CODE 106729 ACADEMIC YEAR 2025/2026 CREDITS 6 cfu anno 1 BIOENGINEERING 11933 (LM-21 R) - GENOVA 6 cfu anno 2 BIOENGINEERING 11159 (LM-21) - GENOVA SCIENTIFIC DISCIPLINARY SECTOR ING-INF/06 LANGUAGE English TEACHING LOCATION GENOVA SEMESTER 2° Semester OVERVIEW The course provides the essential physiological background and knowledge of experimental methods and computational tools for understanding human movements and their neural control. AIMS AND CONTENT LEARNING OUTCOMES The course covers the technologies, the analytical methods, the modeling approaches used for the analysis and quantification of human movement and its neural correlates. Specific topics include three-dimensional analysis of movements, muscle and body mechanics, physiology and physiological signals in motor control, computational motor control. AIMS AND LEARNING OUTCOMES By the end of the course the students will be able to record and analyse human movements: kinematics kinetics muscle activity describe the underlying control using the appropriate analytical tools modeling tools PREREQUISITES There are no formal prerequisites, but students are expected to know mechanics, geometry, linear algebra, calculus and signal analysis. TEACHING METHODS The course combines lectures, guided lab activities, and analysis of movement data. SYLLABUS/CONTENT Part I: movement Human movement. Levels of description of movement: kinematic, kinetic, muscle mechanics. Terminology for describing human movements (limb movements, hand movements). Manipulation. Oral cavity and speech Movement kinematics. Rigid body kinematics. Kinematic chains. Reference frames and their parameterization. Quaternions as representations of 3D spatial geometry Motion capture technologies. Introduction to projective geometry. Stereophotogrammetry. Inertial measurement units. Markerlesssystems. Analysis of movement kinematics. Signal processing of kinematic data (low-pass filters, derivative filters) Movement dynamics. Rigid body mechanics. Newton-Euler and Lagrange Methods. Multi-joint movement statics. Dynamics: equations of motion of kinematic chains. Dynamometry. Force platforms. Mechanical impedance and its measure. Case study: locomotion. Gait kinematics and kinetics. Running, cycling, swimming. Muscle mechanics. Reminder of muscle physiology. Fiber types: intrafusal, extrafusal. Hill’s model of muscle force generation. Muscles and contraction types. Measures of muscle strength Part II: neural control of movement Neuroanatomy of the sensorimotor system. Cortico-spinal tract. Extrapyramidal system: cerebellum, basal ganglia. Somatosensory cortex, frontal cortex. Electromyography. Surface vs intramuscular. Analysis of EMG signals. Motor units and the size principle. Computational motor control. Historical overview. The reflex arc. Central pattern generators. The reafference principle. Bernstein’s physiology of activity: motor equivalence. Marr’s computational framework. Movement psychophysics: movement time, spatio-temporal invariances. Multi-sensory and sensorimotor integration. Taking decisions and taking actions. Optimality in motor control. Motor learning. Sensorimotor adaptation. Implicit vs explicit learning. Savings. Joint Action. Optimality in joint action: game theory and Nash equilibria. Theory of mind. Learning in joint action. RECOMMENDED READING/BIBLIOGRAPHY Uchida TK, Delp SL (2021) Biomechanics of Movement. MIT Press. TEACHERS AND EXAM BOARD VITTORIO SANGUINETI Ricevimento: VITTORIO SANGUINETI. Appointment: Tel. 0103356487 or vittorio.sanguineti@unige.it CECILIA DE VICARIIS LESSONS LESSONS START https://corsi.unige.it/11159/p/studenti-orario Class schedule The timetable for this course is available here: Portale EasyAcademy EXAMS EXAM DESCRIPTION Written exam (weight 60%) Lab Activities (weight 40%) ASSESSMENT METHODS The written exam will consist of questions and problems on lecture topics. There will be four lab activities which will be carried out as teams. Each activity will involve recording a specific movement, analyzing the recorded data and preparing and submitting a technical report. FURTHER INFORMATION Ask the teacher for any other information not provided here Agenda 2030 - Sustainable Development Goals Good health and well being