Fabio Stroppa (Eng., PhD) received the B.S. and M.S. degrees in Computer Science Engineering from Polytechnic University of Bari, Bari, Italy, in 2011 and 2013, respectively, and the PhD in Perceptual Robotics from Scuola Superiore Sant’Anna, Pisa, Italy in 2018. He is currently a postdoc at CHARM Lab, Stanford University, California, USA. His publications and his main research interests deal with computer vision for control purposes of robotic devices, robotic-based neurorehabilitation, bioinformatics, virtual reality and artificial intelligence.

Professional Education

  • Doctor of Philosophy, Higher Schl Univ & Adv Stu Sant' Anna (2018)
  • M.S., Polytechnic University of Bari, Bari, Italy, Computer Science Engineering (2013)
  • B.S., Polytechnic University of Bari, Bari, Italy, Computer Science Engineering (2011)

All Publications

  • Convex polygon fitting in robot-based neurorehabilitation APPLIED SOFT COMPUTING Stroppa, F., Loconsole, C., Frisoli, A. 2018; 68: 609–25
  • Real-time 3D tracker in robot- based neuro rehabilitation Computer Vision for Assistive Healthcare Stroppa, F. Elsevier. 2018; 1: 30
  • Upper Limb Joint Angular Velocity Synergies of Human Reaching Movements IEEE International Conference on Cyborg and Bionic Systems (CBS) Tang, S. 2018

    View details for DOI 10.1109/CBS.2018.8612235

  • An Improved Adaptive Robotic Assistance Methodology for Upper-Limb Rehabilitation International Conference on Human Haptic Sensing and Touch Enabled Computer Applications Stroppa, F. 2018
  • Teleoperated bilateral-arm rehabilitation with ALEx Rehab Station nternational Conference on NeuroRehabilitation Barsotti, M. 2018
  • Kids (learn how to) save lives in the school with the serious game Relive RESUSCITATION Semeraro, F., Frisoli, A., Loconsole, C., Mastronicola, N., Stroppa, F., Ristagno, G., Scapigliati, A., Marchetti, L., Cerchiari, E. 2017; 116: 27–32


    Relive is a serious game focusing on increasing kids and young adults' awareness on CPR. We evaluated the use of Relive on schoolchildren.A longitudinal, prospective study was carried out in two high schools in Italy over a 8-month period, divided in three phases: baseline, competition, and retention. Improvement in schoolchildren's CPR awareness, in terms of knowledge (MCQ results) and skills (chest compression (CC) rate and depth), was evaluated. Usability of Relive and differences in CC performance according to sex and BMI class were also evaluated.At baseline, students performed CC with a mean depth of 31mm and a rate of 95 cpm. In the competition phase, students performed CC with a mean depth of 46mm and a rate of 111 cpm. In the retention phase, students performed CC with a mean depth of 47mm and a rate of 131 cpm. Thus, the training session with Relive during the competition phase affected positively both CC depth (p<0.001) and rate (p<0.001). Such an effect persisted up to the retention phase. CC depth was also affected by gender (p<0.01) and BMI class (p<0.01). Indeed, CC depth was significantly greater in male players and in players with higher BMI. Seventy-three percent of students improved their CPR knowledge as represented by an increases in the MCQ score (p<0.001). The participants perceived the Relive to be easy to use with effective feedback.Relive is an useful tool to spread CPR knowledge and improve CPR skills in schoolchildren.

    View details for DOI 10.1016/j.resuscitation.2017.04.038

    View details for Web of Science ID 000405398500020

    View details for PubMedID 28476478

  • Online Adaptive Assistance Control in Robot-Based Neurorehabilitation Therapy Stroppa, F., Marcheschi, S., Mastronicola, N., Loconsole, C., Frisoli, A., Amirabdollahian, F., Burdet, E., Masia, L. IEEE. 2017: 628–33


    Repetitive and task specific robot-based rehabilitation has been proved to be effective for motor recovery over time. During a therapy, the task should improve subject's impaired movements, but also enhance their efforts for a more effective recovery. This requires an accurate tuning of the task difficulty, which should be tailored directly to the patient. In this work, we propose a system for real-time assistance adaptation based on online performance evaluation for post-stroke subjects. In particular, the aim of the system is to implement the "assist-as-needed" paradigm based on actual patients' motor skills during a therapy session with an active upper-limb robotic exoskeleton. The strength of the work is to propose a real-time algorithm for the assistance tuning based on an "assistance-performance" relationship. Such a relationship is based on experimental measurements, and allows the algorithm to compute a straightforward calculation of the assistance required. Finally, an assessment phase will show how the system provides assistance based on the difficulties experienced from the subjects, also facilitating their adaptation during the task.

