Mu-Cyun Tang

Gesture Sensing Using Retransmitted Wireless Communication Signals Based on Doppler Radar Technology

This paper presents a Doppler radar based on an injection-locked quadrature receiver (ILQR) architecture that can use the wireless communication signals from an input cable or an antenna to perform gesture sensing at a short distance. Since the proposed radar does not require an illumination source, radio interference does not occur. To study parametrically the effect of the signal parameters on radar detection performance, a simulation was carried out by modeling the radar system in the discrete-time domain, and the results were verified experimentally using an actuator. In demonstrated applications, the radar uses an input 20 MHz Long-Term Evolution (LTE) signal or captures an ambient Wi-Fi signal to detect several gestures quite successfully.

Same side dual SIL-radar system for real-time vital sign monitoring with random body movement cancellation

This paper presents a Doppler radar system for real-time vital sign monitoring. To reduce the random body movement effect, this system involves two self-injection-locked (SIL) radars that are mutually injection locked to each other using a branch-line coupler and a circulator array. Moreover, the two SIL radars use different gain antennas. As a result, over 85 percent of the body movement is canceled so as to render the vital sign signals liable to appear in real time.

A single radar-based vital sign monitoring system with resistance to large body motion

This paper presents a self-injection-locked (SIL) radar system to transmit and retransmit (T&RT) a continuous wave to the opposite sides of a human body to detect vital signs with large body movement cancellation. The system can reduce the nonlinear effects caused by body movement on the vital sign signals in the process of cancelling the body motion artifacts. Moreover, a tunable phase shifter is used to improve the limitation of this system due to the environmental clutter. In the experiments, over 95% of the body motion artifacts are removed in real-time monitoring of the vital sign signals when the body moves over a range of more than a wavelength.

Displacement monitoring system based on a quadrature self-injection-locked radar technology

This paper presents a quadrature self-injection-locked (SIL) radar to detect the displacement of a moving target. Owing to the quadrature phase-switching architecture and corresponding digital signal processing techniques, this proposed system is capable of achieving excellent detection sensitivity and determining the targets Doppler phase shift without being affected by nonlinear distortion caused by the SIL phenomenon. In the experiment, a metal plate is driven by a laptop-controlled linear stage, and a 2.4-GHz ISM-band prototype is placed 1.25 m away from the target to detect its motion. As a result, the measured error is less than 3 mm for the moving plate with a peak-to-peak displacement up to 5 cm.

Wrist Pulse Rate Monitor Using Self-Injection-Locked Radar Technology

To achieve sensitivity, comfort, and durability in vital sign monitoring, this study explores the use of radar technologies in wearable devices. The study first detected the respiratory rates and heart rates of a subject at a one-meter distance using a self-injection-locked (SIL) radar and a conventional continuous-wave (CW) radar to compare the sensitivity versus power consumption between the two radars. Then, a pulse rate monitor was constructed based on a bistatic SIL radar architecture. This monitor uses an active antenna that is composed of a SIL oscillator (SILO) and a patch antenna. When attached to a band worn on the subject’s wrist, the active antenna can monitor the pulse on the subject’s wrist by modulating the SILO with the associated Doppler signal. Subsequently, the SILO’s output signal is received and demodulated by a remote frequency discriminator to obtain the pulse rate information.

A hybrid computer vision and Wi-Fi Doppler radar system for capturing the 3-D hand gesture trajectory with a smartphone

This paper presents a 3-D hand gesture capture technique using the 2D camera and Wi-Fi connection signals of a smartphone. The motion detection principle of this technique involves combining the algorithm of pixel-based computer vision and the extraction of Doppler shift from the reflected Wi-Fi signals. Moreover, a joint displacement calibration procedure is proposed to transform the camera pixel coordinates to the radar space coordinates. This technique has the advantages of lower computation resources and power consumption than the current counterparts and requires no extra cameras and RF transmission sources when used on a smartphone.

Chest-worn health monitor based on a bistatic self-injection-locked radar

This paper presents a chest-worn health monitor based on continuous-wave Doppler radar technology. To achieve low complexity, low power consumption and simultaneous wireless transmission of Doppler information, the radar architecture is bistaic with a self-injection-locked oscillator (SILO) tag and an injection-locked oscillator (ILO) based frequency demodulator. In the experiments with a prototype operated in the 2.36-2.4 GHz Medical Body Area Networks (MBAN) band, the SILO tag is attached to the chest of a subject to transform the movement of the chest due to cardiopulmonary activities and body exercises into a transmitted frequency-modulated wave. The ILO-based frequency demodulator that is located 30 cm away from the subject receives and demodulates the wave to provide a waveform associated with the chest movement. This waveform is further analyzed using short-time Fourier transform (STFT) and ultimately displayed as time-frequency spectrograms. Promisingly, the experimental results as presented in this paper reveal that the proposed monitor is capable of tracking cardiopulmonary activity of a subject during exercise.

Vital-sign detection based on a passive WiFi radar

This paper presents a passive radar to detect human vital signs with ambient WiFi signals. The proposed radar does not contain a transmitting source. Instead, it captures WiFi signals produced by a far IEEE 802.11b/g/n access point and utilizes those signals to perform vital-sign detection according to Doppler effects. The reliability of detection depends on the conditions of WiFi connection, such as downloading or non-downloading states and signal strength, which is the focus of this study.