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About

Luis Paulo Reis is an Associate Professor at the University of Minho in Portugal and Director of LIACC â?? Artificial Intelligence and Computer Science Laboratory where he also coordinates the Human-Machine Intelligent Cooperation Research Group. He is a IEEE Senior Member and vice-president of both the Portuguese Society for Robotics and the Portuguese Association for Artificial Intelligence. During the last 25 years he has lectured courses, at the University, on Artificial Intelligence, Intelligent Robotics, Multi-Agent Systems, Simulation and Modelling, Educational/Serious Games and Computer Programming. He was principal investigator of more than 10 research projects in those areas. He won more than 50 scientific awards including wining more than 15 RoboCup international competitions and best papers at conferences such as ICEIS, Robotica, IEEE ICARSC and ICAART. He supervised 17 PhD and 95 MSc theses to completion. He organized more than 50 scientific events and belonged to the Program Committee of more than 250 scientific events. He is the author of more than 250 publications in international conferences and journals (indexed at SCOPUS or ISI Web of Knowledge).

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Details

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Publications

2018

Developments and Advances in Intelligent Systems and Applications

Authors
Rocha, Á; Reis, LP;

Publication
Studies in Computational Intelligence

Abstract

2018

Real-time tool for human gait detection from lower trunk acceleration

Authors
Gonçalves, HR; Moreira, R; Rodrigues, A; Minas, G; Reis, LP; Santos, CP;

Publication
Advances in Intelligent Systems and Computing

Abstract
The continuous monitoring of human gait would allow to more objectively verify the abnormalities that arise from the most common pathologies. Therefore, this manuscript proposes a real-time tool for human gait detection from lower trunk acceleration. The vertical acceleration signal was acquired through an IMU mounted on a waistband, a wearable device. The proposed algorithm was based on a finite state machine (FSM) which includes a set of suitable decision rules and the detection of Heel-Strike (HS), Foot-flat (FF), Toe-off (TO), Mid-Stance (MS) and Heel-strike (HS) events for each leg. Results involved 7 healthy subjects which had to walk 20 m three times with a comfortable speed. The results showed that the proposed algorithm detects in real-time all the mentioned events with a high accuracy and time-effectiveness character. Also, the adaptability of the algorithm has also been verified, being easily adapted to some gait conditions, such as for different speeds and slopes. Further, the developed tool is modular and therefore can easily be integrated in another robotic control system for gait rehabilitation. These findings suggest that the proposed tool is suitable for the real-time gait analysis in real-life activities. © Springer International Publishing AG, part of Springer Nature 2018.

2018

Trends and Advances in Information Systems and Technologies - Volume 1 [WorldCIST'18, Naples, Italy, March 27-29, 2018]

Authors
Rocha, A; Adeli, H; Reis, LP; Costanzo, S;

Publication
WorldCIST (1)

Abstract

2018

Trends and Advances in Information Systems and Technologies - Volume 2 [WorldCIST'18, Naples, Italy, March 27-29, 2018]

Authors
Rocha, A; Adeli, H; Reis, LP; Costanzo, S;

Publication
WorldCIST (2)

Abstract

2018

An Agent-based Electronic Market to Help Airlines to Recover from Delays

Authors
Reis, LP; Rocha, AP; Castro, AJM;

Publication
Proceedings of the 10th International Conference on Agents and Artificial Intelligence, ICAART 2018, Volume 1, Funchal, Madeira, Portugal, January 16-18, 2018.

Abstract