A VHDL Based Controller Design for Photoplethysmography-Based Heart Rate Monitoring System Kiet Duong, Dat Tran, and Ujjal Kumar Bhowmik Electrical Engineering and Computer Science Dept. Catholic University of America, Washington DC 20064, USA Email: bhowmik@cua.edu Abstract—Continuous monitoring of heat rate using wearable technology has the potential of improving healthcare and fitness and reducing the risk of cardiovascular diseases. A Photoplthysmography (PPG) based optical sensors are becoming popular to detect heart rate from human body. However, interfacing different sensors, acquiring and processing data in real time is a challenging task and requires dedicated hardware. Field Programmable Gate Array (FPGA) has become most widely used technology for real-time application. In this research, the necessary drivers and interfacing hardware for the PPG sensor are implemented on a FPGA platform using hardware description language (HDL). With the help of simulation and experimental results the accuracy and functionality of the proposed system are verified. Keywords—: Photoplthysmography (PPG), Heart-rate monitoring, FPGA, VHDL, Wearable healthcare. I. INTRODUCTION The emergence of micro-sensors and wireless technology has enabled changes in the conventional healthcare systems, replacing it with wearable technology. Wearable devices for measuring ambulatory heart rate becomes a new research topic in industry and academia. Several industries have recently introduced smart-watch and smart wrist-band for healthcare and fitness. Most of these smart devices use PPG based sensors to measure heart rate and other parameters from human body. Heart rate monitoring using PPG technology has many advantages compared to the conventional ECG, such as convenience in using, lower-cost, portability and continuous monitoring without any special assistance [1], [3], [4]. Recent advances in the optical technology, PPG based sensors are becoming more popular in clinical settings and fitness industries. However, integrating and interfacing different sensors in healthcare, fitness or other systems and acquiring and processing data in real time is a challenging task. The current trend in hardware design is implementing the complete design in a single chip. The FPGA based technology has become most successful and widely used technology for developing systems that require real-time signal processing [5]. In this research, the VHDL based hardware description language is used to design, implement the necessary interfacing hardware, controller, and signal processing units. The system is implemented and verified on an Altera DE2-115 FPGA board. During the development phases of our system, different signal processing modules are first designed using MATLAB. After successful implementation and verifications, the MATLAB code is converted to VHDL code using HDL-coder toolbox. A simulation software, ModelSim 10.3 PE, is also used for testing and verifying the functionality of different modules of our design. The rest of the paper is organized as follow. Section II describes briefly the TI AFE4400 heart rate sensor used in this research, section III discussed elaborately the PPG data acquisition system, section IV discusses the MATLAB implementation of necessary filters, section V discusses the three-stage signal processing section, and finally a brief conclusion is given in section VI. II. HEART RATE MONITOR AND PULSE OXIMETER SYSTEM The TI AFE4400 is a fully-integrated analog front-end (AFE) specifically designed for pulse oximetry applications [2]. The PPG data is obtained by illuminating the skin and measuring the changes in light absorption caused by the pulses (Figure 1). The sensor consists of a low-noise receiver channel with an integrated analog-to-digital converter (ADC) and LED driver. The device communicates with the host processor using SPI communication [2] [6]. The sensor has two working mode: reflection mode and transmission mode as illustrated by Fig 2. In this project, reflection mode is chosen over transmission mode since it can obtain data from more parts of the body while not requiring exact placement like the transmission mode does. A typical PPG signal is shown in figure 3. Figure 1. PPG signal acquisition Figure 2. Two modes of PPG operation 2015 International Conference on Computational Science and Computational Intelligence 978-1-4673-9795-7/15 $31.00 © 2015 IEEE DOI 10.1109/CSCI.2015.156 792 2015 International Conference on Computational Science and Computational Intelligence 978-1-4673-9795-7/15 $31.00 © 2015 IEEE DOI 10.1109/CSCI.2015.156 791