Title: Adaptive proportional-derivative adjuster for notch filtering in wearable ECG monitoring

Authors: Chao-Ting Chu; Jia-Wei Chang

Addresses: Chunghwa Telecom Laboratories, Internet of Things Laboratory, Yangmei District, Taoyuan City, Taiwan ' Department of Computer Science and Information Engineering, National Taichung University of Science and Technology, Taichung City, Taiwan

Abstract: This paper presents an adaptive proportional-derivative adjuster (APDA) integrated into a notch filter for processing ECG signals in wearable smart clothing. The APDA filter dynamically adjusts parameters - such as gain and cutoff frequency - in real time to mitigate environmental interference, including 60 Hz noise and electromyographic signals common in workplaces and fitness centres. Unlike traditional fixed-parameter filters, this adaptive method minimises noise and preserves ECG clarity under varying conditions. A notable contribution of this study is optimising the APDA algorithm for resource-constrained microcontrollers, reducing both memory requirements and processing power. This streamlined computation lowers complexity and extends battery life, making it suitable for continuous, long-term monitoring. Experimental results from a smart clothing prototype validate the filter's effectiveness in suppressing noise while maintaining signal integrity, offering an energy-efficient and cost-effective solution for wearable healthcare applications. This advancement addresses the limitations of conventional designs and shows promising potential for future clinical applications.

Keywords: adaptive filtering; proportional-derivative control; wearable ECG monitoring; real-time noise suppression; sustainable healthcare technology.

DOI: 10.1504/IJWGS.2025.150156

International Journal of Web and Grid Services, 2025 Vol.21 No.3/4, pp.308 - 327

Received: 30 Aug 2024
Accepted: 30 Jan 2025
Published online: 02 Dec 2025 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article