Adaptive motion artefact reduction in respiration and ECG signals for wearable healthcare monitoring systems

Adaptive Noise Reduction Algorithm to Improve R Peak Detection in ECG Measured by Capacitive ECG Sensors

“…The reduction of noise depends on the extent to which the correlation conditions are satisfied. Therefore, the selection of the reference signal is the most important step and has been researched to satisfy these conditions [6,17,18]. Reference noise ${\mathrm{boldn}}_i^{\prime }$, determined using the differences between the cECGs from adjacent sensors, has been suggested to improve R peak detection by reducing the noise of $EC{G}_m$ [6]: ${\mathbf{n}}_i^{\prime }={\left[r_L\left(i\right),r_L(i-1),\dots ,r_L(i-L+1),r_R\left(i\right),r_R(i-1),\dots ,r_R(i-L+1)\right]}^{\mathrm{T}},$ where L denotes half the length of the filter weight and T denotes its transpose.…”

“…It is impossible to limit motion caused by breathing, vibrations, and various other actions of daily life; therefore, noise reduction via signal processing is necessary. Many methods for noise reduction have been suggested using bandpass filters [9], wavelet filters [10,11], independent component analysis [12], injection signals [13], spectro-temporal filtering [14], extended Kalman Filters [15], and active noise cancellation (ANC) [16,17,18]. Among them, adaptive filters, which are used in ANC, can effectively reduce noise that constantly changes by updating the filter weight adaptively as the noise changes.…”

“…Among them, adaptive filters, which are used in ANC, can effectively reduce noise that constantly changes by updating the filter weight adaptively as the noise changes. ANC has been studied to find a reference signals that can improve noise-reduction performance, but the commonly used reference signal that is obtained from acceleration sensors was not efficient in removing the noise from cECGs [17,18]. …”

Comparison of Motion Artefact Reduction Methods and the Implementation of Adaptive Motion Artefact Reduction in Wearable Electrocardiogram Monitoring

“…In fact, the need for a reference input signal limits the application of adaptive filters for noise cancellation, as this usually means that specially designed hardware and related firmware are required to support the provision of the reference input signal. Although the need for a reference input signal poses a challenge to using adaptive noise cancellation, some researchers have managed to investigate the possibility of using auxiliary sensors for providing a reference input signal to adaptive filters for reducing the motion artefact in ECG signals [36,[45][46][47][48][49]. In these studies various sensors such as strain sensors, accelerometers, and optical sensors have been used as the source of reference input signal in adaptive filters.…”

Wavelet Based Method for Congestive Heart Failure Recognition by Three Confirmation Functions

“…Arrhythmia is a common clinical term for any cardiac rhythm that diverges from a normal ECG known as normal sinus rhythm. Arrhythmia is not considered in all cases as an irregular heart behavior [ 5 ] like in case of respiratory sinus arrhythmia, which is a natural periodic variation that occurs in RR intervals, corresponding to normal respiratory mechanism [ 6 ]. The heart rate, normal, slow, or fast, impulse formation may originate in pace-making cells in the sinoatrial (SA) node or ectopically [ 7 , 8 ].…”