Non-invasive Methods of Measuring Lung Volume (NIM-LV)

An Investigation Into the Measurement of Lung Volume by Analysis of Breathing Parameters Using Non-invasive Wearable Devices

Each breath humans take can be split into different measurements that clinicians can use to see how well a patient's lungs are working. Clinicians take these measurements to see how the lungs of patients with conditions such as asthma, chronic obstructive pulmonary disease or other muscle problems are affected. This also allows us to monitor how a patient's disease changes over time. At present, to measure lung volumes patients need to attend a clinic appointment and complete a test called spirometry. This takes both time and effort for patients and not all will be able to attend. There are simple devices available that can be attached to patients which measure breathing parameters such as breathing rate. Many different devices are available to do this; a common version is a chest band. These comprise of a tight-fitting band that is placed around the centre of the chest and as patients breathe in and out, the band stretches and contracts. The force of this stretching and contraction can be measured and turned in to a continuous breathing rate. Although this is useful, there is no device that can currently measure lung volumes as well as spirometry can. Therefore, the investigators will use software analysis to change data collected from two different chest bands to make the measurements comparable to spirometry testing. Doing this could mean that patients could test their breathing at home and any problems be picked up sooner. It would also help patients be more involved in the care of their breathing and may lead to earlier treatments. Our study is the first stage in developing this device, but the investigators hope that it will help with other research later.

Study Overview

• Status: Completed
• Conditions: Respiration Disorders
• Intervention / Treatment: Other: Respiratory monitoring band

Detailed Description

The study design was chosen so that the investigators can directly compare results produced from wearable respiratory devices to spirometry. In order to do this in a protocolised manner, pulmonary function testing (PFT) clinic was chosen as the location of the study. Prior to the protocol being agreed, this was discussed and approved by the medical and nursing team in charge of the pulmonary function clinic. The investigators also approached patients in PFT clinic to discuss the proposed protocol and if they felt it was suitable for someone attending the clinic. The investigators received positive responses form this and any comments were considered in the final protocol.

Potential participants will be identified when they are booking into their clinic appointment. All patients will be attending PFT clinic as part of their clinical care; none will be attending as part of the study only. Patients will be asked if they would like to participate in the study after receiving the patient information leaflet and given time to ask any questions. The investigators aim to recruit 50 patients. This was deemed a suitable number to be able to undertake machine learning analysis with sufficient data. The investigators aim to recruit these 50 patients by attending PFT clinic weekly for approximately 3 months. They will vary the days of the week/clinic times they attend to gain a range of different patient groups as PFT clinics vary across the week.

After participants are fully consented, baseline data will be collected. This will involve a medical questionnaire that they will be asked to complete. The following data will be collected using the questionnaire:

Patient demographics: Age, sex, height, weight Comorbidities including past medical and surgical history Smoking status Alcohol status Current medications used Allergy status Reason for spirometry testing

Once the questionnaire is completed the participants will start the measurement section of the study. They will have two respiratory measurement devices attached. The Go Direct Respiration Sensor and a biosignal respiratory belts will both be fitted over light clothing so that participants will wear both sensors at once. They work in different ways but both use chest movement during breathing to determine respiratory effort and respiratory rate. They fit as bands around the chest. The investigators will aim to place the devices in similar positions in all participants (around the centre of the chest at the breast bone). Before confirming their placement, participants will be asked if the devices are comfortable and allow for normal breathing. These devices will track chest movement for the duration of the spirometry test and during timed activities of sitting, speaking, and walking. Once fitted, participants will continue with their spirometry appointment as planned. Some results from their spirometry testing will be noted in a secure database. This will include their inspiratory reserve volume, expiratory reserve volume, tidal volume and forced expiratory volume. The values alone will be recorded with no other patient data from the clinic appointment. At the end of the appointment, once they are back at baseline breathing, participants will be asked to read a short standardised script (in the form of a simple poem) over the course of 1-2 minutes that will allow us to analyse breathing patterns during speech. This will be coordinated with audio recordings of the speech which will be used in later data analysis of speech breathing. This may occur in the clinic room or another quiet room opposite the clinic depending on clinic timings. The final task before removal of the devices will be a short walk down the corridor outside of the clinical room to assess breathing during light exercise. This will be a set distance of 75 meters and should take around 1 minute to complete. Variability in timing of the walk will be accepted due to different patient walking speeds. The total data collection will take approximately 30 minutes. There should not be any additional clinic time required as the speech assessment and walking assessment can be undertaken outside of the clinic room. When the devices are removed, participants will be asked if they wish to comment on anything they felt during the study including discomfort from wearing the devices. The spirometry data will be collected by the PFT team as part of their routine testing and as such should not be influenced by the study. The researcher will not be involved in the spirometry testing portion of the study and therefore should not bias any results obtained.

