Non-contact Breathing Rate Detection Based on Time of Flight Sensor

Area of Science:

• Biomedical Engineering
• Mobile Health Technology
• Sensor Technology

Background:

• Current breathing rate detection methods often require physical contact, are uncomfortable, or are too expensive for daily use.
• Smartphones, with their widespread adoption, present a promising platform for accessible health monitoring.
• Time-of-Flight (ToF) sensors are increasingly integrated into smartphones, offering new sensing capabilities.

Purpose of the Study:

• To demonstrate the feasibility of using off-the-shelf smartphone ToF sensors for non-contact breathing rate detection.
• To develop and validate a method for extracting respiratory rate from ToF signals.
• To compare the accuracy of the proposed ToF-based method against a temperature sensor-based method.

Main Methods:

• Utilized the Time-of-Flight (ToF) lens integrated into smartphones to capture subtle movements associated with respiration.
• Developed a signal processing algorithm to extract breathing rate from the raw ToF data.
• Compared the smartphone ToF-derived breathing rate with measurements from a reference temperature sensor in 6 healthy adults at rest.

Main Results:

• The proposed method successfully captured breathing rate using smartphone ToF signals without physical contact.
• The mean absolute error between the ToF-based method and the temperature sensor was 0.009 Hz.
• The mean absolute percentage error was 3.56%, and the root mean squared percentage error was 6.64%, outperforming other non-contact methods.

Conclusions:

• Smartphone ToF sensors can be effectively utilized for non-contact, accurate breathing rate monitoring.
• The developed method offers a low-cost, user-friendly alternative for continuous or periodic respiratory monitoring.
• This technology has the potential to significantly improve remote and daily health surveillance.