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About

Duarte Dias is a Biomedical Engineer at INESC TEC and the Coordination Assistant of the Center for Biomedical Engineering (CBER). He is also an invited teacher at the Faculty of Engineering of University of Porto. He has a transversal expertise in wearable health devices, human physiology, hardware and firmware development, signal processing and data analysis. He is co-author in more than ten scientific publications, including a first-author review in “Sensors” related with Wearable Health Devices with more than 100 citations. His interest for entrepreneurship and technology transfer lead him to support and be involved in the creation of two spin-offs at INESC TEC.

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Publications

2022

PDapp: A Companion Mobile Application with Appcessories for Continuous Follow-up of Parkinson’s Disease Patients

Authors
Dias, D; Silva, J; Oliveira, N; Massano, J; Cunha, JPS;

Publication
MELECON 2022 - IEEE Mediterranean Electrotechnical Conference, Proceedings

Abstract

2022

Estimation of ANT-DBS Electrodes on Target Positioning Based on a New PerceptTM PC LFP Signal Analysis

Authors
Lopes, EM; Rego, R; Rito, M; Chamadoira, C; Dias, D; Cunha, JPS;

Publication
SENSORS

Abstract
Deep brain stimulation of the Anterior Nucleus of the Thalamus (ANT-DBS) is an effective therapy in epilepsy. Poorer surgical outcomes are related to deviations of the lead from the ANT-target. The target identification relies on the visualization of anatomical structures by medical imaging, which presents some disadvantages. This study aims to research whether ANT-LFPs recorded with the PerceptTM PC neurostimulator can be an asset in the identification of the DBS-target. For this purpose, 17 features were extracted from LFPs recorded from a single patient, who stayed at an Epilepsy Monitoring Unit for a 5-day period. Features were then integrated into two machine learning (ML)-based methodologies, according to different LFP bipolar montages: Pass1 (nonadjacent channels) and Pass2 (adjacent channels). We obtained an accuracy of 76.6% for the Pass1-classifier and 83.33% for the Pass2-classifier in distinguishing locations completely inserted in the target and completely outside. Then, both classifiers were used to predict the target percentage of all combinations, and we found that contacts 3 (left hemisphere) and 2 and 3 (right hemisphere) presented higher signatures of the ANT-target, which agreed with the medical images. This result opens a new window of opportunity for the use of LFPs in the guidance of DBS target identification.

2021

Changes in heart rate variability after transcranial direct current stimulation in patients with refractory epilepsy

Authors
Lopes, EM; Van Rafelghem, L; Dias, D; Nunes, MC; Hordt, M; Noachtar, S; Kaufmann, E; Cunha, JPS;

Publication
2021 10TH INTERNATIONAL IEEE/EMBS CONFERENCE ON NEURAL ENGINEERING (NER)

Abstract
Cathodal transcranial direct current stimulation (c-tDCS) is a non-invasive option for treatment of refractory epilepsy. However, it is still unknown whether this therapy has a positive stabilizing effect on the vegetative function of these patients. Heart Rate Variability (HRV) is considered an efficient tool to monitor the cardiac autonomic system, which has been correlated with the risk of Sudden Unexpected Death in Epilepsy (SUDEP). In this study, changes in HRV are investigated after c-tDCS of six patients (34.50 ± 11.10 years) with refractory epilepsy, which have been selected at the University Hospital, LMU Munich. Patients were categorized as responders (n=2), non-responders (n=3) and uncategorized (n=1). We analyzed 24 hours of electrophysiological data recorded before and after treatment, and computed HRV metrics (AVNN, SDNN, RMSD, pNN20, pNN50, LH/HF, 0V, IV, 2LV, 2UV, SD1 and SD2). All patients revealed a change in almost all HRV metrics post stimulation. Grouped all patients, there was a significant (p < 0.05) change in RMSSD, pNN50, SD1 and LH/HF. For responders there was an increase in all time domain and non-linear metrics, which was not seen for non-responders. These results suggest that tDCS exerts significant changes in cardiovascular autonomic system in patients with refractory epilepsy. HRV metrics may also serve as biomarkers of the response to tDCS stimulation. A larger dataset is being gathered for further analysis. © 2021 IEEE.

2021

Implementing a Quantified Occupational Health Sensing Platform in the Aviation Sector: an Exploratory Study in Routine Air Traffic Control Work Shifts

Authors
Rodrigues, S; Dias, D; Aleixo, M; Retorta, A; Cunha, JPS;

Publication
2021 43RD ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE & BIOLOGY SOCIETY (EMBC)

Abstract

2020

IHandU: A novel quantitative wrist rigidity evaluation device for deep brain stimulation surgery

Authors
Murias Lopes, E; Vilas Boas, MD; Dias, D; Rosas, MJ; Vaz, R; Silva Cunha, JP;

Publication
SENSORS

Abstract
Deep brain stimulation (DBS) surgery is the gold standard therapeutic intervention in Parkinson’s disease (PD) with motor complications, notwithstanding drug therapy. In the intraoperative evaluation of DBS’s efficacy, neurologists impose a passive wrist flexion movement and qualitatively describe the perceived decrease in rigidity under different stimulation parameters and electrode positions. To tackle this subjectivity, we designed a wearable device to quantitatively evaluate the wrist rigidity changes during the neurosurgery procedure, supporting physicians in decision-making when setting the stimulation parameters and reducing surgery time. This system comprises a gyroscope sensor embedded in a textile band for patient’s hand, communicating to a smartphone via Bluetooth and has been evaluated on three datasets, showing an average accuracy of 80%. In this work, we present a system that has seen four iterations since 2015, improving on accuracy, usability and reliability. We aim to review the work done so far, outlining the iHandU system evolution, as well as the main challenges, lessons learned, and future steps to improve it. We also introduce the last version (iHandU 4.0), currently used in DBS surgeries at São João Hospital in Portugal. © 2020 by the authors.