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Smart measurements in sports and physical activity

01FVVMV

A.A. 2022/23

Course Language

Inglese

Course degree

Master of science-level of the Bologna process in Ingegneria Biomedica - Torino

Course structure
Teaching Hours
Lezioni 49,5
Esercitazioni in laboratorio 10,5
Teachers
Teacher Status SSD h.Les h.Ex h.Lab h.Tut Years teaching
Martins Taian   Ricercatore a tempo det. L.240/10 art.24-B ING-INF/06 49,5 0 4,5 0 1
Teaching assistant
Espandi

Context
SSD CFU Activities Area context
ING-INF/06 6 B - Caratterizzanti Ingegneria biomedica
2022/23
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.
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.
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.
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.
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.
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.
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
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
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.
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.
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.
Different sources were considered to prepare the content of the course, from textbooks to scientific manuscripts published in peer-reviewed journals. Mainly, theory 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, covering all topics dealt with during the course. 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. Students not familiar with Matlab would benefit from following the free, Matlab Onramp Course
Modalità di esame: Prova orale obbligatoria; Elaborato progettuale in gruppo;
Exam: Compulsory oral exam; Group project;
Gli studenti e le studentesse con disabilità 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'Unità Special Needs, al fine di permettere al/la docente la declinazione più idonea in riferimento alla specifica tipologia di esame.
Exam: Compulsory oral exam; Group project;
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.
In addition to the message sent by the online system, students with disabilities or Specific Learning Disorders (SLD) are invited to directly inform the professor in charge of the course about the special arrangements for the exam that have been agreed with the Special Needs Unit. The professor has to be informed at least one week before the beginning of the examination session in order to provide students with the most suitable arrangements for each specific type of exam.
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