MétaCan
Menu
Back to cohort
Record W4407909434 · doi:10.2196/59532

Contactless Breathing Monitoring at Home and in the Hospital: Protocol for a Low-Cost Frequency-Modulated Continuous-Wave Radar-Based Device

2025· article· en· W4407909434 on OpenAlexvenueno aff
Arnav Hari, Brijesh Kumbhani, Sam Darshi, Satyam Agarwal, J. S. Sahambi, Suksham Jain, Deepak Chawla

Bibliographic record

VenueJMIR Research Protocols · 2025
Typearticle
Languageen
FieldEngineering
TopicNon-Invasive Vital Sign Monitoring
Canadian institutionsnot available
Fundersnot available
KeywordsBreathingRadarSIGNAL (programming language)ApneaReal-time computingComputer scienceVital signsRespiratory rateContinuous monitoringAcousticsMedicineTelecommunicationsEngineeringHeart ratePhysicsAnesthesia

Abstract

fetched live from OpenAlex

BACKGROUND: Contactless monitoring of vital signs, especially the breathing of children, in the hospital is performed on a priority basis because their organs and immune system are immature. Therefore, continuous monitoring of their vital signs with a sensor that is directly attached to their body is not possible, as it irritates the sensitive newborn skin and causes discomfort. A contactless frequency-modulated continuous-wave (FMCW) radar-based device can wirelessly monitor the breathing rate and pattern of a child in the hospital or at home. Signal-processing capability can be added to this device to process breathing data and analyze the apnea condition arising due to irregular breathing patterns. OBJECTIVE: This study will develop a contactless FMCW radar-based system to accurately monitor the breathing rate and pattern of neonates and infants in hospitals and at home in order to provide a noninvasive, nonintrusive and contactless alternative to conventional sensor-based methods and address a critical need in neonatal care, potentially improving health outcomes for vulnerable infants. METHODS: The radar transmits a signal toward the body, and the time taken by the signal received to travel from the body to the receiving antenna is analyzed. This time is proportional to the distance between the radar and the body, and the breathing pattern is recognized as a slight, periodic variation in this distance. We will use this concept with multiple antenna systems to monitor the breathing of neonates with improved sensitivity. The radar-based device will be installed, in addition to conventional breathing monitors, in the neonatal intensive care unit. The signals received at the radar and the respiration signals from conventional monitors will be recorded in a database. Signal-processing techniques will be applied to extract breathing signals from the signals received at the radar. RESULTS: This study was funded in January 2023 by the Science and Engineering Research Board (SERB) of India. The device was designed by May 2024, and a working proof-of concept was verified in the Indian Institute of Technology (IIT) Ropar laboratory. Implementation of the proposed method for initial study began in December 2024. Results are expected to be published in the first quarter of 2025. CONCLUSIONS: The contactless FMCW radar-based system will provide reliable estimation of the breathing rate and pattern, which is close to the conventional reference device values most of the time. Our device will also provide a seamless breathing-monitoring system to be used both in hospitals and at home for newborns and premature babies until they are fully healthy and fit. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/59532.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.191
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.115
GPT teacher head0.449
Teacher spread0.335 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreProtocol

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations5
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueJMIR Research ProtocolsSame topicNon-Invasive Vital Sign MonitoringFrench-language works237,207