Once the bands are removed the data will be downloaded onto a secure laptop with all patient identifying information removed. Following the collection of data for all 50 patients, the investigators aim to spend a further 1-2 months analysing the data and comparing it to the spirometry results. The final report will be available within 24 months of the study start date.

There will not be any planned interim analysis.

• Study Type: Interventional
• Enrollment (Actual): 50
• Phase: Not Applicable

Contacts and Locations

Study Locations

• United Kingdom
  • Southampton, United Kingdom
    • PFT

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult; Older Adult
• Accepts Healthy Volunteers: Yes

Description

Inclusion Criteria:

• Subject: Human participants
• Gender: Any
• Aged 18 years and over.
• Able to give informed consent in English.
• Physically able to take part including a simple walking exercise
• Either in a asymptomatic participant group or planned for spirometry testing

Exclusion Criteria:

• Significant chest deformity or having a medical device fitted in (e.g. Implantable cardioverter defibrillator (ICD), Spinal cord stimulator, Pacemaker, etc)
• Pregnant
• Unable/uncomfortable to use a chest belt device for any reason.
• Patients <18 years old
• Unable to read and speak in English to an understandable level
• Unable to walk (aided or unaided) for 1 minute

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Basic Science
• Allocation: N/A
• Interventional Model: Single Group Assignment
• Masking: None (Open Label)

Number of Arms

1

Arms and Interventions

Participant Group / Arm

Intervention / Treatment

Experimental: Patients undergoing planned pulmonary function testing; Participants will be recruited from patients attending a planned pulmonary function clinic appointment. They will be invited to participate when they are booking into clinic. Should they agree to participate the will have the following interventions: Basic medical questionnaire; 2x chest band devices fitted over clothing They will then undertake their planned clinic appointment. No additional resources will be required for this. Once they have finished their clinic appointment, the investigators will ask them to read a short script whilst recording their speech. Following this the investigators will ask them to walk 75m down the hall. The devices will then be removed and the study time is over.

Other: Respiratory monitoring band; The only intervention in this study is the application of two CE marked study approved chest bands- the Go direct respiratory sensor and a biosignal respiration belt; Other Names: Go Direct Respiration Sensor; biosignal respiratory belt

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Data extraction from respiratory band devices using machine learning modelling	Data will be extracted using machine learning modelling to form respiratory parameters	From enrollment to one year post data collection to allow for data extraction and analysis time
Measurement of Tidal volume (in mL) using machine learning techniques	Tidal volume will be extracted from respiratory band devices using machine learning techniques	From enrollment to one year post data collection to allow for data extraction and analysis time
Measurement of Inspiratory Reserve Volume (in L) using machine learning techniques	Inspiratory reserve volume will be extracted from respiratory band devices using machine learning techniques	From enrollment to one year post data collection to allow for data extraction and analysis time
Measurement of Expiratory reserve volume (in L) using machine learning techniques	Expiratory reserve volume will be extracted from respiratory band devices using machine learning techniques	From enrollment to one year post data collection to allow for data extraction and analysis time
Measurement of Forced vital capacity (in L) using machine learning techniques	Forced vital capacity will be extracted from respiratory band devices using machine learning techniques	From enrollment to one year post data collection to allow for data extraction and analysis time

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Accuracy and reliability of the respiratory parameters formed using machine learning techniques in comparison to spirometry	By wearing the devices at the same time as pulmonary function testing, it will allow for a direct comparison of respiratory rates and respiratory parameters (as described in primary outcomes).	From enrolment to one year post data collection to allow for data extraction and analysis time
Direct comparison of machine learning results formed from the two devices against spirometry	As the two devices will be worn at the same time, the investigators will be able to compare each device individually to determine if there are differences between the devices and their data.	From enrollment to one year post data collection to allow for data extraction and analysis time
Analysis of how breathing patterns and respiratory volumes change with speech using data collected from two wearable respiratory devices	Whilst wearing the devices we will record a short speech and then analyse the breathing patterns with auditory analysis and transcription.	From enrollment to one year post data collection to allow for data extraction and analysis time
Analysis of different disease severities and patient demographics and their impact on non-invasive breathing measurement		From enrollment to one year post data collection to allow for data extraction and analysis time

