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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: January 8, 2022

CALL FOR PAPER

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. 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)

2. 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)

Program

The program will be available soon.