Health and wellness monitoring is a primary way to manage personal health and awareness for a healthy lifestyle. Many wearable activity tracking devices, smart watches, and smartphone applications collect and analyze data from bodily sources. Other types of devices used to monitor vital signs can help the wearer manage health issues but can limit the wearer’s mobility or cause discomfort if worn continuously. These restrictions have prompted a growing interest in developing noncontact, wireless devices to detect vital signs, especially for people who are unconscious, sleeping, very young, elderly, or infirm. This article explains why 24 GHz Doppler radar sensors are useful for such devices and highlights some of the features suitable for meeting these applications.
Doppler Radar Technology Essentials
Historically, the 23~25 GHz frequency range has long been utilized for applications like land mobile communication, maritime mobile communication, space/satellite communication, radio astronomy, broadcasting, amateur radio/satellite, and standard frequency and time signal.
In the United States, the unlicensed radio band usable for such radar applications is defined as 24.075 GHz ~ 24.175 GHz (CFR 15.245) and 24.000 GHz ~ 24.250 GHz (CFR 15.249), and the field strength of the fundamental signal is limited to 2,500 mV/m and 250 mV/m, respectively. A Doppler radar sensor that is compliant with the CFR 15.245 standard is a suitable option for data collection in health and wellness monitoring.
The Doppler effect is a known physical theory, commonly noticeable by the apparent, variable sound effect from a traveling ambulance or police car’s siren. A listener hears a higher siren pitch while the vehicle approaches and a lower siren pitch while the car recedes away from the listener. This high-to-low tone transition is very clear.
The 24 GHz Doppler radar utilizes the same process and transforms these sounds to a radio wave. A Doppler radar sensor uses continuous wave modulation (CW mode) to generate a constant frequency radio signal that is transmitted through a TX antenna. It then detects the frequency difference by receiving the reflected radio signal through the RX antenna for the speed of the object (see Figure 1).
Gaining 1 Hz of Doppler effect from a transmitted frequency to reflection frequency requires half the radio wave length of movement per second. For example, with a 24.100 GHz radar frequency, one wavelength is roughly equal to 1.24 cm (half inch), and thus, 1 Hz of Doppler effect is equivalent to 0.62 cm (quarter inch)/sec movement of the object.
Using the same frequency condition, the Olympic-class marathon running speed of 21 Km/h will generate around 942 Hz of Doppler effect, and the natural human walking speed of 4 Km/h will generate 179 Hz of Doppler effect (see Figure 2).
Sensing Human Vital Signs
A Doppler radar sensor can detect minute movements of the human body. For example, even though a heartbeat occurs inside the human body, its movement is observable at the body’s surface through the change in blood pressure. Although these movements are just a few millimeters per heartbeat at most, it is an involuntary movement that translates to a higher Doppler effect, which provides a signal capable of being analyzed by an external circuit and host system software.
Similarly, respiration is detectable at the body’s surface with movements larger than a heartbeat. Respiration is primarily a slow movement and can be detected using the Doppler effect, but it may require utilizing another parametric character of the reflecting signal. For example, the slowly changing amplitude of the synchronized inhale and exhale motion may be an alternative source to use in parallel. Figure 3 illustrates the trend of the reflected signal strength from the inhale and exhale movement. This is subject to the distance from the Doppler radar sensor to the target, which may not be significant.
Figure 4 shows a sample image of detection results using a 24 GHz Doppler radar sensor with embedded algorithm to identify actual heart and respiration rate from the Doppler effect. In this example, the inhalation and exhalation are intentionally exaggerated for illustrative purposes. The red top waveform plot indicates the detected heart rate signal, and the blue bottom waveform plot indicates the detected respiration rate signal. The overlapping green and magenta color plot in the middle indicates the radar sensor output raw signals I and Q.
Detecting heartbeat and respiration rates requires some level of signal analytic capability, and the actual implementation may require further optimization. That said, this example illustrates limitless possibilities for using Doppler radar to detect many other human vital signs, beyond heartbeat and respiration rates, to expand noncontact wellness and healthcare monitoring applications.