Capturing Inhalation Efficiency with Acoustic Sensors in Mobile Phones

Research output: Contribution to conferencePaperResearchpeer-review

Abstract

Increasing popularity of inhaled therapy for the treatment of asthma and chronic obstructive pulmonary disease (COPD) stimulates research on both drug formulations and smart devices to support efficient pulmonary drug delivery. A major concern is the variability of the drug dose delivered to the lungs from the inhalation devices, due to the following three factors: 1) the drug formulation, 2) the device design, and 3) the patient’s inhalation profile [23]. This paper investigates the use of microphones embedded in modern smartphones to accurately monitor the patient’s inhalation manouvre. In our experiments we focus on dry powder inhalers (DPIs) with a breath-activated capsule spinning mechanism, such as Breezhaler®. We design an algorithm to capture inhalation profiles and evaluate it against measurements obtained with a precise gas flow meter. Our algorithm achieves an average error of up to 4.89 slm (standard liters per minute) given typical inspiratory flow rates through a Breezhaler® between 60 and 130 slm. We detect capsule rotation to ensure the inhalation was effective, and observe that the capsule spinning mechanism helps reduce measurement errors by 2 slm. Given a proper calibration, the proposed algorithm can be used with other capsule-based DPIs, such as HandiHaler®.
Original languageEnglish
Number of pages6
Publication statusPublished - 4 Nov 2018
EventWorkshop on Real-World Embedded Wireless Systems and Networks - Southern University of Science and Technology, Shenzhen, China
Duration: 4 Nov 20184 Nov 2018
https://sites.google.com/site/realwsn2018/

Workshop

WorkshopWorkshop on Real-World Embedded Wireless Systems and Networks
Abbreviated titleRealWSN
CountryChina
CityShenzhen
Period4/11/184/11/18
Internet address

Fingerprint

Mobile phones
Acoustics
Sensors
Powders
Pulmonary diseases
Smartphones
Microphones
Measurement errors
Drug delivery
Flow of gases
Flow rate
Calibration
Experiments
Pharmaceutical Chemistry

Cite this

Saukh, O. (2018). Capturing Inhalation Efficiency with Acoustic Sensors in Mobile Phones. Paper presented at Workshop on Real-World Embedded Wireless Systems and Networks, Shenzhen, China.

Capturing Inhalation Efficiency with Acoustic Sensors in Mobile Phones. / Saukh, Olga.

2018. Paper presented at Workshop on Real-World Embedded Wireless Systems and Networks, Shenzhen, China.

Research output: Contribution to conferencePaperResearchpeer-review

Saukh, O 2018, 'Capturing Inhalation Efficiency with Acoustic Sensors in Mobile Phones' Paper presented at Workshop on Real-World Embedded Wireless Systems and Networks, Shenzhen, China, 4/11/18 - 4/11/18, .
Saukh O. Capturing Inhalation Efficiency with Acoustic Sensors in Mobile Phones. 2018. Paper presented at Workshop on Real-World Embedded Wireless Systems and Networks, Shenzhen, China.
Saukh, Olga. / Capturing Inhalation Efficiency with Acoustic Sensors in Mobile Phones. Paper presented at Workshop on Real-World Embedded Wireless Systems and Networks, Shenzhen, China.6 p.
@conference{839d27d7ef684ed8ae2acb86b5b76aa9,
title = "Capturing Inhalation Efficiency with Acoustic Sensors in Mobile Phones",
abstract = "Increasing popularity of inhaled therapy for the treatment of asthma and chronic obstructive pulmonary disease (COPD) stimulates research on both drug formulations and smart devices to support efficient pulmonary drug delivery. A major concern is the variability of the drug dose delivered to the lungs from the inhalation devices, due to the following three factors: 1) the drug formulation, 2) the device design, and 3) the patient’s inhalation profile [23]. This paper investigates the use of microphones embedded in modern smartphones to accurately monitor the patient’s inhalation manouvre. In our experiments we focus on dry powder inhalers (DPIs) with a breath-activated capsule spinning mechanism, such as Breezhaler{\circledR}. We design an algorithm to capture inhalation profiles and evaluate it against measurements obtained with a precise gas flow meter. Our algorithm achieves an average error of up to 4.89 slm (standard liters per minute) given typical inspiratory flow rates through a Breezhaler{\circledR} between 60 and 130 slm. We detect capsule rotation to ensure the inhalation was effective, and observe that the capsule spinning mechanism helps reduce measurement errors by 2 slm. Given a proper calibration, the proposed algorithm can be used with other capsule-based DPIs, such as HandiHaler{\circledR}.",
author = "Olga Saukh",
year = "2018",
month = "11",
day = "4",
language = "English",
note = "Workshop on Real-World Embedded Wireless Systems and Networks, RealWSN ; Conference date: 04-11-2018 Through 04-11-2018",
url = "https://sites.google.com/site/realwsn2018/",

}

TY - CONF

T1 - Capturing Inhalation Efficiency with Acoustic Sensors in Mobile Phones

AU - Saukh, Olga

PY - 2018/11/4

Y1 - 2018/11/4

N2 - Increasing popularity of inhaled therapy for the treatment of asthma and chronic obstructive pulmonary disease (COPD) stimulates research on both drug formulations and smart devices to support efficient pulmonary drug delivery. A major concern is the variability of the drug dose delivered to the lungs from the inhalation devices, due to the following three factors: 1) the drug formulation, 2) the device design, and 3) the patient’s inhalation profile [23]. This paper investigates the use of microphones embedded in modern smartphones to accurately monitor the patient’s inhalation manouvre. In our experiments we focus on dry powder inhalers (DPIs) with a breath-activated capsule spinning mechanism, such as Breezhaler®. We design an algorithm to capture inhalation profiles and evaluate it against measurements obtained with a precise gas flow meter. Our algorithm achieves an average error of up to 4.89 slm (standard liters per minute) given typical inspiratory flow rates through a Breezhaler® between 60 and 130 slm. We detect capsule rotation to ensure the inhalation was effective, and observe that the capsule spinning mechanism helps reduce measurement errors by 2 slm. Given a proper calibration, the proposed algorithm can be used with other capsule-based DPIs, such as HandiHaler®.

AB - Increasing popularity of inhaled therapy for the treatment of asthma and chronic obstructive pulmonary disease (COPD) stimulates research on both drug formulations and smart devices to support efficient pulmonary drug delivery. A major concern is the variability of the drug dose delivered to the lungs from the inhalation devices, due to the following three factors: 1) the drug formulation, 2) the device design, and 3) the patient’s inhalation profile [23]. This paper investigates the use of microphones embedded in modern smartphones to accurately monitor the patient’s inhalation manouvre. In our experiments we focus on dry powder inhalers (DPIs) with a breath-activated capsule spinning mechanism, such as Breezhaler®. We design an algorithm to capture inhalation profiles and evaluate it against measurements obtained with a precise gas flow meter. Our algorithm achieves an average error of up to 4.89 slm (standard liters per minute) given typical inspiratory flow rates through a Breezhaler® between 60 and 130 slm. We detect capsule rotation to ensure the inhalation was effective, and observe that the capsule spinning mechanism helps reduce measurement errors by 2 slm. Given a proper calibration, the proposed algorithm can be used with other capsule-based DPIs, such as HandiHaler®.

M3 - Paper

ER -