# Deep learning enabled classification of real-time respiration signals acquired by MoSSe quantum dot-based flexible sensors.
> MoSSe量子ドットを用いたフレキシブルセンサーによる呼吸信号のリアルタイム深層学習分類


## Abstract

A flexible, disposable respiration sensor was developed using Janus-structured MoSSe quantum dots (MoSSe QDs), and its performance was evaluated alongside a deep learning classification framework. The MoSSe QD material demonstrated stable sensing characteristics under humid conditions, with electron affinity and work function analyses indicating a pronounced tendency to interact with hydrogen molecules. A one-dimensional convolutional neural network (1D CNN) was applied to classify four distinct breathing patterns—normal, slow, deep, and fast—achieving 10-trial classification accuracies of 98.18%, 95.25%, 97.64%, and 98.18%, respectively. The results suggest that this low-cost, biocompatible sensor platform holds promise for wearable personal health monitoring applications.

### Mechanism

The electron affinity and work function properties of MoSSe quantum dots confer a high tendency to donate electrons to hydrogen molecules, enabling stable respiration sensing even under humid conditions without significant changes in wear rate.

## Bibliographic

- **Authors**: Bokka N, Karhade J, Sahatiya P
- **Journal**: J Mater Chem B
- **Year**: 2021 (2021-09-14)
- **PMID**: [34612334](https://pubmed.ncbi.nlm.nih.gov/34612334/)
- **DOI**: [10.1039/d1tb01237a](https://doi.org/10.1039/d1tb01237a)
- **Study type**: other
- **Delivery route**: not specified
- **Effect reported**: not assessed

## Delivery context

The delivery route is not clearly identifiable from this paper. For hydrogen intake, inhalation is the most efficient route; inhalation, however, carries explosion risk (empirical LFL of 10%; high-concentration devices are not recommended).

## Safety notes

The delivery route is not clearly identifiable from this paper. For hydrogen intake, inhalation is the most efficient route; inhalation, however, carries explosion risk (empirical LFL of 10%; high-concentration devices are not recommended).

See also:
- [Inhalation concentration and LFL / UFL](https://h2-papers.org/en/safety-notes/inhalation-concentration)
- [Consumer Affairs Agency accident cases](https://h2-papers.org/en/safety-notes/accident-cases)

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> **Cite as**: H2 Papers — PMID 34612334. https://h2-papers.org/en/papers/34612334
> **Source**: PubMed PMID [34612334](https://pubmed.ncbi.nlm.nih.gov/34612334/)