Neuroengineering

Applying engineering to neuroscience, the silver thread of the course will be the analysis of the human brain at different level of integration: from the single cell to small neural networks up to organ level, quantitatively measuring brain metabolism and studying complex brain functions such as neural control of muscle synergies, visual-sensory integration, and dual tasking.

Smart measurements in sports and physical activity

Smart, wearable devices integrate and facilitate many of the daily living process we are all subjected to. Most importantly, smart devices are embedded with sensors providing information of potential biomechanical and physiological interest, like whole-body kinematics and relative changes in blood oxygenation. The ease with which biological data can be collected, allied to the increasing popularity of consumer wearable and smartphone devices, stimulated indeed the emergence of mobile applications for promoting sport and physical activity in different populations. While the market of these health-related devices and applications has garnered the interest of both worldwide manufactures and independent developers, the validity of proposed solutions has been of deceptive concern. European concerted actions have been put into force to contend with this issue, ensuring the delivery of technology at the highest standards to the community. The successful development of health-related devices and applications requires skills transverse to exercise physiology, electronics and signal processing, offering Biomedical Engineers a unique opportunity to further their knowledge. At the basis of this developmental process is the multiplicative benefits of physical activity, limiting the emergence and the effects of non-communicable diseases as per the Global Action Plan on Physical Activity of the World Health Organization.

Neuroengineering

The student will acquire the knowledge of currently available and emerging technologies for interfacing with the human brain. The student will obtain the ability to acquire real brain signals and process these signals using Matlab algorithms. Soft skills will also be developed such as: the ability to work in a team to deal with a laboratory assignment mimicking a real-world problem; the competence to analyze information in the literature and apply that information to a novel problem; and the capability to communicate effectively the methodological choices adopted to solve a problem.

Smart measurements in sports and physical activity

Upon completion of the course students will have got acquainted with: - the three pathways for energy expenditure during physical activity, including the circumstances under which each pathway predominates. - the different methods for assessing the intensity of physical exercise for different sports and physical activities, targeting different populations―able-bodied subjects, aged individuals, subjects with spinal cord injury. - how data provided by sensors in smartphones and wearable devices can be used to obtain information of physiological interest in sport and physical activity. - the use of these data as surrogates for predicting exercise intensity and energy expenditure during walking, running and other activities, as well as the peak anaerobic power output. - the application of appropriate inferential statistics for testing the validity of predictive methods based on smart devices and applications in sports and physical activity.

Neuroengineering

Basic knowledge of mathematics, physics, informatics, and mechanical, chemical and electrical bioengineering as learned in the 3-year program of Biomedical Engineering. Basic knowledge of biomedical signal processing.

Smart measurements in sports and physical activity

Students attending the course are expected to be aware of the basic concepts dealt with during the Bachelor course in Biomedical Engineering. Of specific interest is the knowledge matured in linear algebra, signal processing, physics, and human physiology. Although not compulsory, having experience with the Matlab programming language would be helpful.

Neuroengineering

1. Functional neuroanatomy and neurophysiology (including short notes on brain connectivity) 2. Neurobiological engineering: from the single cell to small networks 2.1 Single cell transmembrane potential detection, voltage clamp/patch clamp, spike sorting 2.2 Microelectrode Arrays (MEAs) to study electrical activity of cell networks LAB: Evaluation of Spike Sorting Techniques applied to Synthetic Extracellualr Recordings 3. Measuring the brain function and metabolism: from large networks to organ level 3.1 Near Infrared Spectroscopy (NIRS) 3.2 Functional Magnetic Resonance Imaging (fMRI) LAB: Acquiring and processing NIRS signal from the pre-frontal cortex under different types of stimuli 4. Stimulating the brain: neuromodulation techniques 4.1 Non-invasive techniques: Transcranial Direct Current Stimulation (tDCS), tACS, Transcranial magnetic stimulation (TMS) 4.3 Invasive techniques: Deep Brain Stimulation (DBS), Intracranial Cortical Stimulation (ICS) 5. Integration of CNS and PNS: a quantitative study of motor control 5.1 Motor control 5.2 Muscle synergies 5.2 Clinical applications 5.3 Motor-cognitive dual task LAB: Non-Negative Matrix factorization (NNMF) to extract muscle synergies during gait 6. Brain Machine Interfaces: from thought to action 6.1 BCI classification: Invasive, semi-invasive, non-invasive, stimulating, bi-directional 6.2 EEG-based BCIs: Visual Evoked Potentials (VEPs), Slow Cortical Potentials (SCPs), P300 oddball paradigm, sensorimotor rhythms (SMR) 7. Neuroprostheses (motor/sensory prostheses): a vision on the future 7.1 Pre-clinical research: retinal prosthesis (bionic eye) LAB PROJECT: To be defined

