Sentence examples for wireless ecg from inspiring English sources
Study objectives: Wireless ECG transmission relies on cellular network development and network transmission priority.
This paper proposed a high energy efficient analog compressed sensing encoder for wireless ECG system, where the input analog signal is multiplied by the random matrix and the products are integrated on the Multiplying Digital-to-Analog Converter/Integrators (MDAC/Is).
In this paper, for wireless ECG signal preprocessing, we firstly applied LPF and HPF for artificial and machine noise removal; then, for on-body stress level classification, we used "DWT" for ECG signal decomposition, for better analysis in both frequency and time domain; third, six statistical features were extracted from dynamic frequency bands for stress level classification.
During this time, the emergence of many innovative sensor-based health solutions has been particularly noteworthy: from iPhone-connected glucose meters and wireless ECG heart monitors, to fertility prediction solutions, to wearable fitness activity trackers, to mobile eye exams using a smartphone's camera.
The wireless ECG electrode was also evaluated during cardiopulmonary resuscitation.
The wireless ECG electrode was operative even during DC shock.
Our objective is to improve the rate of successful first transmission of wireless ECGs.
During our study of the effect wireless ECGs have on acute coronary syndrome management, we encountered difficulty with a low first-transmission success rate.
This textile composite is integrated to a wearable carrier (T-Shirt) with a miniaturized wireless sensing platform to collect ECG signals from the human.
The emergency medical technician (EMT) in the ambulance can use a cell phone equipped with Wi-Fi and 3G wireless telecommunication modules to deliver ECG to the hospital and the cell phones of off-site senior cardiologists in real time.
Thus, the general structure of proposed scheme is shown in Fig. 1 and 2. Processes of ECG signal in the Wireless Body Area Network (WBAN) are shown in the steps 1 3: (1) ECG signal collection by on-body sensors, (2) artifacts and machine noise removal by low frequency pass filter (LPF) and High frequency pass filter (HPF), and (3) features extraction and stress level identification.
