Designing for People, Sports and Vitality (DfPSV)
Recent developments in Sensor Technology, Real Time Data Acquisition and (unobtrusive) data representation have opened new and innovative opportunities to support people during their daily life. It is now possible to acquire, analyze and represent data on a real-time 24/7 basis. Although in some application areas the use of these new technologies can be considered controversial there are fields where these possibilities are widely appreciated and this creates new possibilities both for research as well as for product development.
One of those fields is Leisure Time Sports/Vitality. Where in top-sports very expensive and dedicated equipment (+ coaches / support staff) is available to monitor and support elite sports people during both training and matches/events this, highly personalized, analysis is usually not available for recreational sports people or for people who want to lead a more active, vital lifestyle.
In recent years, there has been an exponential growth of individual and unorganized sport (outside sports clubs) creating flexibility for people to combine their (individual) sports with work and family life. Hence, the thresholds and barriers to get involved in sports are lessening more and more. But in this do-it-yourself trend with a low threshold there is a lack of social support and coaching. For less experienced sport participants this often results in high drop-out rates due to injuries, lack of motivation and other constraints. Industrial design could respond to the growing numbers of (i) physically inactive people, and (ii) less experienced sport participants who require support. However, both the acquisition, representation and visualization of data among recreational sports participants and less-active people holds scientific and design challenges. Among others, (i) this group of people is extremely heterogeneous in terms of physical abilities, body perceptions, motivational drivers and attitudes, and (ii) they cannot be approached through experimental lab settings and obtrusive measurements.
TU/e envisions a world where these fundamental challenges are addressed with the aid of interactive and evolving product-service-systems. The department aims at employing state-of-the-art technology to design novel concepts to empower people towards physical, mental, emotional and social well-being.
One of the “EU Grand Challenges” is “Health, demographic change and wellbeing” available to everybody. Currently we see that, on one hand, life expectations are rising. On the other hand this happens with a low quality of life, especially towards the end, due to often highly stressful chronic diseases and against very high costs for both the patients as well as for society in general.
Since there is a proven and strong relation between leading an active lifestyle during life and the risk of chronic diseases during later life it is a very attractive proposition to encourage and support people to lead a more active lifestyle. The problem is that, in our current daily life, these activities are for many people difficult to embed. Especially (but not exclusively) in the age between 20 and 67, for many people daily life is centered around efficiency; how to manage often conflicting demands relating to work, social- and family-life with maximum efficiency in a minimal amount of time. Activities that in earlier times assured a certain amount of physical activities (ensuring the availability of food, transport, etc) can now be done with a minimum effort against reasonable costs. This has resulted in a situation where, for large groups of people, physical activities have largely disappeared from their daily life and, due to their busy agendas, they are barely aware of it.
Recent developments in sensor technology, data analytics and data representation have made it possible to, unobtrusively, measure physical activities for large groups of people, if necessary or required on a 24/7 basis. This information can be used to
a) Make people aware of their (lack of) physical activities
b) Indicate the possible consequences this may have on their (future) health
c) Enable, support or nudge these people to lead a more active lifestyle
Although the data obtained can have a considerable value for the people involved it is a topic where ethical and legal considerations are of imminent importance. Therefore these topics are explicitly addressed as part of this USE learning line.
Based upon the above, the USE learning line ‘Designing for People, Sport and Vitality’ is closing a gap between engineering, design and human movement sciences. Based on recent developments in sensor technology, data analytics, data representation and persuasive design it will explore the design space in recreational sports and physical activity. It requires a distinctive approach and envisioning of societal and personal needs as well as a strong sense of the ethical and legal boundaries involved.
The three courses in this learning line have one central theme: how to design personalized and data-intense products that support individual recreational sporters in both the motivational as well as in the physical aspects of enjoying their sport. It consists of three, closely connected, courses:
- Understanding recreational sporters
- Possibilities to acquire and represent data from/to these sporters
- Using the above to design and test an actual system that can be used by these sporters.
In this USE learning line students will acquire and use the following knowledge and skills:
- Insight in (leisure time) sports, physical activity and vitality as well as in the underlying motivational principles (sociology & psychology) and apply this insight in actual design principles that can be used in this field.
- Insight in- and actual use application of- recent developments in unobtrusive data acquisition and visualization /representation through embodied sensors and actuators (engineering) as well as in the corresponding methods for data analysis (data science)
- Insight in and application of recent design strategies in order to design, make and validate systems to support “physical activities / vitality” in the context of daily life.
- Course 1 will provide a theoretical basis both of the research challenges as well as of the available methodology. It will establish the required psychological and sociological basis.
- Course 2 will focus especially on the technical/engineering/computer science aspects of the learning line. It will focus on how to obtain longitudinal real-life datasets in a semi-open environment. Next to this it will address FAIR data principles (data should be Findable, Accessible, Interoperable and Re-usable) and data-ethics.
- Course 3 will have, as primary focus, the actual execution of field experiments with selected groups of (recreational) sports people in a semi-open Experiential Design Landscape.
Each course will comprise of an intermediate and final assessment moment, and make active use of formative (feedback) and summative assessment approaches - depending on the type of learning activity. As a horizontal line, ethics will be addressed and assessed in each of the courses (making a connection with the USE Basic content (cf. psychology, ethical cycle, technology (data+sensors), design).
In the following, we will explain the setup of the different components in more detail.
