Photoplethysmographic Time-Domain Heart Rate Measurement Algorithm for Resource-Constrained Wearable Devices and its Implementation.

Marek Wójcikowski,Bogdan Pankiewicz

doi:10.3390/s20061783

Abstract

This paper presents an algorithm for the measurement of the human heart rate, using photoplethysmography (PPG), i.e., the detection of the light at the skin surface. The signal from the PPG sensor is processed in time-domain; the peaks in the preprocessed and conditioned PPG waveform are detected by using a peak detection algorithm to find the heart rate in real time. Apart from the PPG sensor, the accelerometer is also used to detect body movement and to indicate the moments in time, for which the PPG waveform can be unreliable. This paper describes in detail the signal conditioning path and the modified algorithm, and it also gives an example of implementation in a resource-constrained wrist-wearable device. The algorithm was evaluated by using the publicly available PPG-DaLia dataset containing samples collected during real-life activities with a PPG sensor and accelerometer and with an ECG signal as ground truth. The quality of the results is comparable to the other algorithms from the literature, while the required hardware resources are lower, which can be significant for wearable applications.

Highlights

Advancements in modern technologies enabled field monitoring of some parameters of human health [1]; for example, heart monitoring is used for off-hospital monitoring and in fitness and professional sport activities
The database contains signals collected from a PPG sensor, accelerometer, and ECG, where the ECG is used as ground truth
As described in [15], ground truth heart rate values were obtained from an ECG signal processed by R-peak detection algorithm [21]

Summary

Introduction

Advancements in modern technologies enabled field monitoring of some parameters of human health [1]; for example, heart monitoring is used for off-hospital monitoring and in fitness and professional sport activities. The intensity of the reflected light depends on the absorption of the skin, which depends on the blood volume supplied to the tissues In this way, the received signal contains information about the current blood supply to the vessels near the measuring device. There are two main approaches used: time-domain sophisticated filtering and frequency-domain processing Both are often accompanied by a movement sensor (accelerometer) for movement-based artefacts/spectrum removal. The proposed solution of time-domain heart rate measurement algorithm (TDHR) consists of three main blocks: signal conditioning, peak detection, and heart-rate-measuring blocks. A two-stage input-signal-conditioning digital nonlinear filtering block with limiter; Application of the AMPD algorithm for HR peak detection; Modification of the AMPD algorithm toward efficient implementation in low-power resource-constrained hardware; The proposition of a time-domain heart-rate-measuring algorithm with an accelerometer-based false measurement removal.

Signal Conditioning

Elimination of the patient’s detection: signal

Evaluation on Dataset

Implementation

Discussion and Conclusions