# MoRe-Fi: Motion-robust and Fine-grained Respiration Monitoring via Deep-Learning UWB Radar

arXiv: https://arxiv.org/abs/2111.08195 · HTML: https://mlsanity.com/paper/2111.08195/

## Key facts

- Cited by 11 papers in the map (data through 14 Oct 2026).
- Builds on 16 of its 94 references that are in the map.
- First posted on arXiv 16 Nov 2021.

## Builds on (most cited first, 16 of 16)

- [PyTorch: An Imperative Style, High-Performance Deep Learning Library](https://mlsanity.com/paper/1912.01703/) (2019)
- [Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift](https://mlsanity.com/paper/1502.03167/) (2015)
- [Auto-Encoding Variational Bayes](https://mlsanity.com/paper/1312.6114/) (2013)
- [Variational Inference: A Review for Statisticians](https://mlsanity.com/paper/1601.00670/) (2016)
- [Variational Autoencoders and Nonlinear ICA: A Unifying Framework](https://mlsanity.com/paper/1907.04809/) (2019)
- [Deep Complex Networks](https://mlsanity.com/paper/1705.09792/) (2017)
- [TasNet: time-domain audio separation network for real-time, single-channel speech separation](https://mlsanity.com/paper/1711.00541/) (2017)
- [How good is my GAN?](https://mlsanity.com/paper/1807.09499/) (2018)
- [On weight initialization in deep neural networks](https://mlsanity.com/paper/1704.08863/) (2017)
- [Learning Longer-term Dependencies in RNNs with Auxiliary Losses](https://mlsanity.com/paper/1803.00144/) (2018)
- [RF-Net: a Unified Meta-learning Framework for RF-enabled One-shot Human Activity Recognition](https://mlsanity.com/paper/2111.04566/) (2021)
- [A Study of Complex Deep Learning Networks on High Performance, Neuromorphic, and Quantum Computers](https://mlsanity.com/paper/1703.05364/) (2017)
- [SiWa: See into Walls via Deep UWB Radar](https://mlsanity.com/paper/2110.14279/) (2021)
- [V2iFi: in-Vehicle Vital Sign Monitoring via Compact RF Sensing](https://mlsanity.com/paper/2110.14848/) (2021)
- [Enhancing RF Sensing with Deep Learning: A Layered Approach](https://mlsanity.com/paper/2110.14849/) (2021)
- [A Recurrent Encoder-Decoder Approach with Skip-filtering Connections for Monaural Singing Voice Separation](https://mlsanity.com/paper/1709.00611/) (2017)

## Built on by (most cited first, 11 of 11)

- [RFBoost: Understanding and Boosting Deep WiFi Sensing via Physical Data Augmentation](https://mlsanity.com/paper/2410.07230/) (2024)
- [CardiacMamba: A Multimodal RGB-RF Fusion Framework with State Space Models for Remote Physiological Measurement](https://mlsanity.com/paper/2502.13624/) (2025)
- [PhysDrive: A Multimodal Remote Physiological Measurement Dataset for In-vehicle Driver Monitoring](https://mlsanity.com/paper/2507.19172/) (2025)
- [Large Model for Small Data: Foundation Model for Cross-Modal RF Human Activity Recognition](https://mlsanity.com/paper/2410.19766/) (2024)
- [Towards White-Box Deep Wireless Sensing](https://mlsanity.com/paper/2507.21799/) (2025)
- [RPM-Distill: Physiology-guided Adaptive Cross-modal Distillation for Robust Remote Physiological Measurement](https://mlsanity.com/paper/2606.28089/) (2026)
- [Thermal Imaging and Radar for Remote Sleep Monitoring of Breathing and Apnea](https://mlsanity.com/paper/2407.11936/) (2024)
- [Tracing Human Stress from Physiological Signals using UWB Radar](https://mlsanity.com/paper/2410.10155/) (2024)
- [MobiVital: Self-supervised Time-series Quality Estimation for Contactless Respiration Monitoring Using UWB Radar](https://mlsanity.com/paper/2503.11064/) (2025)
- [mmWave-Diffusion:A Novel Framework for Respiration Sensing Using Observation-Anchored Conditional Diffusion Model](https://mlsanity.com/paper/2603.20700/) (2026)
- [RF-LEGO: Modularized Signal Processing-Deep Learning Co-Design for RF Sensing via Deep Unrolling](https://mlsanity.com/paper/2604.10183/) (2026)

## Abstract (arXiv)

Crucial for healthcare and biomedical applications, respiration monitoring often employs wearable sensors in practice, causing inconvenience due to their direct contact with human bodies. Therefore, researchers have been constantly searching for contact-free alternatives. Nonetheless, existing contact-free designs mostly require human subjects to remain static, largely confining their adoptions in everyday environments where body movements are inevitable. Fortunately, radio-frequency (RF) enabled contact-free sensing, though suffering motion interference inseparable by conventional filtering, may offer a potential to distill respiratory waveform with the help of deep learning. To realize this potential, we introduce MoRe-Fi to conduct fine-grained respiration monitoring under body movements. MoRe-Fi leverages an IR-UWB radar to achieve contact-free sensing, and it fully exploits the complex radar signal for data augmentation. The core of MoRe-Fi is a novel variational encoder-decoder network; it aims to single out the respiratory waveforms that are modulated by body movements in a non-linear manner. Our experiments with 12 subjects and 66-hour data demonstrate that MoRe-Fi accurately recovers respiratory waveform despite the interference caused by body movements. We also discuss potential applications of MoRe-Fi for pulmonary disease diagnoses.