1: Introduction to (leisure time sports), physical activity and vitality (Prof. dr. Steven Vos, prof.dr. Wijnand IJsselsteijn)
In this first course, the students will be introduced to the basic concepts in sport, physical activity (PA) and vitality. They will get a better understanding of the definitions used in research and policy. Students will generate a more general understanding of users’ needs and requirements (Why do people partake in sports? Why not? How physically active are people? What are their main drivers and thresholds?, etc.) and the role technology might play in stimulating or reducing physical activity. Emphasis will also be given to a more societal perspective. We will go more in to depth on societal changes, trends in sports and physical activity and policy perspectives.
A mix of theory, examples and case studies and practice will be used to get a better understanding. The course will start with a small project in which the students will explore the topic of this USE learning line in a city context (explorations to get a better understanding of the end-users in Genneper Parken). From this course students may select a certain target group that can be used as carrier in the subsequent courses.
The students will write a research proposal/position paper (including a personal reflection as well as an ambition statement for the rest of the USE learning line)in which they address the contribution of modern sensor systems for physical (in) activity as part of daily life and propose a strategy how to utilize this in a realistic context such as will be used in course 3 (EDL). Ethical aspects have to be addressed. Ethiek, Technologie
The learning objectives can be found in the field of design, social sciences, human movement sciences and law/ethics:
- Students will learn to understand societal challenges regarding physical inactivity
- Students will learn to analyze the needs of groups consisting group of extremely heterogeneous people (physical abilities, body perceptions, motivational drivers and attitudes)
- Students will acquire insight in and understanding of real world research design process (incl ethics)
- Students will be able to develop a research plan for in the specific context of their project
- Students will learn how to deal with the ethical implications of addressing issues which could harm users which are more vulnerable in terms of their own body perception, mental state and knowledge about exercise and health
- Students will learn to receive and provide feedback on group work
- Students will learn to formulate and evaluate personal goals
2: Data acquisition and visualization through embodied sensors (Prof. dr. ir. Aarnout Brombacher, dr. Natalia Siderova)
In the last five to ten years, developments in ICT and sensor technology have resulted in a wide range of ‘technological gadgets’ such as health related smartphone applications, activity trackers and sports watches. One of the game changers in these recent advances in technology is their ability to track behaviors in daily life situations over time, and across a large number of users. The capturing of temporally, behaviorally and ecologically contextualized data from their users generates large datasets. Trend and pattern analysis (i.e., data science) creates more understanding about the correlations and associations between individual, social and environmental factors and physical activity and health as well as other aspects of life, such as wellbeing.
In this course students will have to design a sensor/data acquisition system that can be used in an actual (field-)research context, such as will be used in course 3, to acquire data, process data and allow several forms of data-analytics to get an insight in physical activity patterns of the people involved as well as the underlying parameters. In contrast to the course “Making sense of sensors” (DAB100, mandatory for ID students) the focus in this course will be be far more on processes of data acquisition in groups of people discussed/defined in the first course in this USE learning line. (higher ISO/OSI level data). Next to this there will be a strong emphasis on data representation for a given target group. Also in this course principles of FAIR data apply.
The students will define (feedback 1), design (feedback 2) and use (feedback 3) a data acquisition and representation system relating to health/vitality/wellbeing of a selected target group. They will deliver a system + a report on the acquisition and analysis of the data.
- Students will acquire insight in and understanding of real world research design process (incl ethics)
- Students will be able to design and Implement a data acquisition system that can be used for a selected target group
- Students will be able to use principles of field data acquisition (sensors), transmission and data analytics
- Students will be able to apply and integrate quantitative research methods in real life situations
- Students will be able to design and Implement a data representation (visual or otherwise) system that meets the personalized needs of the earlier defined target group
- Students will be able to interpret, combine and translate qualitative and quantitative data/information
3: Designing for PSV in a real-life setting (dr. ir. Carl Megens)
In this third course the obtained knowledge and skills learned in the previous courses will be integrated and brought into practice. The focus of this course is to design people-environment interactions in which the choice for physical activity or sports is self-evident. You will learn how to prototype for behavior change, integrate and apply different research methods and evaluate a real-life research process. With the use of experimental design landscapes (EDLs) you will work on a real-life case study commissioned by a client (e.g. Heijmans, Municipality of Eindhoven, Tu/e, UMCU or Fontys). These case studies will be presented as problem-based learning projects in a multidisciplinary team setting.
You will be assessed on your ability to apply design research skills to develop, present and articulate a collaborative design solution in a real-life setting. You will learn to apply and integrate quantitative and qualitative research methods and translate your findings into a design to enhance the vitality of people.
The deliverables for this course are 1) a working prototype, 2) a research article, 3) a poster presentation, 4) a group reflection and 5) a personal reflection.
- Learn to understand and use concepts such as Experiential Design Landscapes for doing experiments in (near) real-life environments
- Understand requirements/models for prototype/probes to be used in (near) real life environments
- Design and implement working people-environment interaction prototype
- Formulating and assessing design research objectives and conceptual models
- Applying and integrating quantitative and qualitative research methods in real life situations
- Interpret and translate qualitative and quantitative findings
Prof. dr. Steven Vos Human Movement Sciences / Social Psychology
Prof. dr. Wijnand IJsselsteijn Motivational Psychology / Human Technology Interaction
Prof.dr.ir. A.C. Brombacher Industrial Design / Electrical Engineering / Computer Science
Dr. Natalia Siderova Computer Science/Data Analytics
Dr. ir. Carl Megens– Industrial Design
Ida Damen (MSc) – Industrial Design / Movement Sciences