Frequency modulated continuous wave (FMCW) radar, which can detect the range and small displacement of a target, has been used for contactless vital information extraction. For accurate vital sign (respiration and heartbeat) measurement, a precise selection of the target range bin, where vital information exists, is important. In this paper, an effective method for selecting the range bin with accurate vital information is proposed. The proposed method is based on the newly introduced magnitude-phase coherency (MPC) index. The experimental results show that the vital information extracted by the proposed method is more accurate than those by conventional methods, indicating that the proposed range bin selection based on MPC is an effective method for extracting accurate respiration and heartbeat rates.

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We propose a novel range-bin selection method, temporal phase coherency (TPC), to improve the accuracy of heartbeat extraction by using the frequency-modulated continuous wave (FMCW) radar.The FMCW radar has a range-resolution, and the micro-displacement at each range bin can be analyzed by calculating the phase corresponding to the range. To extract accurate heartbeat signal, selecting the range bin is important. However, the heartbeat signal, whose displacement is minute, is hard to be detected. To select the range bin with accurate heartbeat signal, we quantified the unique characteristic of heartbeat, sinus rhythm, as TPC index. In experimental results, we evaluated the accuracy of extracted heart rates for various subjects and experimental situations. The results showed that the TPC can select the range bin with more accurate heartbeat compared to the conventional methods, indicating that the TPC would be useful for the FMCW radar based vital-sign monitoring.

The decreasing trend in power spectral density (PSD) of electroencephalogram (EEG) has been shown to be related with the depth of anesthesia (DOA). However, conventional DOA indices, which utilize part of EEG frequency band, have a difficulty in quantifying the decreasing trend in the EEG PSD along the frequency axis. This paper proposes a method of effectively quantifying the characteristic change in the EEG PSD to measure the DOA. The method is based on the newly introduced ordinal PSD (O-PSD) which assigns ordinal indices to a series of values in the order of PSD magnitude. The O-PSD can capture the spectral trend along the overall frequency band robust to the EEG variation due to inter-subject dependency and measurement environment. We quantified the O-PSD pattern into a unitless index in the range 0 to 1. We compared the proposed O-PSD based index with the conventional indices for 15 subjects with injection rate of 12 mg/kg/h and 12 subjects with injection rate of 6 mg/kg/h. We evaluated the discriminative performance of the proposed index using prediction probability and Spearman's correlation coefficient. Also, we evaluated the steadiness and stability of the proposed index using the coefficient of variation. Our proposed index was shown to be superior in distinguishing consciousness and unconsciousness, and a stable and steady measure during unconsciousness. These results indicate that the O-PSD and the proposed index would be a reliable method for quantifying the DOA. INDEX TERMS Depth of anesthesia, EEG, ordinal representation, power spectral density.

Respiration and heartbeat are basic indicators of the physiological state of human beings. Frequency-modulated continuous wave (FMCW) radar can sense micro-displacement in the human body surface without contact, and is used for vital-sign (respiration and heartbeat) monitoring. For the extraction of vital-sign, it is essential to select the target range containing vital-sign information. In this paper, we exploit the coherency of phase in different range-bins of FMCW radar to effectively select the range-bins that contain accurate signals for remote monitoring of human respiration and heartbeat. To quantify coherency, the spatial phase coherency (SPC) index is introduced. The experimental results show that the SPC can select a range-bin containing more accurate vital-sign signals than conventional methods. This result demonstrates that the proposed method is accurate for monitoring of vital signs by using FMCW radar.