Development and Evaluation of a Wristwatch-Type Photoplethysmography Array Sensor Module

In this paper, we address a new photoplethysmography (PPG) signal-sensing method using a wristwatch-type PPG array sensor. According to the development of the ubiquitous health care system, the many types of medical equipment and treatments have been improved. In conventional PPG signal-sensing appr...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:IEEE sensors journal 2013-05, Vol.13 (5), p.1459-1463
Hauptverfasser: Lee, Yong Kwi, Jo, Jun, Shin, Hyun Soon
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext bestellen
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:In this paper, we address a new photoplethysmography (PPG) signal-sensing method using a wristwatch-type PPG array sensor. According to the development of the ubiquitous health care system, the many types of medical equipment and treatments have been improved. In conventional PPG signal-sensing approaches, the finger-type PPG probe has been used. However, the finger-type PPG probe requires tight fitting that restricts movement, meaning that patients should endure dome discomfort while wearing it. To solve this problem, we propose a novel PPG array sensor module with a wristwatch-type design. The proposed module measures the PPG signal from the radial artery and the ulnar artery of the wrist, whereas previous methods obtained it from the capillaries of the skin. Moreover, we place phototransistors and infrared-emitting diodes in an array form to improve the PPG signal sensitivity and level of accuracy. Various arrays are considered for optimization, and a conductive rubber wristband is employed to reduce external noise. In the experiments, the proposed module is assessed and compared with the commercial product. This comparison between the commercial finger-type probe dataset and the PPG array module wrist-type probe dataset shows that the degree of similarity between the two signals is greater than 91.2%.
ISSN:1530-437X
1558-1748
DOI:10.1109/JSEN.2012.2235424