Smart Personalised Risk sensor and INtervention TEchnologies foR Students

Societal and health changes

The ageing society requires a change in the health care system, because it is focused on ‘curing’ rather than ‘preventing’. It has to change from the current disease care system in a true health care system, otherwise the costs for this disease care system cannot be afforded by society anymore.

ICT, new sensor technologies and new intervention systems can realise such a health care system, focusing on prevention. Many research has been started to realise these technologies.

• New sensor systems are developed, based on the newest technologies to determine relevant parameters for early diagnosis. They are combined with existing validated sensor systems to be able to realise a complete diagnostic picture of a person.

• New intervention systems are developed, also based on the newest technologies to advice for an appropriate feedback or intervention. They are also combined with existing validated intervention systems.

• ICT-platforms are developed to acquire all data, perform data processing into parameters that can be used to determine the condition of a student in his/her working environment, so enabling appropriate decisions about the best intervention feedback to the user. In addition, the continuous monitoring process will supply valuable information about the efficiency and effectiveness of the proposed intervention, thus creating a self-learning decision center.

There are four important prerequisites for a successful result:

• Users have to change from health demanding to health managing. Strategies for changing behavior that are developed by social psychology will be modified to support this transition.

• in our view, such an approach is only effective if it integrates all factors that are relevant: physical, cognitive, social, mental, lifestyle, nutrition. Existing early diagnostic screening methods are ad-hoc and directed at one specific life-style issue or one specific health risk. Sensor systems that can monitor personal health and life-style status are lacking and personal feedback and intervention systems are either not existing or rarely used.

• Unobtrusiveness is a key requirement for the acceptance of a monitoring system. For optimal effect, monitoring will be done via real-time sensing to enable direct feedback. Real-time monitoring is only effective if it does not interfere with regular work or other activities, if it requires no additional effort and will yield a very complete picture based on facts.

• Obviously, real-time monitoring leads to many ethical and societal issues. Key point is that users will be in full control of all their data and thus can decide if information will be released to third parties.

Target groups

The monitoring and intervention tools can also be used for other persons than older citizens. Students are an important group to focus on. Studying is hard work, study time is more and more restricted, so an optimal condition is required.

Project proposal

The proposal is to start a project, called SPRINTERS, Smart Personalised Risk sensor and INtervention TEchnologies foR Students.

By applying existing sensor technologies and analyzing sensor information in an ICT-dashboard, students at risk will be warned in time. By applying existing intervention technologies the imbalance between workload and -capacity can be restored. Social psychology strategies will be applied to change the behavior of students and make them responsible for their own health.

The project will be focused on the following areas:

  1. Wrong working posture.
  2. Decline of cognitive functions (e.g., attention mechanisms).
  3. Stress that could be caused by various factors, like study organization, sleep problems.
  4. Factors that aggravate or cause these problems: wrong nutrition and a lack of physical exercise.
  5. Create a health self-management attitude.


Examples of sensor systems that can be implemented:

• Current sensors in, for example, wearables, smart phones can measure activity via accelerometers, heartbeat, heart rate variability, blood saturation, mood, and environmental conditions such as noise and light.

• By measuring eye movement, pressure distribution on a seat, and how often the ‘Backspace key’ of a computer is used, alertness of students during lectures can be determined.

• The different sleep phases and thus how well someone is sleeping can readily be deter-mined. For example an accelerometer can be used as sensor to determine the frequency of movements during sleep. From that information the sleep stages can be determined.

Examples of monitoring systems that can be implemented:

• When the lecturer notice a decrease of alertness of students, (s)he can adapt his/her lecture (give a demonstration), change the environment (colder, more blue light), change the working posture (students follow the lecture standing instead of sitting), build in 2 minutes of physical exercise).

• When the sleeping pattern is not optimal, advice can be given how to improve it (while maintaining a decent student life).

• Food without sugar and with a low content of carbohydrates can improve alertness and prevent diabetes.

Project participants

  • UT, dept of Biomechanical Engineering
  • UT, dept eHealth & Wellbeing Research
  • Roessingh Research & Development
  • UMCG, dept of Rehabilitation Medicine
  • RuG, dept Social Psychology
  • SPRINT, IMDI Center of Research Excellence
  • Several SME’s