    View details for Web of Science ID 000426850800107

    View details for PubMedID 28813890

  • A Robot-Assisted Neuro-Rehabilitation System for Post-Stroke Patients' Motor Skill Evaluation with ALEx Exoskeleton Stroppa, F., Loconsole, C., Marcheschi, S., Frisoli, A., Ibanez, J., GonzalezVargas, J., Azorin, J. M., Akay, M., Pons, J. L. SPRINGER INTERNATIONAL PUBLISHING AG. 2017: 501–5
  • RELIVE: A Markerless Assistant for CPR Training IEEE TRANSACTIONS ON HUMAN-MACHINE SYSTEMS Loconsole, C., Frisoli, A., Semeraro, F., Stroppa, F., Mastronicola, N., Filippeschi, A., Marchetti, L. 2016; 46 (5): 755–60
  • Let’s play relive! young people may learn how to save lives with a serious game Resuscitation Semeraro, F. 2016; 106
  • RELIVE Tracking for quality cardiopulmonary resuscitation training: An experimental comparison with a standard CPR training mannequin RESUSCITATION Loconsole, C., Frisoli, A., Mastronicola, N., Stroppa, F., Ristagno, G., Marchetti, L., Semeraro, F. 2015; 93: E1–E2
  • EasyCluster2: an improved tool for clustering and assembling long transcriptome reads Bevilacqua, V., Pietroleonardo, N., Giannino, E., Stroppa, F., Simone, D., Pesole, G., Picardi, E. BIOMED CENTRAL LTD. 2014: S7


    Expressed sequences (e.g. ESTs) are a strong source of evidence to improve gene structures and predict reliable alternative splicing events. When a genome assembly is available, ESTs are suitable to generate gene-oriented clusters through the well-established EasyCluster software. Nowadays, EST-like sequences can be massively produced using Next Generation Sequencing (NGS) technologies. In order to handle genome-scale transcriptome data, we present here EasyCluster2, a reimplementation of EasyCluster able to speed up the creation of gene-oriented clusters and facilitate downstream analyses as the assembly of full-length transcripts and the detection of splicing isoforms.EasyCluster2 has been developed to facilitate the genome-based clustering of EST-like sequences generated through the NGS 454 technology. Reads mapped onto the reference genome can be uploaded using the standard GFF3 file format. Alignment parsing is initially performed to produce a first collection of pseudo-clusters by grouping reads according to the overlap of their genomic coordinates on the same strand. EasyCluster2 then refines read grouping by including in each cluster only reads sharing at least one splice site and optionally performs a Smith-Waterman alignment in the region surrounding splice sites in order to correct for potential alignment errors. In addition, EasyCluster2 can include unspliced reads, which generally account for >50% of 454 datasets, and collapses overlapping clusters. Finally, EasyCluster2 can assemble full-length transcripts using a Directed-Acyclic-Graph-based strategy, simplifying the identification of alternative splicing isoforms, thanks also to the implementation of the widespread AStalavista methodology. Accuracy and performances have been tested on real as well as simulated datasets.EasyCluster2 represents a unique tool to cluster and assemble transcriptome reads produced with 454 technology, as well as ESTs and full-length transcripts. The clustering procedure is enhanced with the employment of genome annotations and unspliced reads. Overall, EasyCluster2 is able to perform an effective detection of splicing isoforms, since it can refine exon-exon junctions and explore alternative splicing without known reference transcripts. Results in GFF3 format can be browsed in the UCSC Genome Browser. Therefore, EasyCluster2 is a powerful tool to generate reliable clusters for gene expression studies, facilitating the analysis also to researchers not skilled in bioinformatics.

    View details for DOI 10.1186/1471-2105-15-S15-S7

    View details for Web of Science ID 000346167900007

    View details for PubMedID 25474441

    View details for PubMedCentralID PMC4271567

  • Fall Detection in indoor environment with Kinect sensor Bevilacqua, V., Nuzzolese, N., Barone, D., Pantaleo, M., Suma, M., D'Ambruoso, D., Volpe, A., Loconsole, C., Stroppa, F., IEEE IEEE. 2014: 319–24
  • A Robust Real-Time 3D Tracking Approach for Assisted Object Grasping Loconsole, C., Stroppa, F., Bevilacqua, V., Frisoli, A., Auvray, M., Duriez, C. SPRINGER-VERLAG BERLIN. 2014: 400–408
  • Evaluation of Resonance in Staff Selection through Multimedia Contents Bevilacqua, V., Salatino, A., Di Leo, C., D'Ambruoso, D., Suma, M., Barone, D., Tattoli, G., Campagna, D., Stroppa, F., Pantaleo, M., Huang, D. S., Jo, K. H., Wang, L. SPRINGER-VERLAG BERLIN. 2014: 185–98
  • Clustering and Assembling Large Transcriptome Datasets by EasyCluster2 International Conference on Intelligent Computing Bevilacqua, V. 2013
  • A Novel Approach to Clustering and Assembly of Large-Scale Roche 454 Transcriptome Data for Gene Validation and Alternative Splicing Analysis Bevilacqua, V., Stroppa, F., Saladino, S., Picardi, E., Huang, D., Gan, Y., Premaratne, P., Han, K. SPRINGER-VERLAG BERLIN. 2012: 641-+
  • An improved procedure for clustering and assembly of large transcriptome data EMBnet.journal Picardi, E. 2012

    View details for DOI 10.14806/ej.18.A.458