Pulse Signal System: Sensing, Data Acquisition and Body Area Network
Date
2017-08-28
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
ORCID
0000-0002-1905-6202
Type
Thesis
Degree Level
Masters
Abstract
Heart rate variability (HRV) is an important physiological signal of the human body, which
can serve as a useful biomarker for the cardiovascular health status of an individual. There are
many methods to measure the HRV using electrical devices, such as ECG and PPG etc. This work
presents a novel HRV detection method which is based on pressure detection on the human wrist.
This method has been compared with existing HRV detection methods.
In this work, the proposed system for HRV detection is based on polyvinylidene difluoride
(PVDF) sensor, which can measure tiny pressure on its surface. Three PVDF sensors are mounted
on the wrist, and a three-channel conditioning circuit is used to amplify signals generated by the
sensors. An analog-to-digital converter and Arduino microcontroller are used to sample and process
the signal. Based on the obtained signals, the HRV can be processed and detected by the
proposed PVDF-sensor-based system.
Another contribution of this work is in designing a wireless body area network (WBAN) to
transmit data acquired on the human body. This WBAN combines two different wireless network
protocols, for both efficient power consumption and data rate. Bluetooth Low Energy protocol is
used for transmitting data from the microcontroller to a personal device, and Wi-Fi is used to send
data to other terminals. This provides the potential for remote HRV signal monitoring.
A dataset consisting of two subjects was used to experimentally validate the proposed system
design and signal processing method. ECG signals are acquired from subjects with wrist pulse
signals for comparison as standard signal. The waveforms of ECG signals and wrist pulse signals
are compared and HRV values are calculated from these two signals separately. The result shows
that HRV calculated by wrist pulse has low error rate. A test of movement effect shows the sensor
can resist mild motions of wrist. Some future improvements of system design and further signal
processing methods are also discussed in the last chapter.
Description
Keywords
Wrist pulse, Body area network
Citation
Degree
Master of Science (M.Sc.)
Department
Electrical and Computer Engineering
Program
Electrical Engineering