Semantic Scholar Open Access 2014 709 sitasi

TROIKA: A General Framework for Heart Rate Monitoring Using Wrist-Type Photoplethysmographic Signals During Intensive Physical Exercise

Zhilin Zhang Zhouyue Pi Benyuan Liu

Lihat Sumber DOI

Abstrak

Heart rate monitoring using wrist-type photoplethysmographic signals during subjects' intensive exercise is a difficult problem, since the signals are contaminated by extremely strong motion artifacts caused by subjects' hand movements. So far few works have studied this problem. In this study, a general framework, termed TROIKA, is proposed, which consists of signal decomposiTion for denoising, sparse signal RecOnstructIon for high-resolution spectrum estimation, and spectral peaK trAcking with verification. The TROIKA framework has high estimation accuracy and is robust to strong motion artifacts. Many variants can be straightforwardly derived from this framework. Experimental results on datasets recorded from 12 subjects during fast running at the peak speed of 15 km/h showed that the average absolute error of heart rate estimation was 2.34 beat per minute, and the Pearson correlation between the estimates and the ground truth of heart rate was 0.992. This framework is of great values to wearable devices such as smartwatches which use PPG signals to monitor heart rate for fitness.

Topik & Kata Kunci

Engineering Medicine Computer Science

Penulis (3)

Zhilin Zhang

Zhouyue Pi

Benyuan Liu

Format Sitasi

APA MLA BibTeX

Zhang, Z., Pi, Z., Liu, B. (2014). TROIKA: A General Framework for Heart Rate Monitoring Using Wrist-Type Photoplethysmographic Signals During Intensive Physical Exercise. https://doi.org/10.1109/TBME.2014.2359372

Akses Cepat

Lihat di Sumber doi.org/10.1109/TBME.2014.2359372

Informasi Jurnal

Tahun Terbit: 2014
Bahasa: en
Total Sitasi: 709×
Sumber Database: Semantic Scholar
DOI: 10.1109/TBME.2014.2359372
Akses: Open Access ✓