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Designing a Smart Bath Assistive Device Based on Measuring Inner Water Temperature for Bathing Temperature Monitoring.

Qun WeiSo-Myoung KangJae-Ho Lee
Published in: Sensors (Basel, Switzerland) (2020)
Today, taking a bath is not only a means to keep clean, but also to reduce fatigue and stress. However, taking a bath with hot water for a long time can also be dangerous, leading to scalding or even a heart attack. To prevent these risks, several studies based on measuring bio-signals have been conducted, but due to high prices, difficulty of use, and restricted functions, these studies' recommendations cannot be easily adopted by the public. Therefore, developing accurate methods to measure bathing temperature and bathing time should be the most direct approach to solve these problems. In this study, a smart bath assistive device based on an inner water temperature measurement function is proposed. Prior to development of the device, a bathing environment was emulated with six temperature sensors affixed to different depths to find the optimal depth for measuring bathing temperature. According to the measurement results, the device was designed in a mushroom shape with the cap part floating on the water's surface and housing the electronic components, and temperature sensors within the stem part were immersed in the water approximately 5 cm below the surface to measure the inner water temperature. Due to the low-power consuming Advanced RISC Machine (ARM) processor and waterproof design, the device is able to float in hot water and monitor the bathing temperature variation over a long period of time. The device was compared alongside a commercial analog bathing thermometer to verify the performance of temperature measurements. In addition, a compensation algorithm was developed and programmed into the device to improve the accuracy of measurements. Processed data is transmitted by Bluetooth to a dedicated Android app for data display and storage. The final results show that the proposed device is highly accurate and stable for monitoring bathing temperature.
Keyphrases
  • heart failure
  • emergency department
  • high resolution
  • deep learning
  • risk assessment
  • climate change
  • big data
  • stress induced