Motion artifact removal based on periodical property for ECG monitoring with wearable systems

Review on Smart Electro-Clothing Systems (SeCSs)

“…Except the display subsystems, in most of the cases, the rest of these subsystems are accumulated within an electronic board in as miniaturised a form as possible to finally connect to textile components [13,14]. Different sensing units that potentially form sensing subsystem of an SeCS can be motion, gesture, and position sensors, temperature and other bio-vital sensors, location sensor, interaction and environmental sensors, and sensors for detecting surrounding objects [4][5][6][7][8][9][10][11][12][13][14]. The common sensors for motion, gesture, and positions are accelerometer, magnetometer, and gyroscope.…”

“…Wrist-worn wearable devices (smart watches and fitness trackers) experienced a growth of 18% and 7% in the United Kindom during the period of 2016-2017 and 2017-2018, respectively [3]. With the advent of conductive threads, textile structures either woven or knitted from conductive yarns, and conductive print-inks including those from graphene, it is now possible to produce or integrate light-weight weight sensors onto textiles to monitor health, fitness, and performance in a non-clinical environment, in daily-life, and in sport-training conditions [4][5][6][7]. An overview of the recent developments in wearable sensors for remote health monitoring is presented by Majumder et al [8], while the smart sensors and fusion systems for sports and biomedical applications are reviewed by Mendes Jr. et al [9].…”

ECG Waveform Classification Based on P-QRS-T Wave Recognition

“…As verified in the simulated noise ECG signal tests, the QRSMR outputs with severely contaminated ECG signals have an increase in the correlation with its original cleaning signals from 40% to almost 80%, demonstrating the improved QRSMR noise elimination capability. In addition, in the tests of the real ECG signals measured in volunteers with a flexible ECG control device developed at Fudan University, QRSMR is able to recover P and T waves from the contaminated signal, which shows its improved performance in the reduction of artifacts comparing with the adaptive filtering method and other methods based only on empirical decomposition [38].…”

Review on Smart Electro-Clothing Systems (SeCSs)

“…Wrist-worn wearable devices (smart watches and fitness trackers) experienced a growth of 18% and 7% in the UK during the period of 2016-2017 and 2017-2018 respectively [1]. With the advent of conductive threads, textile structures either woven or knitted from conductive yarns, conductive print-inks including those from graphene, it is now possible to produce or integrate light-weight sensors onto textiles to monitor health, fitness and performance in non-clinical environment, in daily-life and in sport-training conditions [2][3][4][5]. An overview of the recent developments in wearable sensors for remote health monitoring is presented by Majumder et al [6]; while the smart sensors and fusion systems for sports and biomedical applications are reviewed by Mendes Jr. et al [7].…”