Athlete impairment level is an important factor in wheelchair mobility performance (WMP) in sports. Classification systems, aimed to compensate impairment level effects on performance, vary between sports. Improved understanding of resemblances and differences in WMP between sports could aid in optimizing the classification methodology. Furthermore, increased performance insight could be applied in training and wheelchair optimization. The wearable sensor-based wheelchair mobility performance monitor (WMPM) was used to measure WMP of wheelchair basketball, rugby and tennis athletes of (inter-)national level during match-play. As hypothesized, wheelchair basketball athletes show the highest average WMP levels and wheelchair rugby the lowest, whereas wheelchair tennis athletes range in between for most outcomes. Based on WMP profiles, wheelchair basketball requires the highest performance intensity, whereas in wheelchair tennis, maneuverability is the key performance factor. In wheelchair rugby, WMP levels show the highest variation comparable to the high variation in athletes’ impairment levels. These insights could be used to direct classification and training guidelines, with more emphasis on intensity for wheelchair basketball, focus on maneuverability for wheelchair tennis and impairment-level based training programs for wheelchair rugby. Wearable technology use seems a prerequisite for further development of wheelchair sports, on the sports level (classification) and on individual level (training and wheelchair configuration).
Athlete impairment level is an important factor in wheelchair mobility performance (WMP) in sports. Classification systems, aimed to compensate impairment level effects on performance, vary between sports. Improved understanding of resemblances and differences in WMP between sports could aid in optimizing the classification methodology. Furthermore, increased performance insight could be applied in training and wheelchair optimization. The wearable sensor-based wheelchair mobility performance monitor (WMPM) was used to measure WMP of wheelchair basketball, rugby and tennis athletes of (inter-)national level during match-play. As hypothesized, wheelchair basketball athletes show the highest average WMP levels and wheelchair rugby the lowest, whereas wheelchair tennis athletes range in between for most outcomes. Based on WMP profiles, wheelchair basketball requires the highest performance intensity, whereas in wheelchair tennis, maneuverability is the key performance factor. In wheelchair rugby, WMP levels show the highest variation comparable to the high variation in athletes’ impairment levels. These insights could be used to direct classification and training guidelines, with more emphasis on intensity for wheelchair basketball, focus on maneuverability for wheelchair tennis and impairment-level based training programs for wheelchair rugby. Wearable technology use seems a prerequisite for further development of wheelchair sports, on the sports level (classification) and on individual level (training and wheelchair configuration).
The effects of stress may be alleviated when its impact or a decreased stress-resilience are detected early. This study explores whether wearable-measured sleep and resting HRV in police officers can be predicted by stress-related Ecological Momentary Assessment (EMA) measures in preceding days and predict stress-related EMA outcomes in subsequent days. Eight police officers used an Oura ring to collect daily Total Sleep Time (TST) and resting Heart Rate Variability (HRV) and an EMA app for measuring demands, stress, mental exhaustion, and vigor during 15–55 weeks. Vector Autoregression (VAR) models were created and complemented by Granger causation tests and Impulse Response Function visualizations. Demands negatively predicted TST and HRV in one participant. TST negatively predicted demands, stress, and mental exhaustion in two, three, and five participants, respectively, and positively predicted vigor in five participants. HRV negatively predicted demands in two participants, and stress and mental exhaustion in one participant. Changes in HRV lasted longer than those in TST. Bidirectional associations of TST and resting HRV with stress-related outcomes were observed at a weak-to-moderate strength, but not consistently across participants. TST and resting HRV are more consistent predictors of stress-resilience in upcoming days than indicators of stress-related measures in prior days.
The focus of the research is 'Automated Analysis of Human Performance Data'. The three interconnected main components are (i)Human Performance (ii) Monitoring Human Performance and (iii) Automated Data Analysis . Human Performance is both the process and result of the person interacting with context to engage in tasks, whereas the performance range is determined by the interaction between the person and the context. Cheap and reliable wearable sensors allow for gathering large amounts of data, which is very useful for understanding, and possibly predicting, the performance of the user. Given the amount of data generated by such sensors, manual analysis becomes infeasible; tools should be devised for performing automated analysis looking for patterns, features, and anomalies. Such tools can help transform wearable sensors into reliable high resolution devices and help experts analyse wearable sensor data in the context of human performance, and use it for diagnosis and intervention purposes. Shyr and Spisic describe Automated Data Analysis as follows: Automated data analysis provides a systematic process of inspecting, cleaning, transforming, and modelling data with the goal of discovering useful information, suggesting conclusions and supporting decision making for further analysis. Their philosophy is to do the tedious part of the work automatically, and allow experts to focus on performing their research and applying their domain knowledge. However, automated data analysis means that the system has to teach itself to interpret interim results and do iterations. Knuth stated: Science is knowledge which we understand so well that we can teach it to a computer; and if we don't fully understand something, it is an art to deal with it.[Knuth, 1974]. The knowledge on Human Performance and its Monitoring is to be 'taught' to the system. To be able to construct automated analysis systems, an overview of the essential processes and components of these systems is needed.Knuth Since the notion of an algorithm or a computer program provides us with an extremely useful test for the depth of our knowledge about any given subject, the process of going from an art to a science means that we learn how to automate something.
