfortable (both for patients and clinical professionals), simpler, faster and lower-cost procedure than previous approaches, therefore providing a reliable tool to quantitatively analyze MOI patterns of epileptic seizures in the routine of EMUs around the world. We hope this study encourages other EMUs to adopt similar approaches so that more quantitative information is used to improve epilepsy diagnosis.

2014

Connectivity patterns of pallidal DBS electrodes in focal dystonia: A diffusion tensor tractography study

Autores
Rozanski, VE; Vollmar, C; Cunha, JP; Neves Tafula, SMN; Ahmadi, SA; Patzig, M; Mehrkens, JH; Boetzel, K;

Publicação
NEUROIMAGE

Abstract
Deep brain stimulation (DBS) of the internal pallidal segment (GPi: globus pallidus internus) is gold standard treatment for medically intractable dystonia, but detailed knowledge of mechanisms of action is still not available. There is evidence that stimulation of ventral and dorsal GPi produces opposite motor effects. The aim of this study was to analyse connectivity profiles of ventral and dorsal GPi. Probabilistic tractography was initiated from DBS electrode contacts in 8 patients with focal dystonia and connectivity patterns compared. We found a considerable difference in anterior-posterior distribution of fibres along the mesial cortical sensorimotor areas between the ventral and dorsal GPi connectivity. This finding of distinct GPi connectivity profiles further confirms the clinical evidence that the ventral and dorsal GPi belong to different functional and anatomic motor subsystems. Their involvement could play an important role in promoting clinical DBS effects in dystonia.

Teses
supervisionadas

2017

PhD Work Plan: NeuroOptics - Towards novel optical tools for Neuroscience

Autor
Joana Isabel dos Santos Paiva

Instituição
UP-FEUP

2017

Quantitative assessment of motor performance during robot-aided rehabilitation: preliminary results from NEUROPROBEs project

Autor
Débora Marisa Araújo da Silva Pereira

Instituição
UP-FEUP

2017

Human Sensing and Indoor Location: From coarse to fine detection algorithms based on consumer electronics RF mapping

Autor
Duarte Fleming Oliveira de Sousa

Instituição
UP-FEUP

2016

Low-Cost Device for Live Cell Imaging Applications

Autor
José Manuel Salazar Ribeiro

Instituição
UP-FEUP

2016

Software Defined Radar for Medical Imaging

Autor
Wilson José dos Santos Silva

Instituição
UP-FEUP