IGS 2021: The 20th Conference of the International Graphonomics Society

“Intertwining Graphonomics with Human Movements”

 June 7-9, 2022 (On-site), Museo Elder, Las Palmas de Gran Canaria, Spain

Deadline for Submissions: March 25, 2022

Camera ready: April 25, 2022

IGS 2021 Main Conference Program (DRAFT)






Welcome Cocktail Reception




Opening & Keynote 1

(Topic: Advance in the Kinematic Theory)







Keynote 2

(Topic: Robotics)





Social Gala Dinner




Keynote 3

(Topic: Movements in Quadrupeds Animals)





Closings & Awards


Miguel Ángel Ferrer Ballester

TITLE: Kinematic modeling of human movements: a unitary approach

SHORT ABSTRACT: Human kinematics has been modeled through many different techniques, depending on the movement to be analyzed: handwriting, speech, gait, etc. But, human motion is generated by the same principle: several muscular systems respond coordinately to the potential evoked by motor neurons. Therefore, it is conceivable a unitary procedure able to analyze the kinematics of any human movement. In this talk, we discuss such a hypothesis proposing a unitary model based on the Lognormality Principle combined with other neuroscience theories such as the equivalent motor theory proposed by Lashley, the inverse kinematic model suggested by Kawato, and the theoretical existence of the so-called Central Pattern Generators. Some proof of concept are presented in behavioral biometrics, health, and education. Moreover, this model is extended to livestock farming.

SHORT BIO: Miguel A. Ferrer received an M.Sc. and a Ph.D. from the Universidad Politécnica de Madrid, Madrid, Spain, in 1988 and 1994, respectively. He joined the University of Las Palmas de Gran Canaria, Spain, in 1989, where he is currently a Full Professor. He established the Digital Signal Processing Research Group in 1990. His current research interests include pattern recognition in biometrics, audio quality, and computer vision.

 José Manuel Vilar Guereño

TITLE: Use of Biomechanics for Lameness Detection in domestic animals

SHORT ABSTRACT: Biomechanics for motion analysis has been widely used for different purposes. In Veterinary Medicine, this technology is being used for lameness detection mainly in horses and dogs. Kinematic analysis obtains linear, temporal and angular data from lame and sound limbs by means of the use of videography, electrogiometry or inertial sensors in order to compare them and detect the differences. On the other hand, kinetic devices as force or pressure platforms abtain Ground Reaction Forces with the same purpose.

SHORT BIO: Jose Manuel Vilar Guereño born in Donostia, Spain. He obtained the veterinary degree in 1994 from the University of Cordoba, Spain, and the Ph.D. from the Universidad de Las Palmas de Gran Canaria (ULPGC) in 2001. He joined this year as an associated professor at the ULPGC. He carried out biomechanics studies at the University of Bologna, Italy, from 2003-to 2007. In 2011 got the Professor position in Veterinary surgery. In 2018 got the European diploma in sports medicine and veterinary rehabilitation (DECVSMR). He has published around 50 full articles in top-ranked journals and nearly 100 conference papers. His main research interest is biomechanics.

José Juan Quintana Henández

TITLE: Improving human-robot interaction through lognormal-based kinematic

SHORT ABSTRACT: Collaborative robots or cobots are robots created to interact with humans in a collaborative work environment. An essential issue in these robots is to guarantee the safety of humans. Similarly, their interaction with humans can be improved with human-like movement. It can also motivate friendly interaction with robots. To this aim, analysing their movement can help to understand their kinematics. In this talk, we are analyzing whether providing robots with human movement facilitates interaction with them. First, we will show the lognormal kinematic programming in robots. Next, we will assess whether this type of movement improves the interaction with humans.

SHORT BIO: Jose J. Quintana received the MSc and PhD degrees from the Universidad de Las Palmas de Gran Canaria, Las Palmas, Spain, in 1994 and 2011, respectively. He joined the University of Las Palmas de Gran Canaria, in 2004, where he is currently an associate professor. His current research interests include robotics, supercapacitors modeling using fractional math and control of active power filters used in low voltage systems.

Special Sessions

IGS 2021 conference will be a single track, with only one session at a time. The following accepted special sessions will be integrated into the body of the conference.

All contributed papers are submitted in the same format as regular papers (see Authors), selecting at EasyChair the Special Session box or the main track.

1. Handwriting for Neurodegenerative Disorders

Neurodegenerative diseases (ND) are caused by the progressive degeneration of nerve cells and produce effects on both motor skills and cognitive abilities whose severity increase over time. Unfortunately, there is no cure for this type of disease and their effects can only be slowed down with specific pharmacological and rehabilitative therapies. Early diagnosis, therefore, remains the primary means of delaying damage and improving patients’ quality of life. Because of worldwide lifespan lengthening, it is expected that the incidence of ND will dramatically increase in the coming decades. This creates a critical need for the improvement of the approaches currently used for the diagnosis of these diseases. As cognitive and motor functions are both involved in the planning and execution of movements, and because handwriting requires a precise and properly coordinated control of the body, the analysis of handwriting dynamics might provide a cheap and non-invasive method for evaluating the disease progression. Moreover, it has been observed that the application of machine learning methods to motor function has shown promise in decreasing the time taken to perform clinical assessments. To this aim, cheap and widely used graphic tablets can be used to administer handwriting tests, which include simple and easy-to-perform handwriting/drawing tasks, to record kinematic and dynamic information of the performed movements. For this reason, in the last decades, researchers are showing an increasing interest in developing and using pattern recognition and artificial intelligence methodologies to support both the diagnosis and the treatments of NDs, with particular emphasis on Alzheimer’s and Parkinson’s diseases.

Chairpersons: Angelo Marcelli (Salerno University),  Antonio Parziale (Salerno University)

2. Fine-motor motion and eye-movement based biomarkers

Neurodegenerative diseases such as Parkinson’s, Alzheimer’s, MS, MCI and many others influence fine and gross motor coordination. Motion sensors in smartwatches, touch surfaces, pen tablets, computer mouses are commodities today that can record data related to our motor coordination. The analysis of these otherwise unused data holds the promise of finding valuable biomarkers and a deeper understanding of these conditions. As these biomarkers are non-intrusive and can be monitored continuously, they are likely to aid neurodegenerative disease risk assessment, support early detection, and might assist in treating these chronic conditions. Moreover, it could also have an enormous impact on the efficiency of the healthcare system.

Chairpersons: Hans-Leo Teulings (NeuroScript LLC), András Attila Horváth (Semmelweis University), Erika Griechisch (Cursor Insight)

Technical Secretariat:



e-mail: gruposemisorlpa@viajesinsular.es