A world where technology is ubiquitous and embedded in our daily lives is becoming increasingly likely. To prepare our students to live and work in such a future, we propose to turn Saxion’s Epy-Drost building into a living lab environment. This will entail setting up and drafting the proper infrastructure and agreements to collect people’s location and building data (e.g. temperature, humidity) in Epy-Drost, and making the data appropriately available to student and research projects within Saxion. With regards to this project’s effect on education, we envision the proposal of several derived student projects which will provide students the opportunity to work with huge amounts of data and state-of-the-art natural interaction interfaces. Through these projects, students will acquire skills and knowledge that are necessary in the current and future labor-market, as well as get experience in working with topics of great importance now and in the near future. This is not only aligned with the Creative Media and Game Technologies (CMGT) study program’s new vision and focus on interactive technology, but also with many other education programs within Saxion. In terms of research, the candidate Postdoc will study if and how the data, together with the building’s infrastructure, can be leveraged to promote healthy behavior through playful strategies. In other words, whether we can persuade people in the building to be more physically active and engage more in social interactions through data-based gamification and building actuation. This fits very well with the Ambient Intelligence (AmI) research group’s agenda in Augmented Interaction, and CMGT’s User Experience line. Overall, this project will help spark and solidify lasting collaboration links between AmI and CMGT, give body to AmI’s new Augmented Interaction line, and increase Saxion’s level of education through the dissemination of knowledge between researchers, teachers and students.
Er zijn veel situaties waarin het belangrijk is om de positie en/of de loopbeweging van personen te kunnen meten, zoals voor de brandweer, voor het leger, in de sport of bij revalidatie. In een aantal situaties geldt hierbij de randvoorwaarde dat je geen gebruik kunt maken van bestaande infrastructuren. GPS werkt bijvoorbeeld alleen buiten en is voor veel toepassingen niet nauwkeurig genoeg. Infrastructuur in gebouwen (zoals WiFi) werkt niet altijd bij brand, en bovendien wil je vaak (ambulant) meten in een praktijkomgeving of in een onbekend gebouw, in plaats van in een ?labomgeving?. Een interessant gegeven is dat de afzonderlijke technieken voor het oplossen van bovenstaande problemen wel bestaan, maar dat nog geen enkele partij deze heeft kunnen integreren in een bruikbaar product. Blijkbaar levert de inherente complexiteit van het onderwerp van dergelijke systemen problemen op. In het SaxShoe project onderzoeken Saxion, HvA, NHL, Universiteit Twente en het bedrijfsleven hoe we een schoen-zool systeem kunnen ontwikkelen voor het meten en op afstand monitoren van de locatie en het loopgedrag van de gebruiker in situaties waarbij standaard infrastructuur (GPS, WiFi, camera?s) ontbreekt. In het project wordt een empirische aanpak gehanteerd. Dit op basis van de constatering dat veel zaken in theorie wel zouden moeten werken, maar dat de praktijk weerbarstig is. Door cyclisch een sensorschoen te ontwikkelen worden kennisvragen beantwoord. Deze (deel)vragen betreffen kennisontwikkeling voor nauwkeurige positiebepaling op basis van inertiële navigatie, en gerelateerde vragen rond communicatie, energievoorziening, de verwerking in een schoen en de werking in praktijksituaties. Op basis van gebruikersfeedback wordt het onderzoek continue bijgestuurd (agile development). Om de aanpak concreet te maken richt het project zicht op het ontwikkelen van een brandweerlaars, als middel, niet als doel, maar wel als showcase voor de kennisontwikkeling. De ambitie is het realiseren van de norm van maximaal 10 meter afwijking na 20 minuten lopen. Hiervoor werken in het project topbedrijven die gespecialiseerd zijn in sensortechnologie samen met hogescholen en met bedrijven die gespecialiseerd zijn in de productie van schoenen en zolen. Het project levert inzicht, oplossingen en ontwerpregels op voor de problematiek die speelt bij het ontwerpen van wearables voor het meten van locatie en loopgedrag. Voor de technische bedrijven in het project biedt SaxShoe de mogelijkheid om nieuwe markten te openen voor bestaande technologieën. Voor de eindgebruikers, zoals de brandweer, biedt het concrete oplossingen voor bestaande problemen zoals de veiligheid van hulpverleners in gevaarlijke situaties.