Smart measurements in sports and physical activity

The following concepts will be delivered, with their relative credit hours indicated alongside: - The metabolic pathways for energy expenditure during physical activity: 6h - Methods for the quantification of the intensity of physical activity and energy expenditure: 6h - Extraction of data from smart and wearable devices (accelerometers, encoders, GPS): 6h - Predicting variables of physiological interest in sport and physical activity from smart-related data: 6h - Inferential statistics for hypothesis testing (General linear models, Bland-Altman plots): 6h - Laboratory activities, sought for addressing real-world challenges: 30 h

Neuroengineering

Smart measurements in sports and physical activity

Neuroengineering

Frontal lessons (39 h) + 4 Labs (21 h), including 1 final "Lab-Project" whose solution will be evaluated. During the Labs the students will work in teams of 4 persons. The frequency to the Labs is mandatory to take the final examination.

Smart measurements in sports and physical activity

Half of the course will be delivered through the standard, frontal instruction method. The other half will rely on the problem-based methodology, integrating active, cooperative and experiential learning. In class, students will practice working through contents dealt with during the course and at home (flipped classroom). The course is structured upon four priorities: - Flexible learning - Technology enhanced learning - Student retention and success - Transforming assessment In addition to classic theory (50% of the course duration), smartphones will be used to deliver problem-based teaching, putting students at the centre of an active and flexible learning process. That is, students will be requested to work with experimental data collected by themselves, where and when they feel appropriate. For the sake of clarity, the following example is given. Students will be requested to address the problem of using their smartphone for the estimation of energy expenditure (technology enhanced learning). Addressing this issue requires retrieving acceleration data available in smartphones and implementing different methods for the estimation of energy expenditure available in the literature―theory and practice are integrated for the delivery of technical and conceptual issues. Data will be collected and processed in a self-paced manner and from wherever students feel most appropriate (flexible learning process). An e-learning platform (Matlab Grader) will be used for guiding students through the learning process, providing them with real-time feedback on the solutions proposed (Transforming assessment). The results obtained by the students will be anonymously shared in a server and used to discuss on potential, unsolved issues present in their uploaded solutions.

Neuroengineering

Slides, articles and laboratory assignments provided by the teacher. Data and signals acquired during lab sessions + Matlab code to get some practice on how to process signals and analyze/interpret data. Suggested book: J. Wolpaw and E. Wolpaw - "Brain-Computer Interfaces. Principles and Practice", Oxford University Press, USA

Smart measurements in sports and physical activity

Different sources were considered to prepare the content of the course, from textbooks to scientific manuscripts published in peer-reviewed journals. Mainly, the course is based on two, refence textbooks: - McArdle WD, Katch FI, Katch VL. Exercise Physiology: Nutrition, Energy, and Human Performance (International Edition). Lippincott Williams&Wilki; 8th international edition (2014). 1024 pages. ISBN: 978-1451193831 - Krzanowski WJ. An Introduction to Statistical Modelling. Wiley; Reprint edition (2010). 264 pages. ISBN: 978-0470711019 All slides prepared integrate these different sources. Whenever the content illustrated is based on a scientific manuscript, the reference is provided and the referred material can be accessed online (when freely available) or upon request to the lecturer.

Neuroengineering

Slides; Esercitazioni di laboratorio; Materiale multimediale ; Strumenti di simulazione; Strumenti di collaborazione tra studenti;

Smart measurements in sports and physical activity

Slides; Libro di testo; Esercitazioni di laboratorio;

Neuroengineering

Modalita di esame: Prova orale obbligatoria; Elaborato progettuale in gruppo; Prova scritta in aula tramite PC con l'utilizzo della piattaforma di ateneo;

Smart measurements in sports and physical activity

Modalita di esame: Prova orale facoltativa; Prova pratica di laboratorio; Elaborato progettuale in gruppo;

