An apparatus (100, 700) for estimating blood pressure, the apparatus comprising: a bio-signal acquirer (110, 710) configured to acquire a photoplethysmography, PPG, signal, wherein the PPG signal is composed of a superposition of propagation waves and reflection waves; and a processor (120, 720) configured to extract a value of one or more first features from the PPG signal, wherein the one or more first features are associated with cardiac output, CO, total peripheral resistance, TPR, or a combination thereof, wherein the processor is further configured to determine a scale factor based on the value of the one or more first features, wherein the scale factor is a coefficient for adjusting a scale of the extracted value of the one or more first features, wherein the apparatus for estimating blood pressure is configured to determine that the value of the one or more first features belongs to a homoeostasis maintaining region when a variation in the value of the one or more first features is greater than a variation in the PPG signal, determine that the value of the one or more first features belongs to a linear change region when a correlation between the variation in the value of the one or more first features and the variation in the PPG signal is greater than or equal to a predetermined correlation value, and determine that the value of the one or more first features belongs to a non-linear saturation region when the correlation between the variation in the value of the one or more first features and the variation in the PPG signal is less than the predetermined correlation value, wherein the apparatus for estimating blood pressure is further configured to adjust the scale factor by: (i) decreasing the scale factor when it is determined that the value of the one or more first features belongs to the homoeostasis maintaining region, (ii) determining a predetermined reference scale factor to be the scale factor when it is determined that the value of the one or more first features belongs to the linear change region, (iii) applying the value of the one or more first features to a bio-information estimation model, which is pre-generated by a non-linear function or machine learning, when it is determined that the value of the one or more first features belongs to the non-linear saturation region, wherein the processor is further configured to estimate the blood pressure based on the adjusted scale factor and the extracted value of the one or more first features. a bio-signal acquirer (110, 710) configured to acquire a photoplethysmography, PPG, signal, wherein the PPG signal is composed of a superposition of propagation waves and reflection waves; and a processor (120, 720) configured to extract a value of one or more first features from the PPG signal, wherein the one or more first features are associated with cardiac output, CO, total peripheral resistance, TPR, or a combination thereof, wherein the processor is further configured to determine a scale factor based on the value of the one or more first features, wherein the scale factor is a coefficient for adjusting a scale of the extracted value of the one or more first features, wherein the apparatus for estimating blood pressure is configured to determine that the value of the one or more first features belongs to a homoeostasis maintaining region when a variation in the value of the one or more first features is greater than a variation in the PPG signal, determine that the value of the one or more first features belongs to a linear change region when a correlation between the variation in the value of the one or more first features and the variation in the PPG signal is greater than or equal to a predetermined correlation value, and determine that the value of the one or more first features belongs to a non-linear saturation region when the correlation between the variation in the value of the one or more first features and the variation in the PPG signal is less than the predetermined correlation value, wherein the apparatus for estimating blood pressure is further configured to adjust the scale factor by: (i) decreasing the scale factor when it is determined that the value of the one or more first features belongs to the homoeostasis maintaining region, (ii) determining a predetermined reference scale factor to be the scale factor when it is determined that the value of the one or more first features belongs to the linear change region, (iii) applying the value of the one or more first features to a bio-information estimation model, which is pre-generated by a non-linear function or machine learning, when it is determined that the value of the one or more first features belongs to the non-linear saturation region, (i) decreasing the scale factor when it is determined that the value of the one or more first features belongs to the homoeostasis maintaining region, (ii) determining a predetermined reference scale factor to be the scale factor when it is determined that the value of the one or more first features belongs to the linear change region, (iii) applying the value of the one or more first features to a bio-information estimation model, which is pre-generated by a non-linear function or machine learning, when it is determined that the value of the one or more first features belongs to the non-linear saturation region, wherein the processor is further configured to estimate the blood pressure based on the adjusted scale factor and the extracted value of the one or more first features.