Researchers at the Universidad Internacional Iberoamericana (International Iberoamerican University) (UNIB), Viviana Lipari and Julián Brito Ballester, together with other researchers, use a smart belt to detect, classify, and reduce anxiety using the IIoMT in the cardiac signal.
College students tend to suffer higher rates of mental health problems. The most common symptoms are depression, anxiety, and stress. Because, at the university stage, both environmental and developmental factors change at a crucial time.
That is, college students move from adolescence to adulthood and experience transitions as they search for their identity, as they adapt to social values, and as they reach physical and social maturity. Students are more prone to depression, anxiety, and stress in the first year of college, as many of them start a new life away from their families, live with other students, and become financially independent. In addition, there is the academic pressure to get good grades, generating stress.
On the other hand, the healthcare industry has undergone major changes with the implementation of artificial intelligence and the Internet of Medical Things (IoMT). This has enabled the creation of wearable sensors that help to understand human behavior and physiology, making it possible to detect anxiety in another way.
For a long time, anxiety has been detected using SAS questionnaires. Today, however, thanks to advances in technology, it is possible to detect it by observing its biological and biochemical effects, through blood pressure and heart rate, for example.
Therefore, the aim of this research has been to propose a new model for detection, estimation, and reduction of anxiety in college students, using wearable sensors and SAS, machine learning and MSY.
Process and results
In summary, the process is carried out as follows. Anxiety is detected through the use of SAS, which is an online questionnaire, together with a smart belt. The system provides a score according to established protocols. Then, the safety belt is used to detect heart rate for anxiety detection. Machine learning is used to analyze the results, and RMS and yoga are used to reduce anxiety.
This proposed new model of detection, estimation, and reduction of anxiety was tested on a group of 66 students suffering from anxiety. The results show that this method is very efficient since its results are very accurate compared to other methods. This research has shown that yoga is an effective approach to stress management. MSY may be a promising strategy for the reduction of anxiety disorder symptoms in people with anxiety disorder or for various mental illnesses.
If you want to know more about this fascinating study, click here.
To read more research, check the UNIB repository.
Finally, the Universidad Internacional Iberoamericana (UNIB) offers the Master's Degree in Project Design, Administration and Management with a specialty in Innovation and Product. This program is aimed at professionals who wish to learn about development processes (design) of innovative projects, regardless of whether they are tangible projects or not.