A method for physiological parameter monitoring, the method comprising: providing a physiological indicator signal to a mobile communication device, analyzing, using the mobile communications device, the physiological indicator signal to obtain measurements of one or more physiological parameters; and detecting, using the mobile communications device, effects of motion artifacts in the measurements of the one or more physiological parameters and deciding whether to retain the measurements; characterized in that the step of detecting effects of motion artifacts in the measurements comprises: a. band pass filtering, using a band pass filter with cut-off frequencies of 0.1 Hz and 10 Hz, and polynomial detrending a segment from the measurement of one physiological parameter; wherein a band pass filtered and polynomial detrended segment is hereinafter referred to as a preprocessed segment; b. obtaining a value of at least one indicator of volatility for the preprocessed segment; c. including the segment in analyses of physiological measurements, if comparison of the value of the at least one indicator of volatility with a predetermined threshold indicates noise/motion artifacts are not present; the at least one indicator of volatility being at least Shannon entropy for the preprocessed segment; wherein the Shannon entropy is given by SE = − ∑ i = 1 k p i ∗ log p i log 1 k where i represents the bin number, and p ( i) is the probability distribution of signal amplitude of the preprocessed segment; and d. selecting another segment of the signal from the physiological measurement and proceeding to step (a), if the value of the at least one indicator of volatility is less than a predetermined threshold and another segment is available. providing a physiological indicator signal to a mobile communication device, analyzing, using the mobile communications device, the physiological indicator signal to obtain measurements of one or more physiological parameters; and detecting, using the mobile communications device, effects of motion artifacts in the measurements of the one or more physiological parameters and deciding whether to retain the measurements; characterized in that the step of detecting effects of motion artifacts in the measurements comprises: a. band pass filtering, using a band pass filter with cut-off frequencies of 0.1 Hz and 10 Hz, and polynomial detrending a segment from the measurement of one physiological parameter; wherein a band pass filtered and polynomial detrended segment is hereinafter referred to as a preprocessed segment; b. obtaining a value of at least one indicator of volatility for the preprocessed segment; c. including the segment in analyses of physiological measurements, if comparison of the value of the at least one indicator of volatility with a predetermined threshold indicates noise/motion artifacts are not present; the at least one indicator of volatility being at least Shannon entropy for the preprocessed segment; wherein the Shannon entropy is given by SE = − ∑ i = 1 k p i ∗ log p i log 1 k where i represents the bin number, and p ( i) is the probability distribution of signal amplitude of the preprocessed segment; and d. selecting another segment of the signal from the physiological measurement and proceeding to step (a), if the value of the at least one indicator of volatility is less than a predetermined threshold and another segment is available. a. band pass filtering, using a band pass filter with cut-off frequencies of 0.1 Hz and 10 Hz, and polynomial detrending a segment from the measurement of one physiological parameter; wherein a band pass filtered and polynomial detrended segment is hereinafter referred to as a preprocessed segment; b. obtaining a value of at least one indicator of volatility for the preprocessed segment; c. including the segment in analyses of physiological measurements, if comparison of the value of the at least one indicator of volatility with a predetermined threshold indicates noise/motion artifacts are not present; the at least one indicator of volatility being at least Shannon entropy for the preprocessed segment; wherein the Shannon entropy is given by SE = − ∑ i = 1 k p i ∗ log p i log 1 k where i represents the bin number, and p ( i) is the probability distribution of signal amplitude of the preprocessed segment; and d. selecting another segment of the signal from the physiological measurement and proceeding to step (a), if the value of the at least one indicator of volatility is less than a predetermined threshold and another segment is available.