A Low-Cost Breath Analyzer Module in Domiciliary Non-Invasive Mechanical Ventilation for Remote COPD Patient Monitoring

Abstract

Smart Breath Analyzers were developed as sensing terminals of a telemedicine architecture devoted to remote monitoring of patients suffering from Chronic Obstructive Pulmonary Disease (COPD) and home-assisted by non-invasive mechanical ventilation via respiratory face mask. The devices based on different sensors (CO₂/O₂ and Volatile Organic Compounds (VOCs), relative humidity and temperature (R.H. & T) sensors) monitor the breath air exhaled into the expiratory line of the bi-tube patient breathing circuit during a noninvasive ventilo-therapy session; the sensor raw signals are transmitted pseudonymized to National Health Service units by TCP/IP communication through a cloud remote platform. The work is a proof-of-concept of a sensors-based IoT system with the perspective to check continuously the effectiveness of therapy and/or any state of exacerbation of the disease requiring healthcare. Lab tests in controlled experimental conditions by a gas-mixing bench towards CO₂/O₂ concentrations and exhaled breath collected in a sampling bag were carried out to test the realized prototypes. The Smart Breath Analyzers were also tested in real conditions both on a healthy volunteer subject and a COPD suffering patient.

Keywords: COPD; exhaled breath; noninvasive ventilation; patient monitoring; sensors.

Figure 1

Respiratory gases (CO₂ and O₂) and Volatile Organic Compounds (VOCs) exchange within alveoli. CO₂/O₂ exchanges are approximated by the gas alveolar formula: P_AO₂ = (P_B − PH₂O) × F_iO₂ − (P_ACO₂/R), where P_B is the barometric pressure, P_AH₂O is the water vapor pressure (usually 47 mmHg), F_iO₂ is the fractional concentration of inspired oxygen, and R is the respiratory quotient, dependent on metabolic activity and diet and is considered to be about 0.825). VOC exchanges depend on blood-air partition coefficients (λ_b:a).

Figure 2

Scheme of the connection of the device to the expiratory line of the bi-tube breathing circuit.

Figure 3

(a) 3D rendered model of the gas tight cell; (b) front and back views of MultiSense board.

Figure 4

Device architecture.

Figure 5

Realized unboxed prototype.

Figure 6

Device firmware overview.

Figure 7

Auto-ranging circuit schematic.

Figure 8

Network architecture (example with 4 devices).

Figure 9

Calibration runs for O₂ and CO₂ sensor.

Figure 10

Breath Analyzer Module connected to bi-tube breathing circuit in real operating condition during clinical experimentation in hospital setting.

Figure 11

(left) Traces of all the sensor during a noninvasive ventilation (NIV) session with supplemental oxygen therapy; (right) magnification of a temporal segment during the trace recording. The vertical dotted green lines indicate the start and the end of the NIV session. The measurements refer to the first day of hospitalization of a Chronic Obstructive Pulmonary Disease (COPD) patient due to an exacerbation event.

Figure 12

Traces of all the sensors during a NIV session with supplemental oxygen therapy; the vertical dotted green lines indicates the start and the end of the NIV session. The measurements refer to a hospitalization day following the first day of hospitalization (following that reported in Figure 11).

Figure 13

Exhaled measured and estimated CO₂ concentration values monitored during a NIV session of the patient (a) in the first day of hospitalization and (b) in a hospitalization day following the first day. (c,d) are respectively magnified views of (a,b). The estimated CO₂ values are calculated from the measured CO₂ by coarse estimate by considering the volumetric dilution effect due to the dead space of the breathing circuit and of the water trap.

Figure 13

Exhaled measured and estimated CO₂ concentration values monitored during a NIV session of the patient (a) in the first day of hospitalization and (b) in a hospitalization day following the first day. (c,d) are respectively magnified views of (a,b). The estimated CO₂ values are calculated from the measured CO₂ by coarse estimate by considering the volumetric dilution effect due to the dead space of the breathing circuit and of the water trap.