In recent years, the analysis of human movement in sport and exercise has become increasingly important for optimizing athletic performance, preventing injuries, supporting rehabilitation, and promoting safe and effective physical activity across diverse populations. The availability of advanced biomechanical measurement systems, motion analysis technologies, and computational modeling tools makes it crucial for bioengineers to acquire solid theoretical foundations and practical skills in this multidisciplinary field. This course introduces the scientific principles and practical applications of biomechanics in sports, integrating musculoskeletal biomechanics, ergonomics, movement science, and neuromuscular function. Students will learn how mechanical loads, joint kinematics, muscle activations, and motor control influence sports performance and injury risk. The course combines theoretical knowledge with hands-on experience in experimental techniques widely used in sports biomechanics.
The course offers an advanced and comprehensive understanding of the biomechanical and ergonomic principles that regulate human movement in sports, exercise, and rehabilitation. Students will develop theoretical and practical expertise in the analysis of posture, kinematics, dynamics, muscle function, and joint loading, applied across a variety of athletic and clinical populations, including amateur, professional, and para-athletes. Throughout the course, students will acquire familiarity with state-of-the-art experimental technologies used in the biomechanical evaluation of human movement. They will learn how to collect, process, and interpret complex biomechanical data, and to apply this information to the optimization of athletic performance and the prevention of sport-related injuries. Furthermore, students will be introduced to biomechanical modeling and simulation techniques, gaining the ability to virtually reconstruct and analyze human movement through musculoskeletal models. The integration of theoretical knowledge, experimental practice, and computational modeling will enable students to approach sport biomechanics with a multidisciplinary perspective, critically linking scientific evidence to real-world applications in sports science, rehabilitation, and ergonomic design.
The course aims to provide students with advanced knowledge and practical skills for biomechanical analysis of human movement applied to sports and exercise. Laboratory and field-based activities will support the theoretical lectures, allowing students to directly use motion analysis technologies.
At the end of the course, students will be able to:
Knowledge of biomechanics and informatics
The course includes interactive lectures and laboratory sessions. A combination of theoretical background and applied projects is used, with emphasis on case studies and group work. Students will be divided into small groups and will engage in hands-on computer-based tasks throughout the semester. Students with learning disabilities (DSA) are invited to contact the instructor to discuss personalized arrangements.
Fundamentals of Biomechanics in Sports
Motion Analysis Techniques for sport
Muscle Activity and Neuromuscular Function during sport activity
Biomechanical Assessment and Performance Optimization
Modeling and Simulation of sport gestures
Specific indications on reference bibliography will be provided by the professor at the beginning of the lectures.
Ricevimento: Students may contact the professor by e-mail to arrange an appointment. mail: andrea.canessa@unige.it Office: Dipartimento di informatica bioingegneria, robotica ed ingegneri dei sistemi Via opera pia 13, Building E, second floor
Ricevimento: For appointment contact: camilla.pierella@unige.it
CAMILLA PIERELLA (President)
ANDREA CANESSA
Classes will start according to the official academic calendar of the study program
The timetable for this course is available here: EasyAcademy
The final assessment consists of an oral examination on the theoretical topics covered throughout the course and a project-based discussion related to the laboratory work and data analysis performed by each student or group.
Assessment will be based on both the final oral exam and the laboratory activities. Each component will be evaluated for completeness, originality, and quality, according to a shared and transparent grading rubric. Evaluation criteria include mastery of content, analytical skills, clarity of presentation, and innovation in data analysis or project development.
Ask the professor for other information not included in the teaching schedule.
