In recent years, wearable monitoring devices have been very popular in the health care field and are being used to avoid sport injuries during exercise. They are usually worn on the wrist, the same as sport watches, or on the chest, like an electrocardiogram patch. Common functions of these wearable devices are that they use real time to display the state of health of the body, and they are all small sized. The electromyogram (EMG) signal is usually used to show muscle activity. Thus, the EMG signal could be used to determine the muscle-fatigue conditions. In this study, the goal is to develop an EMG patch which could be worn on the lower leg, the gastrocnemius muscle, to detect real-time muscle fatigue while exercising. A micro controller unit (MCU) in the EMG patch is part of an ARM Cortex-M4 processor, which is used to measure the median frequency (MF) of an EMG signal in real time. When the muscle starts showing tiredness, the median frequency will shift to a low frequency. In order to delete the noise of the isotonic EMG signal, the EMG patch has to run the empirical mode decomposition algorithm. A two-electrode circuit was designed to measure the EMG signal. The maximum power consumption of the EMG patch was about 39.5 mAh. In order to verify that the real-time MF values measured by the EMG patch were close to the off-line MF values measured by the computer system, we used the root-mean-square value to estimate the difference in the real-time MF values and the off-line MF values. There were 20 participants that rode an exercise bicycle at different speeds. Their EMG signals were recorded with an EMG patch and a physiological measurement system at the same time. Every participant rode the exercise bicycle twice. The averaged root-mean-square values were 2.86 ± 0.86 Hz and 2.56 ± 0.47 Hz for the first and second time, respectively. Moreover, we also developed an application program implemented on a smart phone to display the participants’ muscle-fatigue conditions and information while exercising. Therefore, the EMG patch designed in this study could monitor the muscle-fatigue conditions to avoid sport injuries while exercising.

Falling is one of the causes of accidental death of elderly people over 65 years old in Taiwan. If the fall incidents are not detected in a timely manner, it could lead to serious injury or even death of those who fell. General fall detection approaches require the users to wear sensors, which could be cumbersome for the users to put on, and misalignment of sensors could lead to erroneous readings. In this paper, we propose using computer vision and applied machine-learning algorithms to detect fall without any sensors. We applied OpenPose real-time multi-person 2D pose estimation to detect movement of a subject using two datasets of 570 × 30 frames recorded in five different rooms from eight different viewing angles. The system retrieves the locations of 25 joint points of the human body and detects human movement through detecting the joint point location changes. The system is able to effectively identify the joints of the human body as well as filtering ambient environmental noise for an improved accuracy. The use of joint points instead of images improves the training time effectively as well as eliminating the effects of traditional image-based approaches such as blurriness, light, and shadows. This paper uses single-view images to reduce equipment costs. We experimented with time series recurrent neural network, long- and short-term memory, and gated recurrent unit models to learn the changes in human joint points in continuous time. The experimental results show that the fall detection accuracy of the proposed model is 98.2%, which outperforms the baseline 88.9% with 9.3% improvement.

As transmission speeds increase faster than processing speeds, the packet processing time (PPT) of a host is becoming more significant in the measurement of different network parameters in which packet processing by the host is involved. The PPT of a host is the time elapsed between the arrival of a packet at the data-link layer and the time the packet is processed at the application layer (RFCs 2679 and 2681). To measure the PPT of a host, stamping the times when these two events occur is needed. However, time stamping at the data-link layer may require placing a specialized packet-capture card and the host under test in the same local network. This makes it complex to measure the PPT of remote end hosts. In this paper, we propose a scheme to measure the PPT of an end host connected over a single-or multiple-hop path and without requiring time stamping at the data-link layer. The proposed scheme is based on measuring the capacity of the link connected to the host under test. The scheme was tested on an experimental testbed and in the Internet, over a U.S. inter-state path and an international path between Taiwan and the U.S. We show that the proposed scheme consistently measures PPT of a host.

This paper proposed a modified tone reservation (TR) technique that can reduce the peak-to-average power ratio (PAPR) of the orthogonal frequency division multiplexing (OFDM) system and is able to correct errors to avoid channel interference. The TR technique is a widely used PAPR reduction technique, which divides subcarriers of the OFDM system into two sets to generate peak-canceling signals and transmit modulated data. The subcarriers used to reduce the PAPR are called the peak reduction tone sets. The mechanism of peak-canceling signal generation is a primary factor in determining the quality of the PAPR reduction performance of the TR technique. Currently, two signal generation mechanisms exist: TR-gradient-based and TR-clipping-based techniques. Although TR techniques can effectively reduce the high PAPR in the OFDM system, TR techniques lack the ability to correct errors. Therefore, this paper combined block coded modulation codes and TR techniques to provide the modified TR techniques with error correction abilities. From the simulation results, the modified TR techniques had a superior effect on PAPR reduction performance compared with the conventional TR technique. The modified TR technique also possessed the ability to correct errors during signal transmission. 749Numerous techniques improving the high PAPR of the OFDM system have been proposed successively [6], such as amplitude clipping [7], partial transmit sequence (PTS) [8,9], selected mapping (SLM) [10,11], and tone reservation (TR) [12][13][14][15][16]. The amplitude clipping technique adopts the method of filtering signals to reduce the high PAPR. In other words, with a predetermined transmitted signal amplitude threshold, the amplitude clipping technique replaces the transmitted signal amplitude with the threshold when the transmitted signal amplitude is higher than the threshold; conversely, the original transmitted signal is used for transmission when the transmitted signal amplitude is lower than or equal to the threshold. Because the amplitude clipping technique easily induces distortion of transmitted signals, massive calculations must be conducted at the receiving end to improve distortion. Meanwhile, PTS and SLM techniques are categorized as multiple signal representation (MSR) techniques that generate multiple sets of candidate signals, using phase changes during signal transmission and selecting the signal with the minimum PAPR from candidate signals for transmission. Although PTS and SLM techniques can effectively reduce the high PAPR, side information (SI) must be transmitted from the transmission end to the receiving end to identify the candidate signal selected for transmission, thereby facilitating a precise and perfect recovery of transmitted data at the receiving end. The TR technique can also be considered as an MSR technique. However, in contrast to PTS and SLM techniques, the TR technique does not need to transmit additional SI to the receiving end. The TR technique reserves a number of the subcarriers ready to transmit data...

Solar energy is certainly an energy source worth exploring and utilizing because of the environmental protection it offers. However, the conversion efficiency of solar energy is still low. If the photovoltaic panel perpendicularly tracks the sun, the solar energy conversion efficiency will be improved. In this article, we propose an innovative method to track the sun using an image sensor. In our method, it is logical to assume the points of the brightest region in the sky image representing the location of the sun. Then, the center of the brightest region is assumed to be the solar-center, and is mathematically calculated using an embedded processor (Raspberry Pi). Finally, the location information on the sun center is sent to the embedded processor to control two servo motors that are capable of moving both horizontally and vertically to track the sun. In comparison with the existing sun tracking methods using image sensors, such as the Hough transform method, our method based on the brightest region in the sky image remains accurate under conditions such as a sunny day and building shelter. The practical sun tracking system using our method was implemented and tested. The results reveal that the system successfully captured the real sun center in most weather conditions, and the servo motor system was able to direct the photovoltaic panel perpendicularly to the sun center. In addition, our system can be easily and practically integrated, and can operate in real-time.