Athlete evaluation systems can effectively monitor daily training and boost performance to reduce injuries. Conventional heart-rate measurement systems can be easily affected by artifact movement, especially in the case of athletes. Significant noise can be generated owing to high-intensity activities. To improve the comfort for athletes and the accuracy of monitoring, we have proposed to combine robust heart rate and agility index monitoring algorithms into a small, light, and single node. A band-pass-filter-based R-wave detection algorithm was developed. The agility index was calculated by preprocessing with band-pass filtering and employing the zero-crossing detection method. The evaluation was conducted under both laboratory and field environments to verify the accuracy and reliability of the algorithm. The heart rate and agility index measurements can be wirelessly transmitted to a personal computer in real time by the ZigBee telecommunication system. The results show that the error rate of measurement of the heart rate is within 2%, which is comparable with that of the traditional wired measurement method. The sensitivity of the agility index, which could be distinguished as the activity speed, changed slightly. Thus, we confirmed that the developed algorithm could be used in an effective and safe exercise-evaluation system for athletes.

Conventionally, indirect calorimetry has been used to estimate oxygen consumption in an effort to accurately measure human body energy expenditure. However, calorimetry requires the subject to wear a mask that is neither convenient nor comfortable. The purpose of our study is to develop a patch-type sensor module with an embedded incremental radial basis function neural network (RBFNN) for estimating the energy expenditure. The sensor module contains one ECG electrode and a three-axis accelerometer, and can perform real-time heart rate (HR) and movement index (MI) monitoring. The embedded incremental network includes linear regression (LR) and RBFNN based on context-based fuzzy c-means (CFCM) clustering. This incremental network is constructed by building a collection of information granules through CFCM clustering that is guided by the distribution of error of the linear part of the LR model.

Ultrasonic waves have good propagation in the human body and have been widely applied in biomedical device design without any reported side effects. Therefore, ultrasonic waves can provide an alternative method as an information carrier for body sensor networks (BSNs). This paper presents a novel wireless communication method that uses ultrasonic sound waves as a medium for healthcare systems. We investigated the feasibility of our proposal by testing it in a real digital communication experimental setup. To find an acceptable modulation method, the functionality of the proposed ultrasound-based digital communication approach was tested involving three principal modulation methods: amplitude shift keying (ASK), frequency shift keying (FSK), and phase shift keying (PSK). The modulated digital signals obtained from the experiments were compared with the simulated signals. Analysis of the results shows that ultrasonic waves are feasible and can be used for digital communication.

This letter proposes telemetry transmission for a capsule endoscope using human body communication. A passive-type radio frequency identification technique is used to transmit a telemetry signal at 13.56 MHz from the outside of a human body to a capsule endoscope. Due to passive-type telemetry receiving, no power is consumed inside the endoscope for telemetry transmission. Telemetry transmission allows bidirectional communication support for the capsule endoscopy.

In this paper, we present the properties of a communication channel used for implantable devices. The human–body communication (HBC) channel was proposed for data communication in implantable devices. The impulse response was measured using a channel-mimicking model, which mimics electrical losses caused by human body tissues. Furthermore, we compared two types of channel-mimicking models to evaluate their applicability depending on the measurement environment. The resultant impulse responses of the HBC channel showed that HBC does not cause severe changes in the channel properties even when the implantable device is rotated.

This paper proposes a channel sounder to measure the channel properties of an implantable device that transmits data from inside to outside the human body. The proposed channel sounder measures the receiving power of a signal transmitted from outside the human body. The channel sounder is equipped with a Bluetooth module that enables the wireless transmission of the receiving power outside the human body. Wireless transmission enables the channel measurement by isolating the transmitter and receiver inside the channel sounder. Using the proposed channel sounder, the channel properties can be measured without any interference between the transmitter and the receiver.