ABSTRACT The conditions of the environment where a person lives have a great impact on his wellness state. When buying a new house, it is important to select a place that aids in improving the wellness state of the buyer or, at least, keeps it at the same level. A deficient wellness state implies an increase of stress and the appearance of some effects associated with it. Heart rate variability (HRV) allows measuring the stress or wellness levels of a person by measuring the difference in time between heartbeats. A low HRV is related to high stress levels whereas a high HRV is associated with a high wellness state. In this paper, we present a system that measures the wellness and stress levels of home buyers by employing sensors that measure the HRV. Our system is able to process the data and recommend the best neighborhood to live in considering the wellness state of the buyer. Several tests were performed utilizing different locations. In order to determine the best neighborhood, we have developed an algorithm that assigns different values to the area in accordance with the HRV measures. Results show that the system is effective in providing the recommendation of the place that would allow the person to live with the highest wellness state. INDEX TERMS Wellness, heart rate variability, heart rate, stress, BigData, real estate.
Laquesta et al. implemented in REF a system that recommends the best neighborhood to live in based on the wellness state of the user.
System to Recommend the Best Place to Live Based on Wellness State of the User Employing the Heart Rate Variability
IEEE Access
IEEE Access
Computer Science