Wearable technology innovation: student projects in the KEE course
Do you want to live a longer, better and likely happier life? Look at your data!
Our bodies are amazing data generators: from blood pressure to glucose levels, from posture information to nerve impulses. By logging these data wearable technology promises to optimize our lives and to achieve this ambitious goal.
Wearable technology is a trending topic in society, therefore it was chosen as showcase for this year student projects in the MT2541 Knowledge Enabled Engineering course at Blekinge Institute of Technology.
About the KEE course
Engineering activities are becoming more and more data-driven. For instance, data about how a machine is operated throughout its lifecycle are precious for engineers to generate better designs. For consumer products, logging customer behavior allows uncovering hidden needs, and creating product and services that people will love. However, logging data is not enough: engineers have to turn these data into knowledge, and making sense of data is critical to take any type of design decision. This task often requires the involvement of people from different disciplines, meaning that design information has to be shared with others and collaboratively understood.
The MT2541 Knowledge Enabled Engineering in a course in the Sustainable Product Service Systems Master Programme (MSPI) that introduces students to methods and tools for engineering knowledge management, illustrating with a mix of lectures and project activities how these can be used to make faster decisions when developing new products or services (or combinations of them).
About the projects
Team Epi-Care 2.0: IMAN BAKTASH, MARTYNA SZMAGLIK, MUHAMMAD USMAN, XIN YI
The team undertook the ambitious task of exploiting wearable technology to help patients suffering from epileptic seizure. While off-the-shelves devices are able to detect these events and alert relatives, the attacks are usually too brief to be able for them to intervene. Students worked with a new device able to detect an attack and further attract attention from people in the surroundings, providing them with first help instructions in the initial phase of the seizure. The epilepsy detecting function was implemented using accelerometers connected to an Arduino® board. The user interface with instructions was further implemented and prototyped by the use of an MP3 player connected with the sensors. Lessons Learned from the project activities have been gathered through the use of Design Rationale Trees and Lessons Learned Videos.
Team Posture Analysis in Rugby: BABAK NEMAT, ADRIEN REGERAT, RYAN RUVALD
Injury prevention is an important aspect in the life of professional athletes. In disciplines featuring massive physical contact, injuries are often the sum of many events (tackles, etc.). If not recognized and treated on time, these may lead to long periods of stops. Under these premises, the team developed a wearable device to inform rugby players and their coaches about how a player holds his posture during training and games. The device features a jersey incorporating a G-sensor and three flex sensors wirelessly connected to an Arduino® board. The prototype is able to detect the spine movement of the players (i.e., the angle of the three flex sensors and the 3 axis acceleration on the neck) and to transmit this information to a tablet for easier visualization. In this way, rugby coaches can be aware of the seriousness of a tackle and to anticipate injuries by, for instance, replacing a player during a match and afterward teaching him/her on how to better hold tackles or scrums. The jersey may also help amateurs in holding a good posture since young age, to avoid physical problems when growing up. The opportunity of exploiting data mining techniques to reveal patterns in the player behavior was also explored.
Do you want to know more? Please contact the course responsible: Marco Bertoni (firstname.lastname@example.org)