This paper presents a novel integrated data compression and pulse rate measurement scheme for power reduction in Internet-of-Things (IoT) enabled wireless PPG monitoring devices. In the proposed scheme, the recorded photoplethysmograph (PPG) signal is compressed using the differential pulse code modulation and Huffman coding techniques and then the pulse rate (PR) is simultaneously extracted from the differential signal, which is the difference between the original and predicted signals. The proposed scheme achieves an average compression ratio, percentage root-mean-squared difference (PRD), signal-to-noise ratio (SNR), and normalized cross correlation (NCC) of 4.76, 0.19%, 27.90 dB and 0.9991 respectively for the 5 s PPG signals digitized with a sampling rate of 100 Hz and resolution of 12 bits, on the three standard PPG databases (MIT-BIH SLP, MIMIC-II and CSL). Evaluation results show that the method yields peak detection rates of 98.94% and average PR measurement error of 0-2.6 samples. The proposed integrated scheme can enable timely measurement of the pulse rate (PR) and to significantly reduce the overall power consumption and therefore it is highly suited for IoT wireless wearable PPG sensors. © 2018 IEEE.