Neuroengineering

Exam: Compulsory oral exam; Group project; Computer-based written test in class using POLITO platform;

Smart measurements in sports and physical activity

Exam: Optional oral exam; Practical lab skills test; Group project;

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Neuroengineering

EXPECTED LEARNING OUTCOMES The student will acquire the knowledge of currently available and emerging technologies for interfacing with the human brain. The student will obtain the ability to acquire real brain signals and process these signals using Matlab and Python algorithms. Soft skills will also be developed such as: the ability to work in a team to deal with a laboratory assignment mimicking a real-world problem; the competence to analyze information in the literature and apply that information to a novel problem; and the capability to communicate effectively the methodological choices adopted to solve a problem. The exam is aimed at verifying the acquisition of the knowledge and skills described in the Expected Learning Outcomes. It will be composed of 3 parts: - LABORATORY REPORT. The Lab-team of 4 students will produce a report with a textual and/or graphical description of the methods used to solve the "Lab-problem", the results obtained, represented through Matlab figures/plots/graphs produced by the algorithms they developed during the labs, and the interpretation and discussion of the results obtained. Score: Pass/Fail. (It is mandatory to pass to access the following evaluations) (Language: English). - WRITTEN TEST with structured (multiple choice, true/false), semi-structured (exercises, table completion,...) and open-ended questions about the topics covered during the frontal lessons and the Labs. The written test lasts 1 hour. During the exam it is not allowed to keep notes, or other Course materials, while it is allowed to use a calculator. During the exam it is not allowed to keep notes, or other Course materials, while it is allowed to use a calculator. Score: up to 23/33 points (minimum acceptable score to pass: 10) (Language: English). - INDIVIDUAL ORAL EXAMINATION about teamwork project (and lab report), topics covered during the course, as well as laboratory experiences held in class. (Language: English). The final mark, expressed in thirtieths, will be obtained as the sum of the two following scores: - WRITTEN TEST: up to 23/33 points (minimum acceptable score to pass: 10) - INDIVIDUAL ORAL EXAMINATION: up to 10/33 points. If the final mark is equal to or greater than 31.5 the Laude will be assigned. The exam scores will be communicated on the didactic web portal, as well as the date on which the students will be able to view the written test and ask for explanations.

Smart measurements in sports and physical activity

Students will be assessed according to their ability in: - Computing descriptors of interest in sport and physical activity from biomechanical and physiological data collected with smartphones. - Processing these descriptors to assess exercise intensity and the metabolic systems for energy expenditure. - Using and interpreting inferential statistics for testing hypothesis sought to address real-world problems in sport and physical activity. GROUP PROJECT and a compulsory, ORAL EVALUATION will be considered to assess the knowledge and skills earned by the students during the course. GROUP PROJECT Students will be arranged into groups and will be requested to use elements dealt with during the course to address issues of relevance to the study of sport and physical activity. This process entails the: 1) identification of an open question; 2) ability to describe its applied relevance in the context of the course; 3) selection and use of the methodology necessary for addressing the question; 4) presentation and interpretation of results addressing the question. Examples of open questions will be provided to students, who will be free though to undertake any of the examples provided or to explore other questions at their will. Each group of students will be tasked with the preparation and presentation of a report detailing each of the four points just described. Guidelines will be provided to lead students through the preparation and presentation steps. Collectively, the report (16/33) and the presentation (6/33) contribute to 22/33 of the total, possible grade. ORAL EXAMINATION The oral evaluation, to be conducted after group projects have been assessed, is sought to ascertain individual students have: i) retained the knowledge transferred during the course; ii) understood how to apply the knowledge for addressing real-world problems; iii) contributed to the group project. A maximum of three (3) questions will be presented to each student, providing a maximal score of 11/33. Through group project and oral examination, students will be assessed as per their critical thinking skills. Distinction (cum laude) will be assigned to students obtaining a total score greater than 30.

Gli studenti e le studentesse con disabilita o con Disturbi Specifici di Apprendimento (DSA), oltre alla segnalazione tramite procedura informatizzata, sono invitati a comunicare anche direttamente al/la docente titolare dell'insegnamento, con un preavviso non inferiore ad una settimana dall'avvio della sessione d'esame, gli strumenti compensativi concordati con l'Unita Special Needs, al fine di permettere al/la docente la declinazione piu idonea in riferimento alla specifica tipologia di esame.