Phase III: Project abstract 'Grupo Pulso'

Stress Adaptive Manager (SAM) is a technological solution composed of a mobile application (for patients and their caregivers) and a website platform (addressed to healthcare professionals) with the aim of empowering surgical patients throughout their Patient Journey: from the moment they are notified that they must undergo a certain surgery, until they are definitively discharged. With SAM, patients can better manage their stress derived from surgery, being able to always measure it using traditional or innovative methodologies and taking steps to reduce it.

SAM’s app is personalized depending on the following features: the role of its user (patient/caregiver), the disease and type of surgery the patient will undergo, the stage of the surgical journey he/she is at, the medical center in which he/she is treated, and whether the patient is pediatric or adult. The elements composing the app are:

  1. Innovative tools to register and analyze the user’s level of stress or pain through standard VAS scale, and innovative machine-learning based algorithms.
  2. Solutions to reduce the stress:

                        1. Virtual reality content from the hospital environment,
                        2. Biofeedback / mindfulness techniques to reduce stress,
                        3. Listening to personalized music according to the user’s stress level,
                        4. Personalized information to empower the user and improve his/her hospital experience, 
                        5. Tools to turn the hospital environment into a more comfortable space,
                        6. Communication and reminders tools between patients, caregivers, and healthcare 
                        7. Interactive hospital map tool for users to guide them through the hospital facilities.

 In addition, thanks to SAM’s website, healthcare professionals can carry out a much more exhaustive follow-up of their patients throughout the surgical process.

To find a more detailed explanation of the project view our video

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement no. 727585.

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