enrich_BP
This algorithm enriches RIP signals and accompanying breath onsets into breath-by-breath breathing pattern (depth, coordination, and more)
Dual-band wearables (such as respiratory inductance plethysmography; RIP) can provide various information on breathing pattern beyond simply frequency and depth. This algorithm receives one or two RIP signals and pre-processed breath onsets (inspiration and expiration) and outputs a breath-by-breath timetable with new metrics: breathing frequency, depth, sighing events, and, in the case of dual-RIP, % ribcage contribution, and thoraco-abdominal coordination (phase angle). Accompanying scientific references are embedded.
This work was funded by the Austrian Federal Ministry for Climate Action, Environment, Energy, Mobility, Innovation, and Technology (BMK) within the projects Motion Data Intelligence Lab (Contract: 2021-0.641.557) and DiMo-NEXT (Digital Motion in Sports, Fitness and Well-being). DiMo-NEXT is additionally funded by the Federal Ministry for Labour and Economy (BMAW), and the provinces of Salzburg, Upper Austria, and Tyrol within the framework of COMET – Competence Centres for Excellent Technologies. COMET is processed by The Austrian Research Promotion Agency (FFG).
引用格式
Eric (2026). enrich_BP (https://ww2.mathworks.cn/matlabcentral/fileexchange/183728-enrich_bp), MATLAB Central File Exchange. 检索时间: .
Harbour, Eric, et al. “Enhanced Breathing Pattern Detection during Running Using Wearable Sensors.” Sensors, vol. 21, no. 16, Aug. 2021, p. 5606, https://doi.org/10.3390/s21165606.
