E
Eduardo Palermo
Researcher at Sapienza University of Rome
Publications - 83
Citations - 1534
Eduardo Palermo is an academic researcher from Sapienza University of Rome. The author has contributed to research in topics: Computer science & Gait (human). The author has an hindex of 16, co-authored 71 publications receiving 1068 citations. Previous affiliations of Eduardo Palermo include New York University & Boston Children's Hospital.
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Journal ArticleDOI
Gait partitioning methods: a systematic review
TL;DR: This paper identifies, select, and categorize the available methodologies for gait phase detection, analyzing advantages and disadvantages of each solution, and comparatively examines the obtainable gaitphase granularities, the usable computational methodologies and the optimal sensor placements on the targeted body segments.
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Experimental evaluation of accuracy and repeatability of a novel body-to-sensor calibration procedure for inertial sensor-based gait analysis
Eduardo Palermo,Stefano Rossi,Francesca Marini,Fabrizio Patanè,Fabrizio Patanè,Paolo Cappa,Paolo Cappa +6 more
TL;DR: In this paper, a functional body-to-sensor calibration procedure for inertial sensor-based gait analysis is described, which consists in measuring the vertical axis during two static positions, and is not affected by magnetic field distortion.
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A novel HMM distributed classifier for the detection of gait phases by means of a wearable inertial sensor network
TL;DR: The here proposed novel distributed classifier can be implemented in the real-time application of gait phases recognition, such as to evaluate gait variability in patients or to control active orthoses for the recovery of mobility of lower limb joints.
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Gait detection in children with and without hemiplegia using single-axis wearable gyroscopes.
Nicole Abaid,Paolo Cappa,Paolo Cappa,Eduardo Palermo,Eduardo Palermo,Maurizio Petrarca,Maurizio Porfiri +6 more
TL;DR: A novel gait phase detection algorithm based on a hidden Markov model, which uses data from foot-mounted single-axis gyroscopes as input, faithfully reproduces reference results in terms of high values of sensitivity and specificity with respect to FSR signals.
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Fifteen Years of Wireless Sensors for Balance Assessment in Neurological Disorders.
Alessandro Zampogna,Ilaria Mileti,Eduardo Palermo,Claudia Celletti,Marco Paoloni,Alessandro Manoni,Ivan Mazzetta,Gloria Dalla Costa,Carlos Pérez-López,Filippo Camerota,Letizia Leocani,Joan Cabestany,Fernanda Irrera,Antonio Suppa +13 more
TL;DR: This narrative review aims to address the topic of balance and wireless sensors in several neurological disorders, including Alzheimer's disease, Parkinson’s disease, multiple sclerosis, stroke, and other neurodegenerative and acute clinical syndromes.