Course I - SIAMOC-SISMES joint session
Wearable sensors for motion analysis in sport and rehabilitation: a guide to their use and informed interpretation
Sports sector is constantly evolving and changing rapidly also thanks to the recent opportunities offered by technological development. Taking advantage of increasingly miniaturized and wearable hardware solutions, large computing and data storage capacities, better network connection potential, nowadays the use of wearable sensors for movement analysis in sport is a reality and is expected to transform both the amateur and professional sports world. Individual athletes, sports teams, coaches and healthcare professionals can already make use of technological solutions in the field and can obtain large amounts of data to support their sports monitoring activities both for optimizing performance and for reducing the risk of injury. With this joint pre-congress course, SIAMOC and SISMES as scientific societies wishes to combine their skills and experience in the analysis of movement using wearable technologies and in functional evaluation in sport to offer a theoretical-practical insight into the conscious use of these technologies in sport. The event will be organized according to the following schedule:
Joseph Vannozzi
Antonio Tessitore
Foro Italico University of Rome
Introduction to the course: what the field asks and what the technology can offer
Pietro Picerno
eCampus University
Mark Good
Campus Biomedical University
Movement analysis methodologies and protocols for sports performance assessment
Injury risk assessment and the management of the injured athlete
Joseph Vannozzi
Antonio Tessitore
Foro Italico University of Rome
Final summary: potential and challenges on the use of wearable sensors in sport
Course II
Francesca Sylos Labini
Germana Cappellini
Saint Lucia Foundation
Rome Italy
Surface electromyography:
from single muscle to spinal maps
Daniel Borzelli
University of Messina, Italy
- What is EMG signal
- Acquisition methods (surface, needle, arrays, etc.)
- Preparation of the subject, positioning of the electrodes and muscle identification
- Acquisition of the signal (synchronization with systems, pre-amplification, etc.)
- Signal pre-processing (artifact filtering and identification)
- Signal analysis(averaging, normalization, frequency analysis)
- Muscle synergies
• decomposition algorithms and methods
_cc781905-5cde-3194-bb3b-136bad5 cf58d_ (spatial, temporal, space-time, space-by-time)
• remuscles of spectral coherence (muscle networks)
• identification of the number of modules
• clustering and comparison between different groups/subjects
• practical examples
- Spinal maps
• theory
• types of myotomal charts(Sharrard and Kendall)
• from EMGs to spinal maps
• practical examples
- EMG arrays
• limitations of bipolar EMG
• information from the hosts
• decomposition of motor units
• motor units and muscle synergies
• practical examples
- Practical part
• recording and processing of emg in different muscles and in different conditions