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About

Miguel Velhote Correia graduated in Electrical and Computer Engineering from University of Porto, Faculty of Engineering (FEUP) in 1990. He obtained the Master and the Doctoral degrees also from FEUP in 1995 and 2001, in the fields of Industrial Automation and Computer Vision, respectively. Currently, he is an Assistant Professor at the Department of Electrical and Computer Engineering at FEUP, since 2002 and with tenure since 2007. Since March 2008, he is also a senior research member at INESC Technology and Science – Institute of Systems and Computer Engineering of Porto, head of the Bioinstrumentation Laboratory of the Centre for Biomedicla Engineering Research. Additionally, he is co-founder and technical advisor of Kinematix Sense S.A. (formerly Tomorrow Options - Microelectronics S.A), an electronic devices start-up company of University of Porto and INESCTEC. Between 1993 and 2007, he was a researcher at INEB – Institute of Biomedical Engineering, in the Biomedical Imaging and Vision Computing group and previously at the CIM Centre of Porto at FEUP. His main research interests are in Sensors and Electronics, Biomedical Instrumentation, Computational Vision and Image and Signal Processing, with focus in sensing methods, technologies and data fusion for the measurement and analysis of human movement, perception, action and performance. Since 1990, he participated in more than twenty funded research projects and co-authored over 100 research papers published in peer reviewed journals and conference proceedings. He is also member of the Portuguese Official Engineers Association, the International Association of Pattern Recognition, through its Portuguese chapter, and co-founder of the Portuguese Experimental Psychology Association.

Interest
Topics
Details

Details

006
Publications

2021

Secure Triplet Loss: Achieving Cancelability and Non-Linkability in End-to-End Deep Biometrics

Authors
Pinto, JR; Correia, MV; Cardoso, JS;

Publication
IEEE Transactions on Biometrics, Behavior, and Identity Science

Abstract

2021

Orientation-Invariant Spatio-Temporal Gait Analysis Using Foot-Worn Inertial Sensors

Authors
Guimaraes, V; Sousa, I; Correia, MV;

Publication
SENSORS

Abstract
Inertial sensors can potentially assist clinical decision making in gait-related disorders. Methods for objective spatio-temporal gait analysis usually assume the careful alignment of the sensors on the body, so that sensor data can be evaluated using the body coordinate system. Some studies infer sensor orientation by exploring the cyclic characteristics of walking. In addition to being unrealistic to assume that the sensor can be aligned perfectly with the body, the robustness of gait analysis with respect to differences in sensor orientation has not yet been investigated-potentially hindering use in clinical settings. To address this gap in the literature, we introduce an orientation-invariant gait analysis approach and propose a method to quantitatively assess robustness to changes in sensor orientation. We validate our results in a group of young adults, using an optical motion capture system as reference. Overall, good agreement between systems is achieved considering an extensive set of gait metrics. Gait speed is evaluated with a relative error of -3.1 +/- 9.2 cm/s, but precision improves when turning strides are excluded from the analysis, resulting in a relative error of -3.4 +/- 6.9 cm/s. We demonstrate the invariance of our approach by simulating rotations of the sensor on the foot.

2020

Secure Triplet Loss for End-to-End Deep Biometrics

Authors
Pinto, JR; Cardoso, JS; Correia, MV;

Publication
2020 8th International Workshop on Biometrics and Forensics (IWBF)

Abstract

2020

Comparison of upper limb kinematics in two activities of daily living with different handling requirements

Authors
Mesquita, IA; Pereira da Fonseca, PFP; Borgonovo Santos, M; Ribeiro, E; Vieira Pinheiro, ARV; Correia, MV; Silva, C;

