Cardiopulmonary signals can be detected at a distance using simple Doppler radars operating in CW mode. Tests with and without audio modulation show the feasibility of measurements with this hardware, providing a maximum measured difference to the reference of just 1.6bpm for heart rate. Tests show good correspondence of heart/respiration rate with the reference data.

This paper describes the calibration technique for a non-contact Doppler radar to monitor respiration and tidal volume in human subjects. The detected change in sensor output, reflecting the displacement of lung movement, is found to relate linearly to tidal volume. The DC reconstruction and calibration techniques are used to extract the tidal volume measurement from the radar signal. Comparison of the radar prediction and reference tidal volumes shows the average mean difference (d) to be −38.9 ml in seated subjects and 23.5 ml in supine subjects. Other chest wall displacement measurements from piezo-electric sensors at the upper and lower torso reports worsed: −40.6 ml and −54.8 ml in seated subjects and 246.6 ml and 68.5 ml in supine subjects. The predicted volumes are not significantly affected by either frequency of respiration or variation in subjects. The results in this paper show that Doppler radar could provide a valuable tool for the noncontact and unobtrusive measurement of tidal volume in human subjects.

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This paper describes experimental results for an application-specific integrated circuit (ASIC), designed for digital heart rate variability (HRV) parameter monitoring and assessment. This ASIC chip measures beat-to-beat (RR) intervals and stores HRV parameters into its internal memory in real time. A wide range of short-term and long-term ECG signals obtained from Physionet was used for testing. The system detects R peaks with millisecond accuracy, and stores up to 2 min of continuous RR interval data and up to 4 min of RR interval histogram. The prototype chip was fabricated in a 0.5 ¿m complementary metal-oxide semiconductor technology on a 3×3 mm(2) die area, with a measured dynamic power consumption of 10 ¿W and measured leakage current of 2.62 nA. The HRV monitoring system including this HRV ASIC, an analog-to-digital converter, and a low complexity microcontroller was estimated to consume 32.5 ¿V, which is seven times lower power than a stand-alone microcontroller performing the same functions. Compact size, low cost, and low power consumption make this chip suitable for a miniaturized portable HRV monitoring system.

This research presents results obtained from long range measurements of physiological motion pertaining to human cardiac and respiration activity. A pulse pressure sensor was used as reference to verify the results from radar signals. A motion detection and grading algorithm was used to detect the presence of heart rate. In addition to showing that human heart rate and respiration can be measured at distances of 21 and 69 meters respectively, the effect of antenna size, radiation pattern and gain on the range of the radar has also been studied.