A Sensor for Spirometric Feedback in Ventilation Maneuvers during Cardiopulmonary Resuscitation Training

Abstract

This work proposes adapting an existing sensor and embedding it on mannequins used in cardiopulmonary resuscitation (CPR) training to accurately measure the amount of air supplied to the lungs during ventilation. Mathematical modeling, calibration, and validation of the sensor along with metrology, statistical inference, and spirometry techniques were used as a base for aquiring scientific knowledge of the system. The system directly measures the variable of interest (air volume) and refers to spirometric techniques in the elaboration of its model. This improves the realism of the dummies during the CPR training, because it estimates, in real-time, not only the volume of air entering in the lungs but also the Forced Vital Capacity (FVC), Forced Expiratory Volume (FEVt) and Medium Forced Expiratory Flow (FEF20–75%). The validation of the sensor achieved results that address the requirements for this application, that is, the error below 3.4% of full scale. During the spirometric tests, the system presented the measurement results of (305 ± 22, 450 ± 23, 603 ± 24, 751 ± 26, 922 ± 27, 1021 ± 30, 1182 ± 33, 1326 ± 36, 1476 ± 37, 1618 ± 45 and 1786 ± 56) × 10−6 m3 for reference values of (300, 450, 600, 750, 900, 1050, 1200, 1350, 1500, 1650 and 1800) × 10−6 m3, respectively. Therefore, considering the spirometry and pressure boundary conditions of the manikin lungs, the system achieves the objective of simulating valid spirometric data for debriefings, that is, there is an agreement between the measurement results when compared to the signal generated by a commercial spirometer (Koko brand). The main advantages that this work presents in relation to the sensors commonly used for this purpose are: (i) the reduced cost, which makes it possible, for the first time, to use a respiratory volume sensor in medical simulators or training dummies; (ii) the direct measurement of air entering the lung using a noninvasive method, which makes it possible to use spirometry parameters to characterize simulated human respiration during the CPR training; and (iii) the measurement of spirometric parameters (FVC, FEVt, and FEF20–75%), in real-time, during the CPR training, to achieve optimal ventilation performance. Therefore, the system developed in this work addresses the minimum requirements for the practice of ventilation in the CPR maneuvers and has great potential in several future applications.

A Brazilian native bee (Tetragonisca angustula) dataset for computer vision

“…However, currently available datasets exhibit multi-scale properties [ [5] , [6] , [7] ], are characterized by classes imbalance [ [5] , [6] , [7] , [8] , 10 ], include few bee species [ [5] , [6] , [7] , [10] , [11] , [12] , [13] , [14] , [15] , [16] , [17] , [18] , [19] , [20] , [21] ], contain a small number of bee samples [ [5] , [6] , [7] , [8] , [9] , 13 , 16 , 18 , 20 , 21 ], lack sufficient standardized and labeled data [ [5] , [6] , [7] , 13 , 15 , 16 , 18 , 20 , 21 ], and have restricted accessibility [ [5] , [6] , [7] , [12] , [13] , [14] , [16] , [17] , [18] , [19] , [20] ], agreeing with [ 3 , 4 ]. The dataset presented in this work overcomes most of these challenges except for including a few bee species, which we aim to address in future work with other case studies and supports our previous study about multiple objects tracking in native beehives [ 1 ].…”

“…On the other hand, automated annotations do not require a biologist, as the objects of interest are pre-marked. These annotations comprise the following: first, we applied the EuTrack model [ 1 ] to the videos for automated annotations, and then we followed the same procedure as conducted by the biologist.…”

“…Predominantly, studies have centered on Apis mellifera, with a limited number [ 19 , 20 ] addressing Brazilian native bees like ours. Only our dataset includes labeled images and metadata to assist in management, alongside video labels conforming to the benchmark outlined in [ 1 ].…”

A portable triboelectric spirometer for wireless pulmonary function monitoring

“…Conventional spirometers are categorized into volume-measurement and flow-measurement types (Graham et al, 2019;Leocadio et al, 2019). Compared to volume spirometers, flow spirometers are more compact, allowing for better adaptability to any minimization of test instruments.…”

Estimation of peak expiratory flow rate in young Indians.

“…[7][8][9][10] Os valores de referência TPFE publicados variam de população para população. [11][12][13][14][15] Poucos investigadores estabeleceram que a utilização de dados de referência derivados de outras populações cria interpretações erradas na população indiana. 16 Apesar disso, as equações derivadas da população ocidental ainda se encontram na prática na Índia.…”