This study develops a casual smart Na/K meter to measure the sodium and potassium in urine for hypertensive patients. To prevent hypertension from leading to cardiopathies, it is useful to reduce salt intake. The Omron Healthcare Co., Ltd. lunched the prototype, a casual Na/K meter to measure the salt intake from a diet. Nevertheless, it lacks the function to make the patients grasp the historical data. This study improves that meter by adding the NFC and developing the software application linked to Android smartphones and smart watches. Smartphones can store the data and display the historical data. Smart watches make up a part of their daily lives by alerts and messages. The concept of this study provides a continuous value for hypertensive patients. That value is similar to the learning value but it exists beyond the learning effect. For the learning value, after the subjects learn something and obtain the skills, ability, and knowledge, the value is fixed and completed. On the other hand, for the continuous value, the learning value is also included and the subjects receive the learning value; however, they need to continue that behavior until death. If they stop reducing salt intake, they return to hypertension. If they get satisfied with obtaining the learning value and stop their actions, they never receive the continuous value that exists beyond the learning value. The continuous value is brewed in the transtheoretical model of health behavior change. Throughout these stages, to encourage their behavioral change and obtain the continuous value, this study employs Fogg’s theory applied to developing the communication devices. The application stocks the historical data and displays it on the smartphones. The smart watches classify alerts into five colored displays from green (good) to red (bad). It can be helpful for the patients to make the reduction of salt intake as their dietary habit. In the future, the appli cation needs to be improved for making patients adapt with their diets and motivations.
All Science Journal Classification (ASJC) codes
- Mechanical Engineering
- Industrial and Manufacturing Engineering