Publication
HUMAN MOVEMENT SCIENCE

Abstract
Introduction: Recently, kinematic analysis of the drinking task (DRINK) has been recommended to assess the quality of upper limb (UL) movement after stroke, but the accomplishment of this task may become difficult for poststroke patients with hand impairment. Therefore, it is necessary to study ADLs that involve a simpler interaction with a daily life target, such as the turning on a light task (LIGHT). As the knowledge of movement performed by healthy adults becomes essential to assess the quality of movement of poststroke patients, the main goal of this article was to compare the kinematic strategies used by healthy adults in LIGHT with those that are used in DRINK. Methods: 63 adults, aged 30 to 69 years old, drank water and turned on a light, using both ULs separately, while seated. The movements of both tasks were captured by a 3D motion capture system. End-point and joint kinematics of reaching and returning phases were analysed. A multifactorial analysis of variance with repeated measures was applied to the kinematic metrics, using age, sex, body mass index and dominance as main factors. Results: Mean and peak velocities, index of curvature, shoulder flexion and elbow extension were lower in LIGHT, which suggests that the real hand trajectory was smaller in this task. In LIGHT, reaching was less smooth and returning was smoother than DRINK. The instant of peak velocity was similar in both tasks. There was a minimal anterior trunk displacement in LIGHT, and a greater anterior trunk displacement in DRINK. Age and sex were the main factors which exerted effect on some of the kinematics, especially in LIGHT. Conclusion: The different target formats and hand contact in DRINK and LIGHT seem to be responsible for differences in velocity profile, efficiency, smoothness, joint angles and trunk displacement. Results suggest that the real hand trajectory was smaller in LIGHT and that interaction with the switch seems to be less demanding than with the glass. Accordingly, LIGHT could be a good option for the assessment of poststroke patients without grasping ability. Age and sex seem to be the main factors to be considered in future studies for a better match between healthy and poststroke adults.

2019

Combined phase and magnitude metric for validation of lower limb multibody dynamics muscle action with sEMG

Authors
Rodrigues, C; Correia, M; Abrantes, J; Nadal, J; Benedetti, M;

Publication
IFMBE Proceedings

Abstract
This study presents and applies combined phase and magnitude metrics for validation of multibody dynamics (MBD) estimated muscle actions with simultaneous registered sEMG of lower limb muscles. Subject-specific tests were performed for acquisition of ground reaction forces and kinematic data from joint reflective markers during NG, SKG and SR. Inverse kinematics and dynamics was performed using AnyBody musculoskeletal personalized modeling and simulation. MBD estimated muscle activity (MA) of soleus medialis (SM) and tibialis anterior (TA) were compared on phase, magnitude and combined metric with simultaneous acquisition of sEMG for the same muscles. Results from quantitative metrics presented better agreement between MDB MA and sEMG on phase (P) than on magnitude (M) with combined (C) metric following the same pattern as the magnitude. Soleus medialis presented for specific subject lower P and M error on NG and SKG than at SR with similar P errors for tibialis anterior and higher error on M for TA at NG and SKG than SR. Separately and combined quantitative metrics of phase and magnitude presents as a suitable tool for comparing measured sEMG and MBD estimated muscle activities, contributing to overcome qualitative and subjective comparisons, need for intensive observer supervision, low reproducibility and time consuming. © Springer Nature Singapore Pte Ltd. 2019.

Supervised
thesis

2020

bio-signal analysis for neuromuscular control assessment: application to the stretch-shortening cycle in the human locomotion system

Author
Carlos Manuel Barbosa Rodrigues

Institution
UP-FEUP

2020

Detection, characterization and evaluation of posture, and upper-limbs movements in stroke patients by means of sensor fusion

Author
Pedro Filipe Pereira da Fonseca

Institution
UP-FEUP

2020

Mobile Solution for the Assessment of Gait and Motor-Cognitive Functions in Aging

Author
Vânia Margarida Cardoso Guimarães

Institution
UP-FEUP

2020

Prototype of a mandibular advancement device with microsensors for sleep apnea syndrome and snoring

Author
Helena Patrícia Campos da Silva

Institution
UP-FEUP

2020

Seamless Multimodal Biometrics for Continuous Personalised Wellbeing Monitoring

Author
João Tiago Ribeiro Pinto

Institution
UP-FEUP