The subject must be motionless for conventional radar-based non-contact vital signs measurements. Additionally, the measurement range is limited by the design of the radar module itself. Although the accuracy of measurements has been improving, the prospects for their application could have been faster to develop. This paper proposed a novel radar-based adaptive tracking method for measuring the heart rate of the moving monitored person. The radar module is fixed on a circular plate and driven by stepping motors to rotate it. In order to protect the user’s privacy, the method uses radar signal processing to detect the subject’s position to control a stepping motor that adjusts the radar’s measurement range. The results of the fixed-route experiments revealed that when the subject was moving at a speed of 0.5 m/s, the mean values of RMSE for heart rate measurements were all below 2.85 beat per minute (bpm), and when moving at a speed of 1 m/s, they were all below 4.05 bpm. When subjects walked at random routes and speeds, the RMSE of the measurements were all below 6.85 bpm, with a mean value of 4.35 bpm. The average RR interval time of the reconstructed heartbeat signal was highly correlated with the electrocardiography (ECG) data, with a correlation coefficient of 0.9905. In addition, this study not only evaluated the potential effect of arm swing (more normal walking motion) on heart rate measurement but also demonstrated the ability of the proposed method to measure heart rate in a multiple-people scenario.

Heart rate measurement for mm-wave FMCW radar based on phase analysis comprises a variety of noise. Furthermore, because the breathing and heart frequencies are so close, the harmonic of the breathing signal interferes with the heart rate, and the band-pass filter cannot solve it. On the other hand, because heart rates vary from person to person, it is difficult to choose the basic function of WT (Wavelet Transform). To solve the aforementioned difficulties, we consider performing time-frequency domain analysis on human skin surface displacement data. The PA-LI (Phase Accumulation-Linear Interpolation) joint ICEEMDAN (Improved Complete Ensemble Empirical Mode Decomposition with Adaptive Noise) approach is proposed in this paper, which effectively enhances the signal's SNR, estimates the heart rate, and reconstructs the heartbeat signal. The experimental findings demonstrate that the proposed method can not only extract heartbeat signals with high SNR from the front direction, but it can also detect heart rate from other directions (e.g., back, left, oblique front, and ceiling).

The environment surrounding automotive technology is undergoing a major transformation. In particular, as technological innovation advances in new areas called “CASE” such as Connected, Autonomous/Automated, Shared, and Electric, various research activities are underway. However, this is an approach from the standpoint of the automobile centered, and when considering the development of a new automobile society, it is necessary to consider from the standpoint of “human centered,” who are users, too. Therefore, this paper proposes the possibility of technological innovation in the area of “Another CASE” such as Comfortable, Accessible, Safety, and Enjoy/Exciting, and introduces the contents of some interesting researches.

In this paper, a Happiness Cups (H-cups) system is proposed to bi-directionally convey the holding-cup motions of paired cups between two remote users. To achieve this goal, the H-cups system uses three important components. Firstly, paired cups are embedded with accelerometers and gyro sensors to transmit the three-dimensional acceleration and angular signals to a motion recognizer application. This application is designed on an Android phone. The sensors then receive the remotely recognized motions and flash a specific color on the local cup's RGB-LED via Bluetooth. Secondly, the application considers holding-cup motion recognition from the cup based on long short-term memory (LSTM) and sends the local recognized motion through an intermediate server to transmit to the remote paired cup via the internet. Finally, an intermediate server is established and used to exchange and forward the recognized holding-cup motions between two paired cups, in which five holding-cup motions, including drinking, horizontal shaking, vertical shaking, swaying and raising toasts are proposed and recognized by LSTM. The experimental results indicate that the recognition accuracy of the holding-cup motion can reach 97.3% when using our method.

This paper gives a survey of intelligent computational techniques in medical and health care system. First, we briefly describe diagnosable techniques in medical image processing. Next, we demonstrate two ultrasonic surgery support systems for orthopedic and rectum cancer surgeons. In them, intelligent computational technique plays a primary role. Third, computational techniques are introduced in human health care system. Usually, this goal is not to apply clinical treatment but to home use to pay consciousness to health. In it, a simple ECG and respiration meter are introduced with a mat sheet which detects heart rate and respiration. Finally, a medical big data application is introduced, that is, body weight prediction is shown based on autoregressive model. Thus, we show that intelligent computing is effective and essential in modern medical and health care system.

In order to prepare the health care industry for an increasingly aging society, a ubiquitous health care infrastructure is certainly needed. In a ubiquitous computing environment, it is important that all applications and middleware should be executed on an embedded system. To provide personalized health care services to users anywhere and anytime, a context-aware framework should convert low-level context to high-level context. Therefore, ontology and rules were used in this research to convert low-level context to high-level context. In this paper, we propose context modeling and context reasoning in a context-aware framework which is executed on an embedded wearable system in a ubiquitous computing environment for U-HealthCare. The objective of this research is the development of the standard ontology foundation for health care services and context modeling. A system for knowledge inference technology and intelligent service deduction is also developed in order to recognize a situation and provide customized health care service. Additionally, the context-aware framework was tested experimentally.

A novel sensor system of denture base type was developed for simultaneous monitoring of salivary pH and tissue temperature in the oral cavity. Fundamental components of the monitoring system, sensor devices and sensor configuration are showed in this paper. The sensor units consist of IrO2 electrode and thermistor circuit implanted in the denture base that is tightly fixed in the oral cavity. The signals are transmitted by PFM-FM telemeter system that can be used for health care of the aged people without restraint of their daily behavior while at work, sleeping and even at exercise. Some of results concerning the basic characteristics of the sensor system and continuously monitored physiological data were obtained from the preliminary experiments. Availability of the whole system and monitoring method was discussed.