Algorithm for automatic forced spirometry quality assessment: technological developments

Umberto Melia, Felip Burgos, Montserrat Vallverdú, Filip Velickovski, Magí Lluch-Ariet, Josep Roca, Pere Caminal, Umberto Melia, Felip Burgos, Montserrat Vallverdú, Filip Velickovski, Magí Lluch-Ariet, Josep Roca, Pere Caminal

Abstract

We hypothesized that the implementation of automatic real-time assessment of quality of forced spirometry (FS) may significantly enhance the potential for extensive deployment of a FS program in the community. Recent studies have demonstrated that the application of quality criteria defined by the ATS/ERS (American Thoracic Society/European Respiratory Society) in commercially available equipment with automatic quality assessment can be markedly improved. To this end, an algorithm for assessing quality of FS automatically was reported. The current research describes the mathematical developments of the algorithm. An innovative analysis of the shape of the spirometric curve, adding 23 new metrics to the traditional 4 recommended by ATS/ERS, was done. The algorithm was created through a two-step iterative process including: (1) an initial version using the standard FS curves recommended by the ATS; and, (2) a refined version using curves from patients. In each of these steps the results were assessed against one expert's opinion. Finally, an independent set of FS curves from 291 patients was used for validation purposes. The novel mathematical approach to characterize the FS curves led to appropriate FS classification with high specificity (95%) and sensitivity (96%). The results constitute the basis for a successful transfer of FS testing to non-specialized professionals in the community.

Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Figure 1. Spirometer Zones.
Figure 1. Spirometer Zones.
An example of FV curve with five zones described.
Figure 2. Spirometer metrics.
Figure 2. Spirometer metrics.
Metrics involved in the traditional criteria: (A) FVC and FEV1, (B) PEFT.
Figure 3. Zone Z1 analysis.
Figure 3. Zone Z1 analysis.
An example of a FV curve that presents irregularity on the ascent to the PEF.
Figure 4. Zone Z2 analysis.
Figure 4. Zone Z2 analysis.
Examples of FV curves that present (A) bimodal peak; (B) flat peak and (C) slow peak.
Figure 5. Zone Z3 analysis.
Figure 5. Zone Z3 analysis.
Examples of FV curves that present irregularity in the descent from PEF.
Figure 6. Zone Z4 analysis.
Figure 6. Zone Z4 analysis.
Example of FT curve that present irregularity in the final part.
Figure 7. Zone Z5 analysis.
Figure 7. Zone Z5 analysis.
Examples of FV curve with peak and valley.

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