Collaborators and Investigators

• Sponsor: University Hospital Southampton NHS Foundation Trust
• Collaborators: University of Southampton

Publications and helpful links

General Publications

• Brochard L, Martin GS, Blanch L, Pelosi P, Belda FJ, Jubran A, Gattinoni L, Mancebo J, Ranieri VM, Richard JC, Gommers D, Vieillard-Baron A, Pesenti A, Jaber S, Stenqvist O, Vincent JL. Clinical review: Respiratory monitoring in the ICU - a consensus of 16. Crit Care. 2012 Dec 12;16(2):219. doi: 10.1186/cc11146.
• Mateu-Mateus, M., et al., Camera-Based Method for Respiratory Rhythm Extraction From a Lateral Perspective. IEEE Access, 2020. 8: p. 154924-154939.
• Lin, Y.-A., et al., Respiration Monitoring using a Motion Tape Chest Band and Portable Wireless Sensing Node. Journal of Commercial Biotechnology, 2022. 27.
• Ross R, Mongan WM, O'Neill P, Rasheed I, Fontecchio A, Dion G, Dandekar KR. An Adaptively Parameterized Algorithm Estimating Respiratory Rate from a Passive Wearable RFID Smart Garment. Proc COMPSAC. 2021 Jul;2021:774-784. doi: 10.1109/COMPSAC51774.2021.00110. Epub 2021 Sep 9.
• Vitazkova D, Foltan E, Kosnacova H, Micjan M, Donoval M, Kuzma A, Kopani M, Vavrinsky E. Advances in Respiratory Monitoring: A Comprehensive Review of Wearable and Remote Technologies. Biosensors (Basel). 2024 Feb 6;14(2):90. doi: 10.3390/bios14020090.
• Pierce R. Spirometry: an essential clinical measurement. Aust Fam Physician. 2005 Jul;34(7):535-9.
• Flesch JD, Dine CJ. Lung volumes: measurement, clinical use, and coding. Chest. 2012 Aug;142(2):506-510. doi: 10.1378/chest.11-2964.
• Bhakta NR, McGowan A, Ramsey KA, Borg B, Kivastik J, Knight SL, Sylvester K, Burgos F, Swenson ER, McCarthy K, Cooper BG, Garcia-Rio F, Skloot G, McCormack M, Mottram C, Irvin CG, Steenbruggen I, Coates AL, Kaminsky DA. European Respiratory Society/American Thoracic Society technical statement: standardisation of the measurement of lung volumes, 2023 update. Eur Respir J. 2023 Oct 12;62(4):2201519. doi: 10.1183/13993003.01519-2022. Print 2023 Oct. Erratum In: Eur Respir J. 2023 Nov 29;62(5):2251519. doi: 10.1183/13993003.51519-2022.

Helpful Links

• Go direct respiration belt
• Biosignal sensor belt

Study record dates

Study Major Dates

• Study Start (Actual): November 20, 2024
• Primary Completion (Actual): May 19, 2025
• Study Completion (Actual): May 19, 2025

Study Registration Dates

• First Submitted: November 4, 2024
• First Submitted That Met QC Criteria: November 7, 2024
• First Posted (Actual): November 8, 2024

Study Record Updates

• Last Update Posted (Actual): May 22, 2025
• Last Update Submitted That Met QC Criteria: May 19, 2025
• Last Verified: November 1, 2024

More Information

Terms related to this study

• Keywords: machine learning; pulmonary function test; tidal volume; chest band; wearable monitoring device
• Additional Relevant MeSH Terms: Respiratory Tract Diseases; Respiration Disorders
• Other Study ID Numbers: RHM CRI0461; 349993 (Registry Identifier: IRAS)

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO
• IPD Plan Description: The data will be collected and collated as part of a PhD project. The final data will aim to be published but this will be a summary of the participants. There is no plan to share data before the study is complete.

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No
• product manufactured in and exported from the U.S.: No