Luca Romeo
Marche Polytechnic University
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Publication
Featured researches published by Luca Romeo.
International Journal of Social Robotics | 2015
E Elena Torta; Jim van Heumen; Francesco Piunti; Luca Romeo; Rh Raymond Cuijpers
One of the most common tasks of a robot companion in the home is communication. In order to initiate an information exchange with its human partner, the robot needs to attract the attention of the human. This paper presents results of two user studies (
international conference on consumer electronics | 2017
Lucio Ciabattoni; Francesco Ferracuti; Sauro Longhi; Lucia Pepa; Luca Romeo; Federica Verdini
international conference of the ieee engineering in medicine and biology society | 2016
Marianna Capecci; Maria Gabriella Ceravolo; Francesco Ferracuti; Sabrina Iarlori; Sauro Longhi; Luca Romeo; S. N. Russi; Federica Verdini
\mathrm{N}=12
international conference of the ieee engineering in medicine and biology society | 2015
Marianna Capecci; Maria Gabriella Ceravolo; F. D'Orazio; Francesco Ferracuti; Sabrina Iarlori; G. Lazzaro; Sauro Longhi; Luca Romeo; Federica Verdini
international conference on consumer electronics | 2016
Lucio Ciabattoni; Francesco Ferracuti; Sabrina Iarlori; Sauro Longhi; Luca Romeo
N=12) to evaluate the effectiveness of unimodal and multimodal communication cues for attracting attention. Results showed that unimodal communication cues which involve sound generate the fastest reaction times. Contrary to expectations, multimodal communication cues resulted in longer reaction times with respect to the unimodal communication cue that produced the shortest reaction time.
ieee asme international conference on mechatronic and embedded systems and applications | 2014
Massimo Grisostomi; Lucio Ciabattoni; Mariorosario Prist; Luca Romeo; Gianluca Ippoliti; Sauro Longhi
In this work we propose a real-time detection of mental stress during different cognitive tasks. Stress is classified processing Galvanic Skin Response (GSR), RR Interval and Body Temperature (BT) acquired by a commercial smartwatch. The unobtrusive system proposed is validated through clinical psychological tests.
Journal of Biomechanics | 2018
Marianna Capecci; Maria Gabriella Ceravolo; Francesco Ferracuti; Martina Grugnetti; Sabrina Iarlori; Sauro Longhi; Luca Romeo; Federica Verdini
In this paper, the accuracy evaluation of the Kinect v2 sensor is investigated in a rehabilitation scenario. The accuracy analysis is provided in terms of joint positions and angles during dynamic postures used in low-back pain rehabilitation. Although other studies have focused on the validation of the accuracy in terms of joint angles and positions, they present results only considering static postures whereas the rehabilitation exercise monitoring involves to consider dynamic movements with a wide range of motion and issues related to the joints tracking. In this work, joint positions and angles represent clinical features, chosen by medical staff, used to evaluate the subjects movements. The spatial and temporal accuracy is investigated with respect to the gold standard, represented by a stereophotogrammetric system, characterized by 6 infrared cameras. The results provide salient information for evaluating the reliability of Kinect v2 sensor for dynamic postures.
international conference on consumer electronics berlin | 2016
Lucio Ciabattoni; Francesco Ferracuti; Giuseppe Lazzaro; Luca Romeo; Federica Verdini
This work deals with the design of an interactive monitoring tool for home-based physical rehabilitation. The software platform includes a video processing stage and the exercise performance evaluation. Image features are extracted by a Kinect v2 sensor and elaborated to return the exercises score. Furthermore the tool provides to physiotherapists a quantitative exercise evaluation of subjects performances. The proposed tool for home rehabilitation has been tested on 5 subjects and 5 different exercises and results are presented. In particular both exercises and relative evaluation indexes were selected by specialists in neurorehabilitation.
Sensors | 2018
Andrea Monteriù; Mariorosario Prist; Emanuele Frontoni; Sauro Longhi; Filippo Pietroni; Sara Casaccia; Lorenzo Scalise; Annalisa Cenci; Luca Romeo; Riccardo Berta; Loreto Pescosolido; Gianni Orlandi; Gian Marco Revel
We propose a novel e-rehabilitation system based on a commercial RGB-D device. Differently from exergaming approaches, clinical objectives scores of each specific body part involved in the exercise are computed. Subjects performances are sent to the physiotherapists in order to support and improve decisions and therapies.
Sensors | 2018
Marina Paolanti; Luca Romeo; Daniele Liciotti; Annalisa Cenci; Emanuele Frontoni; Primo Zingaretti
Most of the existing commercial node architectures provide little flexibility and configurability. This limitation constrains the usability of the same node across various applications, including the ambient intelligence issue. In this paper a novel architecture for the design of a modular wireless sensor node is proposed, dividing the connection and sensing functions in two separate boards. The division of the wireless transducer interface module (WTIM) in two independent boards allows to perform in a separate way the connection and sensor interfacing function of the WTIM always respecting IEEE 1451 standards. The versatility of the novel architecture has been tested in two different application scenarios. In the first application the modular node has been used in a factory to monitor the efficiency and reliability of the production line. The designed node has been experimentally tested and results shown. Concerning the second application, a smart home approach is proposed. Using different sensing boards, an architecture to monitor in a non-invasive way several home parameters has been presented.